Polaris IP, LLC v. Google Inc. et al

Filing 392

SEALED MOTION for Summary Judgment of Invalidity by AOL, LLC., America Online, Inc., Google Inc., Yahoo!, Inc.. (Attachments: # 1 Affidavit of Todd Kennedy, # 2 Exhibit A, # 3 Exhibit B, # 4 Exhibit C, # 5 Exhibit D, # 6 Exhibit E, # 7 Exhibit F, # 8 Exhibit G, # 9 Exhibit H, # 10 Exhibit I, # 11 Exhibit J, # 12 Exhibit K, # 13 Exhibit L, # 14 Exhibit M, # 15 Exhibit N, # 16 Exhibit O, # 17 Affidavit of Bradley Allen, # 18 Exhibit A, part 1 of 2, # 19 Exhibit A, part 2 of 2, # 20 Exhibit B)(Perlson, David) Modified on 7/2/2010 (ch, ). (Additional attachment(s) added on 7/2/2010: # 21 Text of Proposed Order) (ch, ).

Polaris IP, LLC v. Google Inc. et al

Doc. 392

IN THE UNITED STATES DISTRICT COURT FOR THE EASTERN DISTRICT OF TEXAS MARSHALL DIVISION BRIGHT RESPONSE, LLC F/K/A POLARIS IP, LLC v. GOOGLE INC., et al.

NO. 2:07-CV-371-TJW-CE JURY TRIAL DEMANDED Filed Under Seal

DEFENDANTS' MOTION FOR SUMMARY JUDGMENT OF INVALIDITY UNDER 35 U.S.C. § 102(b), (e), and § 103(a)

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Dockets.Justia.com

TABLE OF CONTENTS Page INTRODUCTION ...........................................................................................................................1 STATEMENT OF ISSUES TO BE DECIDED BY THE COURT ................................................2 STATEMENT OF UNDISPUTED FACTS ....................................................................................2 I. II. THE `947 PATENT DISCLOSES A COMBINATION OF PRIOR ART RULE BASE AND CASE BASE REASONING. ..........................................................................2 THE PRIOR ART EZ READER RESPONDED TO ELECTRONIC MESSAGES USING A RULE BASE AND CASE BASE KNOWLEDGE ENGINE . ..........................4 A. B. C. D. III. Chase Deployed The EZ Reader Before April 1996. ..............................................4 The EZ Reader Received, Interpreted, and Automatically Responded to Electronic Messages from Chase Customers. ..........................................................6 No Disclosure of EZ Reader in an Information Disclosure Statement. ...................7 Bright Response Has No Opinion Regarding the Accuracy of Veracity of the EZ Reader Article. .............................................................................................8

ALLEN DISCLOSES RESPONDING TO NON-INTERACTIVE ELECTRONIC MESSAGES USING A RULE BASE AND CASE BASE KNOWLEDGE ENGINE. ..............................................................................................................................8

LEGAL STANDARD....................................................................................................................10 ARGUMENT .................................................................................................................................11 I. THE EZ READER ANTICIPATES THE ASSERTED CLAIMS. ...................................11 A. The EZ Reader Practiced Every Element of Independent Claim 26. ....................12 1. The EZ Reader practiced "[a] method for automatically processing a non-interactive electronic message using a computer" (Claim 26, preamble). ..................................................................................................12 The EZ Reader practiced "receiving the electronic message from a source" (Claim 26(a)). ...............................................................................13 The EZ Reader practiced "interpreting the electronic message using a rule base and case base knowledge engine" (Claim 26(b)). ..........13

2. 3.

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4.

The EZ Reader practiced "retrieving one or more predetermined responses corresponding to the interpretation of the electronic message from a repository for automatic delivery to the source" (Claim 26(c)). .............................................................................................14

B.

The EZ Reader Practiced Dependent Claims 28, 30, 31, 33, and 38. ....................14 1. 2. 3. 4. 5. The EZ Reader practiced each limitation of Claim 28. .............................14 The EZ Reader practiced each limitation of Claim 30. .............................16 The EZ Reader practiced Claim 31. ...........................................................18 The EZ Reader practiced the normalization of Claim 33. .........................18 The EZ Reader practiced altering the predetermined response "in accordance with the interpretation of the electronic message before delivery to the source." (Claim 38.) ...........................................................19

C. II.

The Rice Testimony Does Not Create a Genuine Issue of Material Fact. .............19

ALLEN INVALIDATES THE ASSERTED CLAIMS. ....................................................21 A. Allen Discloses the Elements of Independent Claim 26. .......................................21 1. 2. 3. 4. Allen discloses "[a] method for automatically processing a noninteractive electronic message using a computer" (Claim 26)...................21 Allen describes "receiving the electronic message from a source" (Claim 26[a]). .............................................................................................22 Allen describes "interpreting the electronic message using a rule base and case base knowledge engine" (Claim 26[b])...............................23 Allen describes "retrieving one or more predetermined responses corresponding to the interpretation of the electronic message from a repository for automatic delivery to the source" (Claim 26[c]). .............23

B.

Allen Anticipates Dependent Claims 28, 30, 31, and 38. ......................................24 1. 2. 3. 4. Allen meets each of the limitations of Claim 28........................................24 Allen discloses each limitation of Claim 30. .............................................25 Allen Discloses Each Limitation of Claim 31. ..........................................27 Allen Disclose Each Limitation of Claim 38. ............................................28

C.

Claims 26, 30, and 33 of the `947 Patent Are Also Obvious. ................................28

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1. 2.

Allen Renders Obvious Claims 26 and 30 of the `947 patent....................28 Allen in Light of the CBR Express Documentation Renders Obvious Claim 33. .....................................................................................29

CONCLUSION ..............................................................................................................................30

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TABLE OF AUTHORITIES Page Cases Arthrocare Corp. v. Smith & Nephew, Inc., 406 F.3d 1365 (Fed. Cir. 2005)................................................................................................23 BLS Joint Venture v. Bank Home Savings Assoc., 985 F.2d 556 (5th Cir. 1993) ...................................................................................................21 Callaway Golf Co. v. Acushnet Co., 576 F.3d 1331 (Fed. Cir. 2009)..........................................................................................27, 28 KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398 (2007) .....................................................................................................11, 29, 30 Kinzenbaw v. Deere & Co., 741 F.2d 383 (Fed. Cir. 1984)..................................................................................................11 In re Kubin, 561 F.3d 1351 (Fed. Cir. 2009)..........................................................................................29, 30 Leggett & Platt, Inc. v. Vutek, Inc., 537 F.3d 1349 (Fed. Cir. 2008)................................................................................................11 Netscape Commc'ns Corp. v. Konrad, 295 F.3d 1315 (Fed. Cir. 2002)................................................................................................11 New Railhead Mfg., L.L.C. v. Vermeer Mfg. Co., 298 F.3d 1290 (Fed. Cir. 2002)................................................................................................12 Schering Corp. v. Geneva Pharms., Inc., 339 F.3d 1373 (Fed. Cir. 2003)................................................................................................11 Sinskey v. Pharmacia Ophthalmics, Inc., 982 F.2d 494 (Fed. Cir. 1992)..................................................................................................21 In re Smith, 714 F.2d 1127 (Fed. Cir. 1983)................................................................................................11 White v. Dunbar, 119 U.S. 47 (1886) ...................................................................................................................23 Statutes 35 U.S.C. § 102(b) .....................................................................................................1, 2, 10, 11, 21 35 U.S.C. § 102(e) .......................................................................................................................1, 2 35 U.S.C. § 102(e)(2)...............................................................................................................11, 22

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35 U.S.C. § 103 ........................................................................................................................11, 29 35 U.S.C. § 103(a) ...........................................................................................................................2 35 U.S.C. § 111(b)(8) ......................................................................................................................8 Federal Rule of Civil Procedure 56 ...............................................................................................21 Rule 30(b)(6)....................................................................................................................................8

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NOTES ON CITATIONS The patent-in-suit, U.S. Patent No. 6,411,947 ("the `947 patent"), is attached as Exhibit A to the Declaration of Todd Kennedy, executed on July 1, 2010. References to the `947 patent are indicated by column and line number, or by claim number. A reference to "3:15" means column 3, line 15. Citations to "Allen Decl. Ex. __" refer to exhibits attached to the Declaration of Bradley Allen, executed on June 28, 2010 and filed herewith. The other exhibits, which are attached to the Declaration of Todd Kennedy, are as follows: Exhibit Description B C D E F G H I J K L M N O "EZ Reader: Embedded AI for Automatic Electronic Mail Interpretation and Routing," AAAI Press / The MIT Press (1996) U.S. Patent No. 5,581,664 to Bradley P. Allen et al. Excerpts of the transcript of the November 13, 2009 deposition of Anthony Angotti Excerpts of the transcript of the July 9, 2009 deposition of Rosanna Piccolo Excerpts of the transcript of the March 19, 2010 deposition of Amy Rice Declaration of Amy Rice, bearing document control numbers RICE001403-06 Plaintiff's Objections and Supplemental Responses to Defendants' First Set of Interrogatories, dated April 29, 2010 Excerpts of the transcript of the June 3, 2010 deposition of Bradlee Sheafe Plaintiff's Objections and Responses to Google's Second Set of Interrogatories Plaintiff's Objections and Responses to Yahoo's First Set of Interrogatories A document entitled "The Eighth Annual Innovative Applications of Artificial Intelligence Conference: Call for Papers, Panels, and Invited Talks." "EZ Reader User's Guide and Reference Manual," dated February 5, 1996 and bearing document control numbers JPM00313-51 and JPM00001-21 U.S. Provisional Application No. 60/042,494 Declaration of Amy Rice, dated June 9, 1998 and bearing document control numbers RICE000034.

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INTRODUCTION The `947 patent describes a system of automatically responding to "non-interactive electronic messages" by interpreting such messages using a rule base and case base knowledge engine and retrieving predetermined responses based on that interpretation. The alleged "innovation" of the `947 patent was well-known in the prior art--in fact, there are many references, three of which are discussed herein, that either anticipate or render obvious all the claims of the `947 patent. First, the claims are invalid under 35 U.S.C. § 102(b) because, through the "EZ Reader" software application, every limitation of the asserted claims was in public use in the United States more than one year before the patent was filed. The EZ Reader, developed by some of the named inventors of the `947 patent, was a software application used to receive, interpret, and respond to email messages sent by actual customers of Chase Manhattan Bank ("Chase") before April 1996--more than one year prior to the filing date of the application leading to the `947 patent. A 1996 publication entitled "EZ Reader: Embedded AI for Automatic Electronic Mail Interpretation and Routing" confirms that the EZ Reader was used to respond to actual customer emails in this timeframe. Notably, the EZ Reader article was filed as U.S. Provisional Application No. 60/042,494 on April 3, 1997. The `947 patent (and Plaintiff) claim priority to the `494 application. Thus, there can be no dispute the Article discloses that EZ Reader met every asserted claim of the `947 patent. Second, claims 28, 30, 31, and 38 are invalid under 35 U.S.C. § 102(e) because they were disclosed in the Allen reference, U.S. Patent No. 5,581,664. Allen, filed on May 23, 1994, discloses a "help desk application" that allows a customer service representative to obtain advice about technical problems. The first line of the Abstract confirms that, like the `947 patent, Allen did so through "[a] case-based reasoning system which is smoothly integrated into a rule-based reasoning system, thus coordinating case-based reasoning techniques and rule-based reasoning techniques in a unified automated reasoning system . . ." (`664 patent, Abstract (emphasis added).)

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Third, claim 33, and to the extent not anticipated, claims 26 and 30 are obvious under 35 U.S.C. 103(a) in light of Allen and documentation describing CBR Express, a software application whose user's guide is incorporated by reference into Allen. There are no genuine issues of material fact about either the date of public use and application, or the scope and content of these prior art references. Accordingly, summary judgment of invalidity under 35 U.S.C. § 102(b), (e), and § 103(a) is appropriate. STATEMENT OF ISSUES TO BE DECIDED BY THE COURT 1. Whether the public use of the EZ Reader in the first quarter of 1996 invalidates

claims 28, 30, 31, 33, and 38 of the `947 patent under 35 U.S.C. § 102(b); 2. Whether claims 28, 30, 31, 33, and 38 of the `947 patent are anticipated by Allen

under 35 U.S.C. § 102(e) or are rendered obvious by Allen either alone or in view of the CBR Express documentation pursuant to 35 U.S.C. § 103(a). STATEMENT OF UNDISPUTED FACTS I. THE `947 PATENT DISCLOSES A COMBINATION OF PRIOR ART RULE BASE AND CASE BASE REASONING. 1. The `947 patent, entitled "Automatic Message Interpretation and Routing

System," was filed on April 2, 1998, and names Amy Rice, Julie Hsu, Anthony M. Angotti, Rosanna M. Piccolo, and Fred R. Cohen as inventors. (Ex. A.) The patent describes a method for responding to a "non-interactive electronic message" using "rule-based reasoning" and "casebased reasoning." (1:60-2:67; 3:24-42.) 2. The `947 patent's specification confirms that both rule-based reasoning and case-

based reasoning were known in the art. The specification states that U.S. Patent No. 5,555,346 to Gross et al. describes "[a]n event driven rule based messaging system." (1:60-63.) The specification further states that "[a] help desk application utilizing a case based reasoning system, see U.S. Pat. No. 5,581,664 to Allen et al., has been described which compares an

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incoming set of facts (a "Problem") with a stored set of exemplar cases (a case base)." (2:4144.) 3. The invention of the `947 patent maintains a repository of past messages received

and responses sent ("case models"). (7:40-47.) The specification describes an embodiment in the form of an email autoresponder. (4:20-28.) When a new email message is received, the system analyzes its content and compares it to the case models in its repository to find the most similar prior received message. (8:37-9:2.) The system then replicates the action taken in response to that case model. (9:11-15.) For example, the system may retrieve the predetermined (i.e. canned) response associated with that case model, and automatically forward it to the sender of the message, perhaps with some modifications based on the content of the received message. (9:24-35.) Thus, if a bank customer sends a message inquiring about opening a new savings account, the system might interpret the message, retrieve a previous such inquiry, and automatically send back a canned response containing instructions for opening a new savings account, with the sender's name inserted into the salutation. 4. Claim 26 states:

A method for automatically processing a non-interactive electronic message using a computer, comprising the steps of: (a) (b) (c) receiving the electronic message from a source; interpreting the electronic message using a rule base and case base knowledge engine; and retrieving one or more predetermined responses corresponding to the interpretation of the electronic message from a repository for automatic delivery to the source. The dependant claims add additional limitations regarding how messages are

5.

interpreted and classified, and how case models are used.

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6.

Bright Response asserts that Defendants infringe claims 28, 30, 31, 33, and 38 of

the `947 patent. 7. The `947 patent was filed on April 2, 1998 and claims priority to provisional

applications filed on April 3, 1997 and April 4, 1997. Bright Response contends that April 3, 1997 is the priority date of the asserted claims of the `947 patent. (Ex. I at 190:18-191:5.) II. THE PRIOR ART EZ READER RESPONDED TO ELECTRONIC MESSAGES USING A RULE BASE AND CASE BASE KNOWLEDGE ENGINE . A. 8. Chase Deployed The EZ Reader Before April 1996. In 1993, Chase Manhattan Bank began exploring technology that would enable it

to process and respond to incoming electronic messages from customers. (Ex. D at 50:14-51:2; 53:14-21.) Chase selected a company called Brightware to help develop that technology, which ultimately became known as the EZ Reader system. (Id. at 50:9-51:2.) Development of the EZ Reader system began by the middle of 1995. (Id. at 62:24-63:6.) The development team included employees of Chase and Brightware. 9. EZ Reader was deployed publicly and was used to interpret and respond to

electronic messages in the first quarter of 1996. (Ex. D at 66:20-68:10, 107:15-18; 109:10-21; 122:21-123:7; 164:10-15; 167:11-15; 167:22-168:3; 170:8-12; 175:2-176:5.) This public use and functionality of the EZ Reader system is documented in a 1996 publication entitled "EZ Reader: Embedded AI for Automatic Electronic Mail Interpretation and Routing," which was submitted to the American Association for Artificial Intelligence ("AAAI") for publication as part of the Thirteenth National Conference on Artificial Intelligence. (Ex. B at BR001250-51.) Named inventors Angotti, Rice, Hsu, and Piccolo were the named authors of the publication. (Ex. B.)

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10.

The official Call for Papers that was issued for the conference states that papers

were due on January 17, 1996. (Ex. L.) A document entitled "EZ Reader User's Guide and Reference Manual" is dated February 6, 1996, and refers to the EZ Reader Article as already having been submitted. (Ex. M at JPM00314, JPM00020.) The EZ Reader User's Guide also states that it describes EZ Reader, "currently in use by the ChaseDirect unit of Chase Manhattan Bank." (Id. at JPM00318.) 11. of 1996: The EZ Reader Article confirms that EZ Reader was deployed in the first quarter

(Ex. B at BR001252 (highlight added).) As explained by Anthony Angotti, the purpose of the first-quarter (January-March) 1996 deployment of EZ Reader was to "legitimize the application and to demonstrate under fire . . . that it was capable of doing the things that we were claiming that it would do." (Ex. D at 175:7-10.) When it was deployed, it was implemented in a Chase production environment "to legitimize the [software] and to prove that it worked." (Id. at 17576, 167-68 (defining "first quarter of 1996")). The EZ Reader Article states that EZ Reader enabled ChaseDirect "to reduce the number of emails that needed manual processing by more than 80%, with an accuracy rate of 95%," and "to provide rapid turnaround time for return messages to customers and prospects and consistency in responses." (Ex. B at BR001253.) The article also states that "EZ Reader eliminated manual intervention for a percentage of messages and more than halved the time to process messages requiring manual intervention." (Id. at BR001259.) "The reduction in manual intervention allowed ChaseDirect to turn around email responses faster to customers." (Id.)

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12.

The EZ Reader Article was filed as the `494 provisional application on April 3,

1997. (Ex. N.) The `947 patent claims priority to the `494 provisional application (1:9-11.), and Plaintiff contends the `947 patent is entitled to this date. (Ex. I at 190:18-191:5.) B. 13. The EZ Reader Received, Interpreted, and Automatically Responded to Electronic Messages from Chase Customers. The EZ Reader Article describes how the EZ Reader was used to receive,

interpret, and respond to electronic messages sent by Chase customers. The article contains the following flow diagram of the process of EZ Reader's retrieval, interpretation, using rule base and case base reasoning, classification, and responding to an incoming email:

(Ex. B at 1509 (annotations added).) 14. Using rule-based reasoning, EZ Reader would "extract features or characteristics

of the email that help distinguish the content of the message." (Ex B at 1512-13.) "For example,

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if EZ Reader infers from incoming email text that the sender does not want to be telephoned by ChaseDirect, the rule for do-not-call-customer? fires and sets that attribute in the case to `Yes.'" (Id.) Then, EZ Reader would apply case-based reasoning. (Id.) To do so, the EZ Reader would prepare a case model of the customer's message, and compare the attributes and text of that case model to the attributes and text of previously stored case models of messages. (Id. at 1512.) "If the value in a feature of the stored email matches the value in the corresponding feature of the incoming email, the feature's match weight is add[ed] to the stored email's score." (Id.) On the other hand, "[i]f the feature's value mismatches, the feature's mismatch weight, typically a negative value, is added to the score." (Id.) 15. Depending on its interpretation of the message, the EZ Reader would either

determine that it could respond to the message automatically, or that the message would need to be routed to a human operator review and response. (Ex. B.) If the message could be responded to automatically, EZ Reader would retrieve a prepared response from a repository of standard responses. (Id. at 1509.) EZ Reader would then send the standard response, or an adapted version of the response, to the customer. (Id. at 1512.) On the other hand, if the message required human review, EZ Reader would route the message, along with a suggested reply, to a human operator, who could review the message and either send the suggested reply or compose a different reply. (Id. at 1509.) C. 16. No Disclosure of EZ Reader in an Information Disclosure Statement. Although the EZ Reader Article and a portion of the EZ Reader Users Guide (that

omitted its February 1996 date) were submitted as provisional applications to the `947 patent, neither the EZ Reader system nor the EZ Reader article were disclosed in an Information Disclosure Statement, nor is there any indication that the Examiner was aware of the deployment of the EZ Reader in the first quarter of 1996. Indeed, provisional patent applications are not -7-

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even examined. See MPEP 601 ([N]o substantive examination is made [of provisional applications]."). See also 35 U.S.C. § 111(b)(8) (providing that provisional applications are not subject to 35 U.S.C. 131, which provides for examination of patents). D. 17. Bright Response Has No Opinion Regarding the Accuracy of Veracity of the EZ Reader Article. During a Rule 30(b)(6) deposition, Bright Response's corporate designee, Bradlee

Sheafe, testified that Bright Response does not know anything about the EZ Reader project besides what the article states, and that Bright Response "has no opinion on the accuracy or veracity of the document." (Id. at 193:25-194:12.) III. ALLEN DISCLOSES RESPONDING TO NON-INTERACTIVE ELECTRONIC MESSAGES USING A RULE BASE AND CASE BASE KNOWLEDGE ENGINE. 18. U.S. Patent No. 5,581,664, entitled "Case-based reasoning system," issued to

inventors Bradley P. Allen and Daniel Lee on December 3, 1996 and was filed on May 23, 1994. (Id.) The first line of the abstract discloses the combination of case-based reasoning and rulebased reasoning: "A case-based reasoning system which is smoothly integrated into a rule-based reasoning system, thus coordinating case-based reasoning techniques and rule-based reasoning techniques in a unified automated reasoning system . . . ." (Ex. C at Abstract.) 19. Allen describes an embodiment used in a "help desk application" to enable a

customer service representative to retrieve advice about a technical problem. The patent describes the process by which the invention receives, interprets, and responds to electronic messages. (See Ex. C at 3:59-4:27; Fig. 2.) 20. The first step of the process is the "description step." In that step, the customer

service representative enters data relating to a technical problem using a user interface. (Ex. C at 3:59-64.) The system then retrieves that data. (Id.) Then, in the "case-matching step," the system uses case-based reasoning and "attempts to match the problem to one or more cases 105 -8-

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in the case base 104." (Id. at 3:66-4:1.) In the preferred embodiment, this process is accomplished using a "feature-matching" technique, in which notable parameters of the problem are compared with those of stored case models of the case base. (Id. at 4:1-3, 5:3-6.) 21. In the preferred embodiment described by Allen, the "inference engine 111 for the

case-based reasoning system 101 may be implemented within a rule-based reasoning system 501." (Ex C at 7:8-10.) Accordingly, "rules 103 may be matched against software objects 112, including a set of facts 502, cases 105 and the case template 312, and may perform procedural actions on them." (Id. at 7:13-17.) Allen depicts the hybrid case-based and rule-based reasoning system in Figure 5:

(Ex. C at Fig. 5 (annotations added).)

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22.

In the "best-case step," the system "evaluate(s) the cases 105 which were found in

the case-matching step 202, and determine a `best' case 204 to match the problem." (Ex. C at 4:4-7.) Allen describes how case-based reasoning and rule-based reasoning are used in conjunction to interpret the description of the problem entered by the user and retrieve the best case:

(Ex. C at 8:5-18 (highlight added).) If the customer's description of the problem is matched to a stored case, the system sends "an advice message 607 to the customer service representative 602, who may then provide advice to the customer 604" without requiring additional information from the customer. (Id. at 9:17-29.) 23. The `947 patent's specification refers to Allen in the "Background of the

Invention" section as "[a] help desk application utilizing a case based reasoning system." (2:4142.) The applicants omitted, however, that Allen discloses a hybrid case-based and rule-based system. (Id.) Nor did the applicants disclose Allen in an Information Disclosure Statement during prosecution, and there is nothing in the prosecution history to indicate the Examiner ever actually reviewed the Allen reference. LEGAL STANDARD Under the patent statute, a person is not entitled to a patent if "the invention was...in public use or on sale in this country, more than one year prior to the date of the application for patent in the United States." 35 U.S.C. § 102(b). Public use includes "any use of [the claimed] -10-

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invention by a person other than the inventor who is under no limitation, restriction or obligation of secrecy to the inventor." In re Smith, 714 F.2d 1127, 1134 (Fed. Cir. 1983). Courts look to the totality of the circumstances when evaluating whether there has been a "public" use within the meaning of § 102(b). Netscape Commc'ns Corp. v. Konrad, 295 F.3d 1315, 1320 (Fed. Cir. 2002) (affirming summary judgment of patent invalidity). Commercial exploitation is a clear indication of public use. Kinzenbaw v. Deere & Co., 741 F.2d 383, 390 (Fed. Cir. 1984). A patent is also invalid if the invention was described in "a patent granted on an application for patent by another filed in the United States before the invention by the applicant for patent." 35 U.S.C. § 102(e)(2). A patent is invalid for anticipation if a single prior art reference discloses each and every limitation of the claimed invention." Schering Corp. v. Geneva Pharms., Inc., 339 F.3d 1373, 1377 (Fed. Cir. 2003). Anticipation, `it may be decided on summary judgment if the record reveals no genuine dispute of material fact.'" Leggett & Platt, Inc. v. Vutek, Inc., 537 F.3d 1349 1352 (Fed. Cir. 2008) (affirming summary judgment of anticipation). A patent is invalid as obvious "if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains." 35 U.S.C. § 103. The Supreme Court has instructed that "[w]here . . . the content of the prior art, the scope of the patent claim, and the level of ordinary skill in the art are not in material dispute, and the obviousness of the claim is apparent in light of these factors, summary judgment is appropriate." KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398, 427 (2007). "The ultimate judgment of obviousness is a legal determination." Id. ARGUMENT I. THE EZ READER ANTICIPATES THE ASSERTED CLAIMS. The asserted claims of the `947 patent are invalid under 35 U.S.C. § 102(b) based on Chase's first-quarter 1996 public use of the EZ Reader, more than one year prior to the earliest claimed filing date of the `947 patent, April 3, 1997. As detailed above in the Statement of

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Undisputed Facts, (supra ¶¶ 8-12), the EZ Reader Article--which was filed with the April 3, 1997 `494 Provisional Application--detailed the public use of the EZ Reader before April 1996. This public use was fully corroborated by named inventor Angotti and other contemporaneous documents. Further, as Plaintiff relies on the `494 Provisional Application as establishing an April 3, 1997 priority date for the asserted claims, Plaintiff cannot dispute that, as demonstrated below, the EZ Reader Article discloses all the elements of the asserted claims. See New Railhead Mfg., L.L.C. v. Vermeer Mfg. Co., 298 F.3d 1290, 1294 (Fed. Cir. 2002) ("[F]or the non-provisional utility application to be afforded the priority date of the provisional application, . . . the written description of the provisional must adequately support the claims of the nonprovisional application."). A. The EZ Reader Practiced Every Element of Independent Claim 26.1 1. The EZ Reader practiced "[a] method for automatically processing a noninteractive electronic message using a computer" (Claim 26, preamble).

The preamble of Claim 26 requires "automatically processing a non-interactive electronic message using a computer." The Court construed the term "non-interactive electronic message" to mean "an electronic message in which the sender does not provide any additional information after the message has been received." (Docket No. 369 at 9.) The EZ Reader practiced a method for automatically processing electronic messages in which the sender did not provide any additional information after the messages were received. For example, the EZ Reader Article states that after a customer would send an email to Chase, EZ Reader would retrieve and interpret the message, and would determine whether it could respond automatically to the email and then provide an "automated response, which is routed directly to the ChaseDirect outbox." (Ex. B at 1509 (emphasis added).) In fact, the EZ Reader Article also touts that the EZ Reader "handles up to 80% of incoming mail automatically." (Id.

Although claim 26 is not asserted against Defendants, asserted claims 28, 30, 31, 33, and 38 depend on claim 26.

1

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at 1507. See also Statement of Facts, supra, ¶ 13, Ex. B at Fig. 3; Ex. D at 55:12-56:3, 122:21123:7; 155:17-21.) 2. The EZ Reader practiced "receiving the electronic message from a source" (Claim 26(a)).

The EZ Reader flow diagram also shows that the EZ Reader system received electronic messages from a source (i.e., the customer). (See Statement of Facts, supra, ¶ 13). At step 1, the customer sends the message. At steps 2 and 3, the message is routed to the EZ Reader. The article states that "EZ Reader periodically checks the inbox (a Lotus Notes mail database) for new mail. When a new email arrives in the inbox, EZ Reader retrieves the message . . . ." (Ex. B at 1509. See also id. at 1507 ("The [EZ Reader] application continuously retrieves incoming Internet email from Chase prospects and customers through an interface to Lotus Notes."); Ex. D at 55:12-16.) 3. The EZ Reader practiced "interpreting the electronic message using a rule base and case base knowledge engine" (Claim 26(b)).

The EZ Reader system interpreted electronic messages using a rule base and case base knowledge engine. The parties stipulated that a "rule base . . . knowledge engine" means "a knowledge engine that tests whether one or more conditions are met and, if so, applies specified actions." (Docket No. 369 at 7.) The Court construed "case base knowledge engine" to mean "a knowledge engine that processes electronic messages by comparing them to a stored set of exemplar cases." (Id. at 11.) The EZ Reader Article states that after a new email arrives in the inbox, "EZ Reader retrieves the message and `interprets' it by performing rule-based parsing and case-based retrieval." (Ex. B at 1509 (emphasis added).) The article later states that the EZ Reader's message interpretation system "combines pre-processing rules for parsing and case-based retrieval with a domain-specific knowledge base," and the processing flowchart at Fig. 3 shows how the EZ Reader applied both rule base and case base reasoning to interpret electronic messages. (See id. at Fig. 3. See also id. at 1511-12 (describing in more detail EZ Reader's case-based and rule-based reasoning).) Rosanna Piccolo and Anthony Angotti, named inventors -13-

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of the `947 patent, also testified that the EZ Reader system included both case-based and rulebased reasoning. (Ex. E at 26:13-17; Ex. D at 125:2-8, 160:4-11, 160:21-161:5; Ex. E at 26:1317.) Thus, the EZ Reader system interpreted incoming electronic messages using both a "rule base knowledge engine" and a "case base knowledge engine." 4. The EZ Reader practiced "retrieving one or more predetermined responses corresponding to the interpretation of the electronic message from a repository for automatic delivery to the source" (Claim 26(c)).

Claim 26 of the `947 patent requires "retrieving one or more predetermined responses corresponding to the interpretation of the electronic message from a repository for automatic delivery to the source." The Court construed "predetermined response" to mean "responses prepared prior to the receipt of the electronic message. The responses may be modified and/or altered based on the interpretation of the electronic message." (Docket No. 369 at 12.) The Court construed "repository" to mean "a place where data is stored." (Id. at 13.) The EZ Reader practiced this element. As discussed above, supra section I.A, the EZ Reader processed email and responded to the source "automatically." (Ex. B at 1507.) As the EZ Reader Article provides, after electronic messages are received and classified, "EZ Reader then uses the inferred classification to select and attach a standard response from the Lotus Notes database of standard responses." (Id. at 1511. See also Ex. E at 26:18-24; Ex. D at 164:10-15.) In accordance with the Court's construction, the EZ Reader also modified and/or altered the responses based on the interpretation of the electronic message. The EZ Reader Article states: "If a similar previous email is found, EZ Reader infers that the response used previously can be used (or adapted) for the incoming email." (Ex. B at 1512 (emphasis added).) Accordingly, the EZ Reader practiced every limitation of independent claim 26. B. The EZ Reader Practiced Dependent Claims 28, 30, 31, 33, and 38. 1. The EZ Reader practiced each limitation of Claim 28.

Claim 28 depends from independent claim 26. Claim 28(b1) requires "classifying the electronic message as at least one of (i) being able to be responded to automatically; and (ii) requiring assistance from a human operator." The parties have stipulated that "classifying the
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electronic message" means "determining whether the electronic message falls into one or more categories." (Docket No. 369 at 6.) The Court construed "requiring assistance from a human operator" to mean "requiring that a manual reviewer review the electronic message or information derived from the electronic message, or review, revise or compose the response to be delivered to the source." (Id. at 14.) The EZ Reader classified messages in exactly this way. The EZ Reader Article states that after the EZ Reader would interpret the message, "[t]he outcome of its interpretation is one of two possibilities." (Ex. B at 1509.) The first outcome is "EZ Reader can respond to the email automatically." (Id. See also Ex. E at 27:15-23.) The second outcome is "EZ Reader cannot respond to the email automatically. It refers the email to ChaseDirect for human review and response." (Ex. B at 1509. See also Ex. E at 27:15-23.) In addition, the human reviewer could "review, revise or compose the response to be delivered to the source," in accordance with the Court's claim construction. The EZ Reader Article states that when EZ Reader would refer an email for human review, "EZ Reader . . . suggests one or more standard replies based on message content." (Ex. B at 1509.) Then, "ChaseDirect specialists review and write responses to all messages referred by EZ Reader and place these electronic replies in the outbox." (Id.) Accordingly, the human operators could review and revise the suggested standard reply, or compose their own reply. (Id.) Claim 28(c) further requires "retrieving one or more predetermined responses corresponding to the interpretation of the electronic message from a repository for automatic delivery to the source when the classification step indicates that the electronic message can be responded to automatically." The EZ Reader Article provides that, after electronic messages are received and classified as being able to be responded to automatically, "EZ Reader then uses the inferred classification to select and attach a standard response from the Lotus Notes database of standard responses." (Ex. B at 1511. See also Ex. D at 164:10-15, 166:18-167:15, 170:8-12.) Accordingly, the EZ Reader practiced each element of claim 28.

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2.

The EZ Reader practiced each limitation of Claim 30.

Claim 30 depends from dependent claim 28, and has several sub-elements. 30(b1) requires "producing a case model of the electronic message including (i) a set of attributes for identifying specific features of the electronic message; and (ii) message text." The EZ Reader Article specifically discloses that the case model (which it refers to as a "case object") "contains attributes, or slots, for the important features of emails as defined by the knowledge used by ChaseDirect to interpret and respond to the messages." (Ex. B at 1512 (emphasis added).) The case model also included the email text, as made apparent by the article's discussion of "[s]tandard case-based scoring for the message text of an email." (Id. at 1512.) Claim 30(b2) further requires "detecting at least one of text, combinations of text, and patterns of text of the electronic message using character matching." The EZ Reader Article explicitly states the EZ Reader system would use "[c]haracter matching" to detect "trigrams," or 3-character combinations of text in the message. (Ex. B at 1512). The EZ Reader Article also states that the EZ Reader system interpreted messages "by first detecting combinations of prominent words and patterns of text in any order throughout an incoming message." (Id. at 1510 (emphasis added).) As for text, the EZ Reader Article states that "EZ Reader processes free-format text," and that the precision of a match for the "message text attribute" could be specified. (Ex. B at 1513.) Claim 30(b3) requires "flagging the attributes of the case model which are detected in the electronic message." As the EZ Reader Article states, "features or characteristics" (i.e., attributes) are extracted from the message, and "features may be set in the pre-processing rule phase." (Ex. B at 1512-13.) Claim 30 (b4) further requires "comparing the flagged attributes of the case model with stored attributes of stored case models of the case base." After the EZ Reader detected the attributes in an incoming electronic message, it would flag those attributes of the case model and compare them to the stored attributes of stored case models of the case base. These features

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"will then affect the scoring calculations performed by ART*Enterprise's case-based reasoning engine." (Id.) The article provides the following example:

(Ex. B at 1513 (highlight added).) In this example, the EZ Reader would flag the "do-not-callcustomer" attribute by setting it to "Yes," and would then compare that flagged attribute to the case models of the case base during a search of the case base. Claim 30(b5) further requires "comparing the text of the case model with stored text of the stored case models of the case base." As discussed above (see Statement of Facts, supra ¶ 12), the EZ Reader compared the text of the case model with stored text of the stored case models of the case base. (Ex. B at 1512-13.) The EZ Reader Article states that "EZ Reader processes free-format text," and one could specify the desired precision of a match between the "message text attribute" of the presented message's case model with the stored case models of the case base. (Id. at 1513.) Claim 30(b6) further requires "assigning a score to each stored case model which is compared with the case model, the score increasing when at least one of the attributes and the text match the stored case model and the score not increasing when at least one of the attributes and the text do not match the stored case model." The EZ Reader also assigned a score to each stored case model. The EZ Reader Article states that "if the value in a feature of the stored email matches the value in the corresponding feature of the incoming email, the feature's match weight is add[ed] to the stored email's score." (Ex. B at 1512.) On the other hand, "[i]f the feature's value mismatches, the feature's mismatch weight, typically a negative value, is added to the score." (Id.) Accordingly, the EZ Reader system practiced each limitation of claim 30.

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3.

The EZ Reader practiced Claim 31.

Claim 31 depends from dependent claim 30, and requires that the score of a stored case model be increased "by a predetermined match weight" "when at least one of the attributes and text match the stored case model." The claim further requires that the score be "decreased" when there is no such match.2 The EZ Reader practiced the limitations of claim 31. As discussed above with respect to claim 30(b6), the EZ Reader would increase the score when at least one of the attributes and text matched the stored case model, and would decrease the score when there was no such match. Based on this disclosure, and as confirmed by the mathematical algorithm for comparing electronic messages to case models of the case base set forth in the EZ Reader Article (see Ex. B at 1512), the EZ Reader could both "arithmetically increase" and "arithmetically decrease" the score of the stored case models, as required by claim 31 as construed by the Court. 4. The EZ Reader practiced the normalization of Claim 33.

Claim 33 depends from dependent claim 31, and requires normalizing the score "by dividing the score by a maximum possible score for the stored case model, where the maximum possible score is determined when all of the attributes and text of the case model and the stored case model match." The parties stipulated that this element means "wherein each match score is divided by the maximum possible score for the stored case model." (Docket No. 369 at 7.) The EZ Reader Article explicitly states this limitation is met: "[A] presented case's raw score is normalized by dividing the raw score by the maximum possible match score for the case." (Ex. B at 1512.)

The Court construed "predetermined match weight" to mean "a predetermined factor which arithmetically decreases a stored case model's match score when a feature from the stored case model matches text and attributes from the presented case model," and "predetermined mismatch weight" to mean "a predetermined factor which arithmetically decreases a stored case model's match score when a feature from the stored case model does not match text and attributes from the presented case model." (Docket No. 369 at 16.)

2

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5.

The EZ Reader practiced altering the predetermined response "in accordance with the interpretation of the electronic message before delivery to the source." (Claim 38.)

Claim 38 depends from independent claim 26, and requires altering the predetermined response "in accordance the interpretation of the electronic message before delivery to the source." The EZ Reader Article states: "If a similar previous email is found, EZ Reader infers that the response used previously can be used (or adapted) for the incoming email." (Ex. B at 1512 (emphasis added).) In addition, the article states that, when the EZ Reader system determined that the message required human review, it would "assign[] a category and priority to the message and suggest[] one or more standard replies based on message content." (Ex. B at 1509.) Then, the original message and EZ Reader's chosen response would be sent "to targeted Lotus Notes databases that can be viewed and edited by business users through a customized Lotus Notes interface that lists outputs by category." (Id. at 1510 (emphasis added).) Accordingly the EZ Reader system could alter the predetermined response in order to appropriately respond to the electronic message. C. The Rice Testimony Does Not Create a Genuine Issue of Material Fact.

Plaintiff may argue an issue of fact exists due to the testimony of Amy Rice, a named inventor of the `947 patent. In its interrogatory responses, Plaintiff cited a 2004 declaration of Amy Rice stating that the EZ Reader system was "never fully operating within Chase's Chase Direct public email environment." (Ex. K at 3; Ex. G at ¶ 14.) The declaration states, EZ Reader in 1996 was only "demonstrated in an experiment" in which the system did not automatically send responses to customers' messages, but rather routed suggested responses for human review. (Id. at ¶ 11.) Ms. Rice was a paid consultant at the time she signed the declaration and worked on the affidavit with Plaintiff's counsel David Pridham. (Ex. F at 130:20-25, 133:25-134:9.) At her deposition, Ms. Rice offered similar testimony. (See id. at 30-31.) Plaintiff maintains that Ms. Rice remains a consultant to Bright Response in this case. (See id. at 20:12-21:21.) Ms. Rice's declaration and testimony do not create an issue of fact for several reasons.

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Initially, Ms. Rice's testimony is not probative of the issue of when EZ Reader was launched because it lacks foundation. Ms. Rice admitted at her deposition that she was not even involved in what she described in her declaration as an "experiment" with EZ Reader in 1996. (Ex. F at 144:11-17, 144:18-21.) In fact, Ms. Rice admitted that she was taken off the EZ Reader project before testing was complete. (Ex. F at 31:18-19.) When asked when she was removed from the project, she could not even remember the year: "I think it was in my affidavit. I am not sure. It was March or April, maybe May. March. I think it was April of ­ I guess it would be `95, `96. I can't remember what year." (Id. at 32:3-6.) Thus, it is unsurprising that her testimony about whether the EZ Reader was deployed was speculative and tentative: "As far as I know, it was never used for that." (Ex. F at 31:5-6 (emphasis added).) Despite Ms. Rice's attempts to parse and characterize Chase's use of the EZ Reader software, she simply does not and cannot offer any admissible testimony with respect to Chase's activities. L.R. 56. Therefore, Ms. Rice's testimony does not create a genuine issue of material fact that would preclude summary judgment on the public use bar of § 102(b). Further, Ms. Rice's testimony contradicts a sworn statement that she submitted on June 9, 1998 with the application leading to the patent-in-suit, which claims the benefit of and incorporates the `494 provisional application containing the EZ Reader Article. In her declaration , signed under penalty of perjury, Ms. Rice confirmed the truth of the provisional application--and hence the truth of the statements in the EZ Reader Article:

(Ex. O (highlight added).) Ms. Rice further stated that "I have reviewed and understand the contents of the above-identified specification . . . ." (Id.) Ms. Rice stated during her deposition

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with respect to the declaration that "I wouldn't have signed it [un]less it were true." (Ex. F at 68:8-15). Ms. Rice also confirmed that she did indeed review the `233 application. (Id. at 76:24-25). As Ms. Rice previously declared, under penalty of perjury, that the contents of the EZ Reader Article are true, Plaintiff should not be allowed to attempt to create the appearance of a factual dispute by now claiming that the contents of the EZ Reader Article are false. "To allow [a party] to preclude summary judgment simply by contradicting his own prior statements would seriously impair the utility of Federal Rule of Civil Procedure 56." Sinskey v. Pharmacia Ophthalmics, Inc., 982 F.2d 494, 498 (Fed. Cir. 1992). See also BLS Joint Venture v. Bank Home Savings Assoc., 985 F.2d 556 (5th Cir. 1993) (same). II. ALLEN INVALIDATES THE ASSERTED CLAIMS. The asserted claims of the `947 patent are also invalid because they are described in U.S. Patent No. 5,581,664 to Bradley Allen, which was filed on May 23, 1994--almost two years before the earliest claimed priority date of April 3, 1996. See 35 U.S.C. § 102(e)(2). A. Allen Discloses the Elements of Independent Claim 26. 1. Allen discloses "[a] method for automatically processing a non-interactive electronic message using a computer" (Claim 26).

Allen discloses a method for automatically processing a non-interactive electronic message using a computer. Allen describes a "help desk application" in which a user (i.e., a customer service representative) describes a technical problem, and the application provides a response to the user without requiring any further information. Allen states that, after the customer problem has been entered into the system, "the application 601 may attempt to match the customer problem 605 to one or more cases 105 in the case base 104 using just the description 606 of the customer problem 605." (Ex. C at 9:21-23.) If the match quality of the case is sufficiently high, "[t]he action 309 which the application 601 performs is to provide an advice message 607 to the customer service representative 602 . . . ." (Id. at 9:23-29.) Thus, Allen discloses providing a response (i.e., the advice message) to the user's message without

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further information, meeting the Court's construction of non-interactive electronic message: "an electronic message in which the sender does not provide any additional information after the message has been received." (Docket No. 369 at 9.) Bright Response has argued that Allen does not disclose a non-interactive electronic message because the customer service representative in Allen is "interactively entering that information [provided by the customer] and answering questions with the system." (4/1/2010 Tr. at 96:17-21.) Plaintiff's argument, however, ignores the scenario discussed above where the advice message is provided with no further information from the user beyond the initial message. Instead, Bright Response's argument focuses only on the scenario were the user's description of the problem in the message results in only low-quality matches to prior cases such that the system requires additional input from the customer in order to provide advice. (Ex. C at 9:3041.) The fact that the second scenario described in Allen may not disclose a non-interactive electronic message is irrelevant.3 See Arthrocare Corp. v. Smith & Nephew, Inc., 406 F.3d 1365, 1371-1372 (Fed. Cir. 2005) (reversing denial of defendant's motion for judgment as a matter of law because district court considered only one embodiment of prior art reference and ignored other embodiments that anticipated the asserted patent). 2. Allen describes "receiving the electronic message from a source" (Claim 26[a]).

Allen describes how the application receives an electronic message from the user, the source of the message: In a description step 201, the inference engine 111 retrieves a description of the facts of a particular situation (the "problem"). In a preferred embodiment, the user 119 may enter data relating to the problem by means of the user interface 118.

Bright Response's contention that Allen does not disclose a non-interactive electronic message also contradicts its theory that Defendants' search engines meet this limitation. Defendants' search engines allow users to obtain and narrow search results by interacting with the system, just like the customer service representative interacts with the system disclosed in Allen. A patent claim is not a "nose of wax" to be twisted one way to preserve a patent's validity and another way to catch an alleged infringer. White v. Dunbar, 119 U.S. 47, 51-52 (1886).

3

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(Ex. C at 3:58-60 (emphasis added).) See also id. at 9:19-29 (stating that the user enters a "text string description 606 of the customer problem 605").) 3. Allen describes "interpreting the electronic message using a rule base and case base knowledge engine" (Claim 26[b]).

The application described in Allen interprets the electronic message using rule base and case base reasoning. The Abstract describes the invention as "[a] case-based reasoning system which is smoothly integrated into a rule-based reasoning system, thus coordinating case-based reasoning techniques and rule-based reasoning techniques in a unified automated reasoning system . . . ." (Ex. C at Abstract. See also id. at 1:58-2:2, 2:45-49, 2:61-63; 7:8-16: 10:40-44.) Allen depicts the case base and rule base in Figure 5, (see Statement of Facts, supra ¶ 22), and describes how the case base and rule base work together to retrieve a solution to the problem entered by the user:

(Ex. C at 8:5-18 (highlighting added).) Accordingly, Allen describes interpreting the electronic message using a rule base and case base knowledge engine. 4. Allen describes "retrieving one or more predetermined responses corresponding to the interpretation of the electronic message from a repository for automatic delivery to the source" (Claim 26[c]).

Allen retrieves predetermined responses corresponding to the interpretation of the electronic message from a repository, for automatic delivery to the source: In a case-matching step 202, the inference engine 111 attempts to match the problem to one or more cases 105 in the case base 104.... In a best-case step 203, the inference engine 111 attempts to evaluate the cases 105 which were found in the case-matching step 202, and determine a "best" case 204 to match the problem....
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In a note-action step 205, the inference engine 111 determines the action prescribed by the "best" case 204, and attempts to determine if that action is a correct action to perform. If so, the inference engine 111 proceeds to a do-action step 206. (Ex. C at 3:66 ­ 4:15.) Allen further discloses that the "action" undertaken may consist of providing a predetermined response--the advice message: "The action 309 which the application 601 performs is to provide an advice message 607 to the customer service representative 602, who may then provide advice to the customer 604." (Id. at 9:26-29.) Accordingly, Allen anticipates Claim 26. B. Allen Anticipates Dependent Claims 28, 30, 31, and 38. 1. Allen meets each of the limitations of Claim 28.

Allen discloses "classifying the electronic message as at least one of (i) being able to be responded to automatically; and (ii) requiring assistance from a human operator," as required by Claim 28(b1). As discussed in section II.A.1 above, Allen describes how messages that sufficiently match prior cases can be responded to automatically. On the other hand, if the message does not sufficiently match a prior case, "[t]he application 601 may present a set of questions 609 from the question-answer pairs 608 to the customer service representative 602, who would provide a set of answers 610 to the application 601 (typically by asking the customer 604)." (Ex. C at 9:30-37.) Thus, if the electronic message sufficiently matches a prior case, the message will be classified as being able to be responded to automatically. If the match quality is too low, however, the message will be classified as needing assistance from the customer service representative. Claim 28 further requires "retrieving one or more predetermined responses corresponding to the interpretation of the electronic message from a repository for automatic delivery to the source when the classification step indicates that the electronic message can be responded to automatically." Allen describes this limitation as well. When the classification step of Allen indicates that the electronic message can be responded to automatically, the predetermined responses corresponding to the interpretation of the message are retrieved from a repository and

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are delivered automatically to the source (i.e., the customer service representative). (See Ex. C at 9:24-30 ("The action 309 which the application 601 performs is to provide an advice message 607 to the customer service representative 602 . . . .").) Accordingly, Allen anticipates claim 28. 2. Allen discloses each limitation of Claim 30.

Allen describes "producing a case model of the electronic message including (i) a set of attributes for identifying specific features of the electronic message; and (ii) message text," as required by claim 30(b1). The case-based reasoning component described in Allen produces a case model of the electronic message, and that model includes both a set of attributes for identifying features of the electronic message, and message text. With respect to the "attributes" requirement, Allen states: "To match a problem 311 to the cases 105 in the case base 104, a case template 312 may be constructed for the problem 311 with attribute-value pairs 303 which correspond to notable parameters of the problem 311." (Ex. C at 5:3-6 (emphasis added).) In other words, a case model of the electronic message is produced, and that case model includes a set of attributes for identifying features (called "notable parameters") of the message. Allen further discloses that the attribute-value pairs may consist of message text: "Fig. 4B shows a method for matching attribute-value pairs 303 which have text string values 302." (Id. at 6:2223; see generally id. at 6:22-59.) Claim 30(b2) requires "detecting at least one of text, combinations of text, and patterns of text of the electronic message using character matching." Allen describes this limitation as well. With respect to "text," Allen states that "[i]n string matching, the entire text string value 302 is matched exactly." (Id. at 6:27-28.) With respect to "combinations of text," and "patterns of text," Allen states that "[i]n word matching, the text string value 302 is broken up into separate words, by reference to word delimiter characters, as is well known in the art." (Id. at 6:30-32.) Claim 30(b3) requires "flagging the attributes of the case model which are detected in the electronic message." Allen describes that that "[e]ach case 105 may comprise a set of attributes 301, each of which has a value 302." (Ex. C at 4:32-24.) The attributes are "flagged" in Allen when the value of that in the message is set. For example, "an attribute 301 such as `approved' .

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. . would have a boolean value 302." (Id. at 4:42-43). Accordingly, the attribute "approved" is flagged by setting the boolean value to "1", which would indicate "yes."4 Claim 30(b4) requires "comparing the flagged attributes of the case model with stored attributes of stored case models of the case base." Allen describes how the flagged attributes are compared to the stored attributes of the stored case models using "hash functions" that are applied to each "attribute-value pair" of the case models, thereby generating "a set of locations 319 in the hash table 320." (Ex. C at 5:41-53). Allen further states that "the inference engine 111 may examine the locations 319 in the hash table 320 to examine attribute-value pairs 303 further, e.g. to determine if there is a match." (Id. at 5:53-59. See also id. at Fig. 3B.) Claim 30(b5) requires "comparing the text of the case model with stored text of the stored case models of the case base." As discussed above, Allen describes comparing text of the case model with text of the stored case models. Allen states: "In a preferred embodiment, an attribute 301 with a text string value 302 may be matched by string matching, word matching and character matching." (Ex. C at 24-26.) Finally, claim 30(b6) requires "[a]ssigning a score to each stored case model which is compared with the case model, the score increasing when at least one of the attributes and the text match the stored case model and the score not increasing when at least one of the attributes and the text do not match the stored case model." Allen describes assigning a score (called "match quality") to each stored case model. (Ex. C at 5:16-26.) When the attributes match the stored case model, the match quality increases. Specifically, "the inference engine 111 may determine match quality 315 for each case 105 in the match table 314 by a weighted sum of an evaluation 316 of those attribute-value pairs 303 which are matched." (Ex. C at 5:16-26.) Although only selected cases appear in the match table, Allen makes clear that using the match

The Allen Patent describes a "boolean" value as "a yes/no data type, i.e., a one-bit boolean value." (Ex. C at 4:47-48.)

4

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table is optional. (Id. at 5:16-17.) One of ordinary skill in the art would understand that if the optional match table is not used, matching involves assigning a score to each stored case model. In addition, Allen incorporates the "CBR Express User's Guide" by reference (10:4044),5 which discloses assigning a match score to each stored case model in the case base. The User's Guide states that "CBR Express conducts a simple string match of the answer against the cases in the case base." (Allen Decl. Ex. A at YAH21181.) See Callaway Golf Co. v. Acushnet Co., 576 F.3d 1331, 1346 (Fed. Cir. 2009) (holding that material incorporated by reference into host document would be considered for purposes of anticipation). 3. Allen Discloses Each Limitation of Claim 31.

Claim 31 requires increasing the score of the case model "by a predetermined match weight" "when at least one of the attributes and the text match the stored case model." Allen anticipates this limitation. As described above, supra section II.B.2, Allen describes how attributes of the case model are compared with attributes of the stored case models to determine the extent to which they match. Allen further describes that "the weights assigned to each attribute-value pair 303 may be predetermined and may be altered by the user 119." (Ex. C at 5:24-26 (emphasis added).) Accordingly, Allen teaches that the score can be increased by a predetermined match weight. Claim 31 further requires decreasing the score "by a predetermined mismatch weight" "when at least one