Polaris IP, LLC v. Google Inc. et al
Filing
610
MOTION for Judgment as a Matter of Law on Invalidity by Google Inc.. Responses due by 8/23/2010 (Attachments: # 1 Text of Proposed Order)(Smith, Kevin)
Polaris IP, LLC v. Google Inc. et al
Doc. 610
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. 2:07CV-371-TJW-CE
GOOGLE'S MOTION FOR JUDGMENT AS A MATTER OF LAW ON INVALIDITY
Dockets.Justia.com
TABLE OF CONTENTS Page Introduction ......................................................................................................................................3 Legal Standard .................................................................................................................................3 Argument .........................................................................................................................................4 I . EZ READER ANTICIPATES EACH OF THE ASSERTED CLAIMS OF THE `947 PATENT. ................................................................................................4 A. B. No Reasonable Juror Could Find that EZ Reader was Not in Public Use Before the Critical Date of the `947 Patent...........................4 Claim 26 is Anticipated by EZ Reader ....................................................5 1 . 2 . 3 . 4 . C. EZ Reader Discloses A Method for Automatically Processing a Non-Interactive Electronic Message ...........................5 EZ Reader Discloses Receiving Message From Source ..................6 EZ Reader Discloses Interpreting the Message ...............................6 EZ Reader Discloses Retrieving a Predetermined Response ...........7
Claim 28 is Anticipated by EZ Reader ....................................................8 1 . 2 . EZ Reader Discloses Classifying the Electronic Message ..............8 EZ Reader Discloses the "Retrieving" Step.....................................9
D.
Claim 30 is Anticipated by EZ Reader ....................................................9 1 . 2 . 3 . 4 . 5 . 6 . EZ Reader Discloses Producing a Case Model................................9 EZ Reader Discloses Detecting Text .............................................11 EZ Reader Discloses Flagging Attributes ......................................11 EZ Reader Discloses Comparing Flagged Attributes ....................11 EZ Reader Discloses Comparing Text ...........................................12 EZ Reader Discloses Assigning a Score ........................................13
E.
Claim 31 is Anticipated by EZ Reader ..................................................14
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1. 2 . F. II.
EZ Reader Discloses Increasing the Score ....................................14 EZ Reader Discloses Decreasing the Score ...................................14
Claim 33 is Anticipated by EZ Reader ..................................................15
THE ALLEN PATENT RENDERS OBVIOUS EACH OF THE ASSERTED CLAIMS OF THE `947 PATENT....................................................15 A. B. Allen Is Prior Art Under 35 U.S.C. § 102 ..............................................15 Claim 26 is Anticipated by Allen ............................................................16 1 . 2 . 3 . C. D. Allen Discloses Receiving a Message From a Source ...................16 Allen Discloses Interpreting the Electronic Message ....................17 Allen Discloses Retrieving a Predetermined Response .................18
Claim 28 is Obvious in Light of Allen ....................................................19 Claim 30 is Obvious in Light of Allen ....................................................20 1 . 2 . 3 . 4 . 5 . 6 . Allen Discloses Producing a Case Model ......................................20 Allen Discloses "Detecting" ..........................................................21 Allen Discloses "Flagging"............................................................21 Allen Discloses Comparing the Flagged Attributes.......................22 Allen Discloses Comparing the Text .............................................22 Allen Discloses Assigning a Score ................................................22
E.
Claim 31 is Obvious in Light of Allen ....................................................24 1 . 2 . Allen Discloses Increasing by a Predetermined Match Weight ............................................................................................24 Allen Discloses Decreasing the Score ...........................................24
F.
Claim 33 is Obvious in Light of Allen ....................................................25
Conclusion .....................................................................................................................................26 CERTIFICATE OF SERVICE ......................................................................................................27
01980.51452/3620869.2
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Pursuant to Federal Rule of Civil Procedure 50, Google hereby moves the Court for entry of judgment as a matter of law that the asserted claims of the `947 patent are invalid under 35 U.S.C. §§ 102 and 103. Introduction Bright Response asserts Google infringes claims 28, 30, 31, 33, and 38 of U.S. Patent No. 6,411,947 ("the `947 patent"). The undisputed evidence presented at trial has shown that every element of the asserted claims was known and used in the prior art, and that the asserted claims are invalid. Because there is no legally sufficient evidentiary basis for a reasonable jury to find that the asserted claims of the `947 patent are valid, Google is entitled to judgment as a matter of law. Legal Standard Judgment as a matter of law is proper when "the facts and inferences point so strongly and overwhelmingly in favor of one party that the Court believes that reasonable men could not arrive at a contrary verdict." Wallace v. Methodist Hosp. Sys., 271 F.3d 212, 219 (5th Cir. 2001); see also Fed. R. Civ. P. 50(a) (judgment as a matter of law appropriate if there is no "legally sufficient evidentiary basis to find for the party on that issue"). The grant of judgment as a matter of law is appropriate in a patent case, and the Federal Circuit has frequently affirmed the decision of a district court to grant judgment as a matter of law . See, e.g., Mahurkar v. C.R. Bard, Inc., 79 F.3d 1572 (Fed. Cir. 1996) (affirming grant of judgment as a matter of law that the patent was anticipated). "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). 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 3
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. Here, because no reasonable jury could find the patents-in-suit valid in light of EZ Reader, the Allen patent, and CBR Express, judgment as a matter of law is appropriate. Argument I. EZ READER ANTICIPATES EACH OF THE ASSERTED CLAIMS OF THE `947 PATENT. EZ Reader was a system developed for Chase Manhattan Bank to automatically respond to e-mail messages using case-based and rule-based reasoning. EZ Reader is described in a paper published by the IAAI in 1996 (DX0030) ("IAAI Article"). The EZ Reader system is also described in the EZ Reader User's Guide and Reference Manual, which is dated February 6, 1996 (DX0081). EZ Reader anticipates the asserted claims under 35 U.S.C. § 102(b). A. No Reasonable Juror Could Find that EZ Reader was Not in Public Use Before the Critical Date of the `947 Patent
No reasonable juror could find that EZ Reader was not in public use prior to the critical date of April 3, 1996. All of the evidence of record that a jury could possibly credit shows by clear and convincing evidence that EZ Reader was, in fact, deployed in the first quarter of 1996. For example, the EZ Reader User's Guide, dated February 6, 1996, states: "This document describes EZ Reader, currently in use by the ChaseDirect unit of Chase Manhattan Bank." (DX81 at JPM00318.) The User's Guide further confirms that the Lotus Notes interface had been completed. For example, the User's Guide states: "EZ Reader is a minimally-interactive client/server application that interfaces with Lotus Notes email software." (Id. at JPM00329.) In addition, named inventors Anthony Angotti and Rosanna Piccolo, as well as Brightware CEO Chuck Williams, confirmed that the EZ Reader was in public use prior to the critical date. (8/6/10 Morning Session 132:17-133:13; 8/6/10 Afternoon Session Tr. 5:2-6:13 & 15:12-16:1)
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In addition, the article that Amy Rice wrote and submitted to the IAAI states: "Phase I of EZ Reader was deployed in the first quarter of 1996, and handles up to 80% of incoming mail automatically, depending on message content." (DX30.) In an attempt to refute this overwhelming evidence of public use, Bright Response relies entirely on Amy Rice, who testified that EZ Reader was not in public use because its Lotus Notes interface was never completed during EZ Reader's development and testing period. (8/3/10 Morning Tr. at 17:25-18:16, 19:4-8.) Ms. Rice, however, admitted that she was taken off the EZ Reader project before testing was complete. (8/3/10 Morning Tr. at 52:21-54:8.) She also admitted that she does not know what Chase Manhattan bank did afterwards, and that it was possible that EZ Reader was deployed by Chase without her knowledge. (8/3/10 Morning Tr. at 57:19-23 & 58:1-17.) Accordingly, Ms. Rice has no personal knowledge of the circumstances of EZ Reader's deployment. No reasonable juror could reject the uncontroverted evidence showing public use in favor of the mere speculation of Ms. Rice, who admits she has no personal knowledge of the events in question. B. Claim 26 is Anticipated by EZ Reader
Dr. L. Karl Branting, an expert in computer science, testified that each element of the asserted claims is disclosed by the EZ Reader system. (8/6/10 Morning Tr. 88:2-97:2.) Bright Response does not dispute Dr. Branting's testimony, and its own expert, Dr. V. Thomas Rhyne, admitted that EZ Reader discloses each element of each claim. (8/6/10 Afternoon Tr. at 144:514).)
1.
EZ Reader Discloses A Method for Automatically Processing a NonInteractive Electronic Message
The preamble to claim 26 of the `947 Patent describes "a method for automatically processing a non-interactive electronic message using a computer." The Court has construed the
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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." (Dkt. 369 at 9.) The EZ Reader system disclosed the requirements of the preamble. For example, the abstract of the IAAI article describes EZ Reader as "an intelligent electronic mail (email) reader that employs a unique combination of rule-based parsing and case-based reasoning to automatically and with a high level of accuracy classify and respond to large volumes of incoming email." (DX0030 at BR001252.)
2.
EZ Reader Discloses Receiving Message From Source
The first limitation of the claim 26 of the `947 patent recites: "receiving the electronic message from a source." The IAAI article shows that EZ Reader received electronic mail from a source. For example, in describing the "process flow," the first step reads "The customer sends an email to Chase Manhattan Bank's Internet address." (DX0030 at BR001254.)
3.
EZ Reader Discloses Interpreting the Message
The second limitation of claim 26 of the `947 patent recites: "interpreting the electronic message using a rule base and case base knowledge engine." The Court, in accordance with the parties' agreement, has construed the term "rule base ... knowledge engine" as "a knowledge engine that tests whether one or more conditions are met and, if so, applies specific actions." (Dkt. 369 at 7-8.) The Court has also construed the term "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 IAAI article shows that EZ Reader discloses this interpreting the message. For example, the third step in the "process flow" of the IAAI article states: "When a new email 6
arrives in the inbox, EZ Reader retrieves the message and `interprets' it by performing rule-based parsing and case-based retrieval." (DX0030 at BR001254.) Figure 3 of the IAAI article shows the "interpret" step:
(Id. at BR001255.)
4.
EZ Reader Discloses Retrieving a Predetermined Response
The third limitation of claim 26 of the `947 patent recites: "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 has construed the term
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"predetermined response" as "responses prepared prior to the receipt of the electronic message. The response may be modified and/or altered based on the interpretation of the electronic message." (Dkt. 369 at 12). The Court has also construed "repository" as "a place where data is stored." (Id. at 13.) The IAAI article shows that EZ Reader discloses retrieving a predetermined response. For example, part of the third step of the "process flow" described in the IAAI article states that, "EZ Reader can respond to the email automatically. An automatic response, which is routed directly to the ChaseDirect outbox, consists of the original email and one or more attachments, or prepared replies, that are retrieved from a Lotus Notes repository of standard responses." (DX0030 at BR001254.) C. Claim 28 is Anticipated by EZ Reader
The first limitation of claim 28 recites: "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."
1.
EZ Reader Discloses Classifying the Electronic Message
The Court, with the agreement of the parties, has construed the term "classifying the electronic message" to mean "determining whether the electronic message falls into one or more categories." (Dkt. 369 at 6.) The IAAI article plainly shows that EZ Reader classifies email, or determines whether an email falls into one or more categories. For example, the IAAI article states: AI Enables Email Classification EZ Reader uses classification rules and case-based reasoning to assign a business category and priority to each incoming email. EZ Reader then uses the inferred classification to select and attach a standard response from the Lotus Notes database of standard responses.
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Categories. Using AI techniques described in the following sections, EZ Reader classifies each incoming email based on total message content into any of the following three categories: Automatic Response. EZ Reader assigns a category of Automatic Response to items that can be associated with a response from the Lotus Notes repository of standard responses and directly mailed back to the sender without manual review or revision. Referral. EZ Reader assigns a category of Referral to messages that cannot be processed solely as automatic reswwwponses. EZ Reader then assigns a further subclassification to the message to assist ChaseDirect staff with interpretation later. (DX0030 at BR001256.) Thus EZ Reader can categorize incoming email as to whether it can be automatically responded to, or whether human assistance is required.
2.
EZ Reader Discloses the "Retrieving" Step
The Court has construed the term "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." (Dkt. 369 at 14.) EZ Reader clearly discloses the limitation of retrieving a predetermined response. For example, the IAAI article states that "EZ Reader can respond to the email automatically. An automatic response, which is routed directly to the ChaseDirect outbox, consists of the original email and one or more attachments, or prepared replies, that are retrieved from a Lotus Notes repository of standard responses." (DX0030 at BR001254.) D. Claim 30 is Anticipated by EZ Reader
1.
EZ Reader Discloses Producing a Case Model
The first limitation of claim 30 of the `947 patent recites: " 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 Court has construed, with the agreement of the
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parties, the term "case model of the electronic message" or "case model" to mean "text and attributes derived from the electronic message." (Dkt. 369 at 7.) The IAAI article clearly discloses that EZ Reader produces a case model by identifying text and attributes from the email. For example, the IAAI article states: In EZ Reader rules fire before the case-based reasoning process to extract features or characteristics of the email that help distinguish the content of the message. Depending on the content of the message, any of the case-base search features may be set in the pre-processing rule phase. *** For example, 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". Features set to "Yes" then contribute to the case-based search by adding weight for similar stored cases during case-base retrieval. *** CASE001: title = "Sign-Up Kit request; Refer." Subject = "chase direct" message text = "Please send me a ChaseDirect sign-up kit. My address is" address? = "Yes" action = refer-sign-up-kit, detected:address, auto: sign-up-ack CASE002: title = "Sign-Up Kit request/no address; Auto Respond." Subject = "chase direct" message text = "Please send me a ChaseDirect sign-up kit." action = chase-direct-std (DX00030 at BR001257-58.) This example shows EZ Reader extracting text and attributes derived from the email--here message text representing the customer's question, and an attribute called "address?" which represents whether the customer has included their address in the email.
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2.
EZ Reader Discloses Detecting Text
The second limitation of claim 30 of the `947 patent recites: "detecting at least one of text, combinations of text, and patterns of text of the electronic message using character matching." The IAAI article shows that EZ Reader can detect text or combinations or patterns of text using character matching. For example, the IAAI article states: "The application emulates the recursive nature of evolving interpretation by first detecting combinations of prominent words and patters of text in any order throughout an incoming message, then setting object attribute values that both trigger and influence the case-based reasoning process." (DX0030 at BR001255.) Moreover, the detection occurs through character matching: "[c]haracter matching with trigrams was chosen to drive case-base scoring in EZ Reader." (Id. at BR001257.)
3.
EZ Reader Discloses Flagging Attributes
The third limitation of claim 30 of the `947 patent recites: "flagging the attributes of the case model which are detected in the electronic message." EZ Reader clearly discloses flagging attributes of the case model detected in the email. The IAAI article describes this limitation. For example, the article states that "[d]epending on the content of the message, any of the case-base search features may be set in the pre-processing rule phase." (DX0030 at BR001257-58.) "For example, if EZ Reader infers from incoming email text that the sender does not want to be telephoned by ChaseDirect, then the rule for do-not-call-customer? fires and sets that attribute in the case to "Yes". Features set to "Yes" then contribute to the case-based search by adding weight for similar stored cases during case-base retrieval." (Id. at BR001258.)
4.
EZ Reader Discloses Comparing Flagged Attributes
The fourth limitation of claim 30 of the `947 patent recites: "comparing the flagged attributes of the case model with stored attributes of stored case models of the case base." 11
The IAAI article clearly shows that EZ Reader compares the flagged attributes of the case model with the stored case models of the case base. For example, the IAAI article states: A sample of EZ Reader hybrid processing flow, including the interaction between rule firings and case-base matching, is set forth below. The importance of set attributes for the case-base search is clearly illustrated in these two examples.
Suppose ChaseDirect receives an email with the body of the message as follows:
A rule for detecting an address will fire, resulting in setting the case attribute address? to "Yes." Next, EZ Reader will perform a search against the case-base. ranking CASE001 with a score higher than CASE002 because of the match on address? (DX0030 at BR001258.)
5.
EZ Reader Discloses Comparing Text
The fifth limitation of claim 30 of the `947 patent recites: "comparing the text of the case model with stored text of the stored case models of the case base."
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The IAAI article shows that EZ Reader compares the text of the case model with the stored text of the case models from the case base. For example, the IAAI article states: "Character matching with trigrams was chosen to drive case-base scoring in EZ Reader. A trigram is a 3-character sequence. For example, the word "CHASE" generates 7 consecutive trigrams: _ C;_ CH; CHA; HAS; ASE; SE_; E__. When character matching is used, the value of the character feature is broken up into consecutive trigrams, and the trigrams of a stored case are matched against the trigrams of the presented case." (DX0030 at BR001257.)
6.
EZ Reader Discloses Assigning a Score
The sixth limitation of claim 30 of the `947 patent recites: "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." EZ Reader also discloses this limitation. For example, the IAAI article states that "EZ Reader searches the case-base assigning relative scores to each stored case based on the number of features, the mismatch of feature values and the absence of features as compared with the presented case using customizable case-based reasoning components supplied in the ART*Enterprise tool." (DX0030 at BR001257.) Moreover, "[I]f 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 to the stored email's score. If the feature's value mismatches, the feature's mismatch weight, typically a negative value, is added to the score." (Id.) Thus EZ Reader satisfies each and every claim limitation of claim 30 of the `947 patent and therefore anticipates claim 30.
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E.
Claim 31 is Anticipated by EZ Reader
1.
EZ Reader Discloses Increasing the Score
The first limitation of claim 31 of the `947 patent recites: "when at least one of the attributes and the text match the stored case model, the score is increased by a predetermined match weight." The Court has construed the term "predetermined match weight" to mean "a predetermined factor that arithmetically increases a stored case model's match score when a feature from the stored case model matches text and attributes from the presented case model." (Dkt. 369 at 16.) EZ Reader discloses increasing the score by a predetermined match weight when at least one of the attributes match the stored case model. For example, he IAAI article states: "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 added to the stored email's score." (DX0030 at BR001257.)
2.
EZ Reader Discloses Decreasing the Score
The second limitation of claim 31 of the `947 patent recites: "when at least one of the attributes and the text does not match the stored case model, the score is decreased by a predetermined mismatch weight." The Court has construed the term "predetermined mismatch weight" to mean "a predetermined factor which arithmetically decreases a stored case model's match score when a feature from the stored use case model does not match text and attributes from the presented case model." (Dkt. 369 at 16.) EZ Reader discloses decreasing the score by a predetermined mismatch weight when at least one of the attributes do not match the stored case model. For example, the IAAI article states: "if the feature's value mismatches, the feature's mismatch weight, typically a negative value, is added to the score." (DX0030 at BR001257.) 14
F.
Claim 33 is Anticipated by EZ Reader
Claim 33 of the `947 patent recites: "The method of claim 31, wherein each score is normalized 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 Court has construed the term "wherein each score is normalized by dividing the score by a maximum possible score for the stored case model" to mean "wherein each match score is divided by the maximum possible score for the stored case model." (Dkt. 369 at 7.) The IAAI article discloses that EZ Reader performed this limitation. For example, in describing how cases are compared, the IAAI article states "Since stored cases can contain different numbers of features, a presented case's raw score is normalized by dividing the raw score by the maximum possible match score for the case." Accordingly, the Court should grant judgment as a matter of law that the EZ Reader prior art anticipates the asserted claims of the `947 patent. II. THE ALLEN PATENT RENDERS OBVIOUS EACH OF THE ASSERTED CLAIMS OF THE `947 PATENT. A. Allen Is Prior Art Under 35 U.S.C. § 102
U.S. Patent No. 5,581,664 to Bradley Allen was issued on December 3, 1996, more than one year prior to the filing date of the patents-in-suit. (DX74.) The face of the Allen patent shows this as well. The Allen patent is also a prior patent under 35 U.S.C. § 102. The Allen patent cites to a book called the CBR Express User's Guide, as a "preferred example case-based reasoning system 101 for providing user help on call-in complaints." (Id. at 10:39-42.)
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B.
Claim 26 is Anticipated by Allen
As Dr. L. Karl Branting testified, the Allen Patent anticipates claim 26, and that it also renders obvious claims 28, 30, 31, and 33, by itself or in combination with the CBR Express documentation. (8/6/10 Morning Tr. 97:3-109:2.) The preamble to claim 26 of the `947 Patent describes "a method for automatically processing a non-interactive electronic message using a computer." The Court has 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." (Dkt. 369 at 9.) Allen discloses a method for automatically processing a non-interactive electronic message. For example, in the specification, the Allen invention is described: In the description step 201, the application 601 may retrieve a text string description 606 of the customer problem 605. In the case-matching step 202, 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. If the match quality 315 of the case 105 which are matched is high, the application 601 may perform the best-case step 203 and following steps. 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. (DX74 at 9:19-29.) Thus the Allen patent satisfies this limitation.
1.
Allen Discloses Receiving a Message From a Source
The first limitation of the claim 26 of the `947 patent recites: "receiving the electronic message from a source." The Allen patent describes receiving an electronic message from a source. For example, Allen states: "In the description step 201, the application 601 may retrieve a text string description 606 of the customer problem 605." (DX74 at 9:12-21.)
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2.
Allen Discloses Interpreting the Electronic Message
The second limitation of claim 26 of the `947 patent recites: "interpreting the electronic message using a rule base and case base knowledge engine." The Court, in accordance with the parties' agreement, has construed the term "rule base ... knowledge engine" as "a knowledge engine that tests whether one or more conditions are met and, if so, applies specific actions." (Dkt. 369 at 7-8.) The Court has also construed the term "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 Allen patent interprets the electronic message use a rule base and case base knowledge engine. For example, the Abstract of the Allen patent reads: A case-based reasoning system which is smoothly integrated into a rule-based reasoning system, thus coordinating case-based reasoning techniques and rulebased reasoning techniques in a unified automated reasoning system, in which an automated processor may proceed by inferential reasoning on the facts of the problem and the cases by means of rule-based reasoning techniques or based on procedural directives supplied by a human programmer, and may select the case which is the best match for the problem, but may act differently from the precise action prescribed for that case. (DX74 at Abstract.) Moreover, Figure 5 of the Allen Patent shows the that the invention utilizes case-base and rule-base reasoning:
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(DX74 at Fig. 5.)
3.
Allen Discloses Retrieving a Predetermined Response
The second limitation of claim 26 of the `947 patent recites: "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 has construed the term
18
"predetermined response" as "responses prepared prior to the receipt of the electronic message. The response may be modified and/or altered based on the interpretation of the electronic message." (Dkt. 369 at 12). The Court has also construed "repository" as "a place where data is stored." (Id. at 13.) The Allen patent discloses retrieving one or more predetermined responses corresponding to the interpretation of the email from a repository for automatic delivery. For example, Allen states: "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." DX74 at 4:11-14.) The Allen patent also discloses that "[t]he action 309 which the application 601 performs is to provide an advice message 607 to the customer service representative 602...." (Id. at 9:26-29.) C. Claim 28 is Obvious in Light of Allen
The first limitation of claim 28 recites: "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 Court, with the agreement of the parties, has construed the term "classifying the electronic message" to mean "determining whether the electronic message falls into one or more categories." (Dkt. 369 at 6.) The Court has construed the term "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 Allen patent discloses this limitation. For example, Allen recites "[a] case based reasoning system which is smoothly integrated into a rule-based reasoning system, thus coordinating case-based reasoning techniques..." (DX74 at Abstract.) Dr. Branting testified that one of skill in the art would find it obvious to classify the electronic message as required by 19
claim 28. (8/6/10 Morning Tr. 90:21-91:7.) Thus, classifying the electronic message would have been obvious in light of Allen. The Allen patent discloses the "retrieval step." For example, Allen states: "In a noteaction 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." (DX74 at 4:11-14.) The Allen patent also discloses that "[t]he action 309 which the application 601 performs is to provide an advice message 607 to the customer service representative 602...." (Id. at 9:26-29.) Thus, the "action" that the Allen system takes is to retrieve and provide an advice message to the customer service representative. Thus, Allen renders obvious claim 28 of the `947 patent. D. Claim 30 is Obvious in Light of Allen
1.
Allen Discloses Producing a Case Model
The first limitation of claim 30 of the `947 patent recites: " 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 Court has construed, with the agreement of the parties, the term "case model of the electronic message" or "case model" to mean "text and attributes derived from the electronic message." (Dkt. 369 at 7.) The Allen patent discloses producing a case model including attributes for identifying specific features and message text. For example, "[t]o 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 attributevalue pairs 303 which correspond to notable parameters of the problem 311." (DX74 at 4:3444.) Additionally, "Attributes 301 and values 302 are typically manipulated as an attribute-value pair 303. In a preferred embodiment, attributes 301 may be particular to the application field, and values 302 may have data types which vary from one attribute 301 to another." (Id. at 5:3-6.) 20
"[A]n attribute 301 with a text string value 302 may be matched by string matching, word matching and character matching." (Id. at 6:24-26.)
2.
Allen Discloses "Detecting"
The second limitation of claim 30 of the `947 patent recites: "detecting at least one of text, combinations of text, and patterns of text of the electronic message using character matching." The Allen patent discloses detecting text, combinations and patterns of text through string matching. For example, Allen states: In string matching, the entire text string value 302 is matched exactly. In 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. A predetermined set of noise words, such as "a", "and" and "the", may also be removed Synonyms for the non-noise words may also be used for matching, and may be determined either globally or for a particular attribute 301. The non-noise words are each recorded as separate attribute-value pairs 303 which may be matched exactly. For example, the text string "BRADLEY P. ALLEN" would match the words "BRADLEY", "P" and "ALLEN", and if "BRAD" is a synonym for "BRADLEY", would also match "BRAD". In character matching, the words of the text string value 302, as determined for word matching, are broken up into separate trigrams (substrings of length three). In a preferred embodiment, each word is prefixed and suffixed with two special initial/final characters prior to breaking each word into trigrams. The trigrams are each recorded as separate attribute-value pairs 303 which may be matched exactly. For example, the text string "DANIEL" would match the trigrams "xxD", "xDA", "DAN", "ANI", "NIE", "IEL", "ELx", and "Lxx", where "x" is the special initial/final character. (DX74 6:27-52.)
3.
Allen Discloses "Flagging"
The third limitation of claim 30 of the `947 patent recites: "flagging the attributes of the case model which are detected in the electronic message."
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The Allen patent discloses flagging attributes of the case model which are detected. For example, the specification for the Allen patent 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 attributevalue pairs 303 which correspond to notable parameters of the problem 311." (DX74 at 5:3-6.)
4.
Allen Discloses Comparing the Flagged Attributes
The fourth limitation of claim 30 of the `947 patent recites: "comparing the flagged attributes of the case model with stored attributes of stored case models of the case base." The Allen patent discloses this limitation. Allen compares the flagged attributes of the case model with stored attributes of stored case models of the case base. For example, the specification of the Allen patent instructs: "[T]he 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." (DX74 at 5:20-23.)
5.
Allen Discloses Comparing the Text
The fifth limitation of claim 30 of the `947 patent recites: "comparing the text of the case model with stored text of the stored case models of the case base." The Allen patent discloses this limitation. For example, Allen states: In string matching, the entire text string value 302 is matched exactly. In 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 .... In character matching, the words of the text string value 302, as determined for word matching, are broken up into separate trigrams (substrings of length three). (DX74 at 6:27-31, 42-44.)
6.
Allen Discloses Assigning a Score
The sixth limitation of claim 30 of the `947 patent recites: "assigning a score to each stored case model which is compared with the case model, the score increasing when at least one
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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 Allen patent discloses this limitation by assigning a score to each case: "In a preferred embodiment, 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. In a preferred embodiment, the weights assigned to each attribute-value pair 303 may be predetermined and may be altered by the user 119." (DX74 at 5:19-23.) This shows that the score would increase for a match because weighted sum would higher. The Allen patent provides additional support: "In a preferred embodiment, string matching, word matching and character matching are assigned weights, and the evaluation 316 of the text string match may be determined by a weighted sum of the evaluations 316 for each type of match." (Id. at 6:5357.) In addition, this limitation is obvious in light of Allen, which discloses that the match table "may" be used, and is therefore optional. One of skill in the art would understand that, if the match table were not used, each of the cases would need to be scored. Moreover, the Allen patent refers to the CBR Express User's Guide as a disclosing a "preferred example case-based reasoning system 101 for providing user help on call-in complaints." (Id. at 10:39-42.) One of skill in the art would therefore consider the CBR Express documentation when evaluating the Allen patent against the `947 patent. The CBR Express User's Guide states: "if a search feature exactly matches a stored feature ... the raw score of the stored case is incremented by the match weight of the question.... The raw score is totaled up for each case." (DX0207 at YAH0021070.) Thus claim 30 is rendered obvious in light of the disclosures of the Allen patent.
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E.
Claim 31 is Obvious in Light of Allen
1.
Allen Discloses Increasing by a Predetermined Match Weight
The first limitation of claim 31 of the `947 patent recites: "when at least one of the attributes and the text match the stored case model, the score is increased by a predetermined match weight." The Court has construed the term "predetermined match weight" to mean "a predetermined factor that arithmetically increases a stored case model's match score when a feature from the stored case model matches text and attributes from the presented case model." (Dkt. 369 at 16.) The Allen patent discloses increasing the score by a predetermined match weight when at least one of the attributes and text match with the stored case model. For example, the specification states: In a preferred embodiment, 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. In a preferred embodiment, the weights assigned to each attribute-value pair 303 may be predetermined and may be altered by the user 119. (DX74 at 5:19-23.) Moreover, "In a preferred embodiment, string matching, word matching and character matching are assigned weights, and the evaluation 316 of the text string match may be determined by a weighted sum of the evaluations 316 for each type of match." (Id. at 6:53-57.)
2.
Allen Discloses Decreasing the Score
The second limitation of claim 31 of the `947 patent recites: "when at least one of the attributes and the text does not match the stored case model, the score is decreased by a predetermined mismatch weight." The Court has construed the term "predetermined mismatch weight" to mean "a predetermined factor which arithmetically decreases a stored case model's match score when a feature from the stored use case model does not match text and attributes from the presented case model." (Dkt. 369 at 16.) 24
Allen, in light of the CBR Reference Manual, also satisfies this limitation by disclosing decreasing the score for a mismatch. For example, the CBR Manual states: "It is also possible to define a mismatch weight for a feature. In this case, failure to match a feature of the search case results in decrementing the stored case's raw score." (DX0207 at YAH0021070.) F. Claim 33 is Obvious in Light of Allen
Claim 33 of the `947 patent recites: "The method of claim 31, wherein each score is normalized 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 Court has construed the term "wherein each score is normalized by dividing the score by a maximum possible score for the stored case model" to mean "wherein each match score is divided by the maximum possible score for the stored case model." (Dkt. 369 at 7.) Allen, in light of the CBR reference manual, satisfies claim 33 by disclosing score normalization. For example, the CBR manual states: The raw score is totaled up for each case, and is then normalized into the range of points left over after scoring the description. For instance, if the description percentage is set to 50% (or 50 points), the contribution from the questions will be some scaled proportion of the remaining 50 points. The normalization confines the final values to a range of 0 to 100 in CBR Express. A normalized score of 100 indicates a perfect match. (DX0207 at YAH0021070.) Thus score normalization was also known in the art, and it would have been obvious to one skilled in the art to add the normalization of CBR Express to Allen. Accordingly, the Court should grant judgment as a matter of law that the Allen prior art reference anticipates or renders obvious the asserted claims of the `947 patent.
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Conclusion For the foregoing reasons, Google respectfully requests that the Court grant its Motion for Judgment as Matter of Law Regarding Invalidity, and enter judgment that the asserted claims of the `947 patent are invalid under 35 U.S.C. §§ 102(a), 102(b), 102(e), and 103.
DATED: August 7, 2010
Respectfully submitted, QUINN EMANUEL URQUHART & SULLIVAN, LLP By Kevin A. Smith Charles K. Verhoeven, CA Bar No. 170151 LEAD ATTORNEY David A. Perlson, CA Bar No. 209502 Amy H. Candido, CA Bar No. 237829 Kevin A. Smith, CA Bar No. 250814 QUINN EMANUEL URQUHART & SULLIVAN, LLP 50 California Street, 22nd Floor San Francisco, California 94111 Telephone: (415) 875-6600 Facsimile: (415) 875-6700 Jennifer Parker Ainsworth TX Bar No. 00784720 Wilson, Robertson & Cornelius, P.C. P.O. Box 7339 Tyler, Texas 75711 Telephone: (903) 509-5000 Facsimile: (903) 509-5092 jainsworth@wilsonlawfirm.com Attorneys for Defendant Google Inc.
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CERTIFICATE OF SERVICE The undersigned hereby certifies that a true and correct copy of the above and foregoing document has been served on August 7, 2010 to counsel of record in the manner agreed by the parties, via electronic mail.
/s/ Kevin A. Smith
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