Rockstar Consortium US LP et al v. Google Inc

Filing 92

MOTION for Leave to File A Supplemental Brief In Response To Googles Motion To Transfer In Light Of Newly-Acquired Evidence by NetStar Technologies LLC, Rockstar Consortium US LP. (Attachments: # 1 Text of Proposed Order Granting Motion for Leave to File a Supplemental Brief In Response to Google's Motion to Transfer in Light of Newly-Acquired Evidence, # 2 Supplement Plaintiffs' Supplemental Brief In Response to Google's Motion to Transfer, # 3 Affidavit of Amanda Bonn In Support of Plaintiffs' Supplemental Brief In Response to Google's Motion to Transfer, # 4 Exhibit 1, # 5 Exhibit 2, # 6 Exhibit 3, # 7 Exhibit 4, # 8 Exhibit 5, # 9 Exhibit 6, # 10 Exhibit 7, # 11 Exhibit 8, # 12 Exhibit 9, # 13 Exhibit 10, # 14 Exhibit 11, # 15 Exhibit 12, # 16 Exhibit 13, # 17 Exhibit 14, # 18 Exhibit 15, # 19 Exhibit 16, # 20 Exhibit 17, # 21 Exhibit 18, # 22 Exhibit 19, # 23 Exhibit 20, # 24 Exhibit 21, # 25 Exhibit 22, # 26 Exhibit 23, # 27 Exhibit 24, # 28 Exhibit 25, # 29 Exhibit 26, # 30 Exhibit 27, # 31 Exhibit 28, # 32 Exhibit 29, # 33 Exhibit 30)(Bonn, Amanda)

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Exhibit 24 Informorion Processing & Management Printed in Great Britain. Vol. 26, No. 6, pp. 719-738, 1990 Copyright 0 0306-4573/90 $3.00 + .@I 1990 Pergamon Press plc INTEGRATION OF USER PROFILES: MODELS AND EXPERIMENTS IN INFORMATION RETRIEVAL SUNGH. MYAENG 4-206 Center for Science & Technology, School of Information Studies, Syracuse University, Syracuse, NY 13244 and ROBERT R. KORFHAGE*’ Department of Information Science, University of Pittsburgh, Room 737 LIS Building, Pittsburgh, PA 15260 (Received 21 May 1988; accepted in final form 26 April 1990) Abstract-One difficult problem in information retrieval (IR) is the proper interpretation of user queries. It is extremely hard for users to express their information needs in a specific yet exhaustive way. In an effort to alleviate this problem, two theoretical models have been proposed to utilize user characteristics maintained in the form of a user profile. Although the idea of integrating user profiles into an IR system is intuitively appealing, and the models seem viable, no research to date has established a foundation for the roles of user profiles in such a system. Aiming at the investigation of the roles of user profiles, therefore, this study first identifies and extends various query/profile interaction models to provide a ground upon which the investigation can be undertaken. From a continuum of models characterized on the basis of interaction types, metrics, and parameters, nearly 400 models are chosen to investigate the “model space.” New measures are developed based on the notion of user satisfaction/frustration. In addition, three different criteria are used to guide users in making judgments on the quality of retrieved items. Analysis of the data obtained from the experiments shows that, for a wide variety of criteria and metrics, there are always some query/profile interaction models that outperform the query alone model. In addition, preferable characteristics for different criteria are identified in terms of interaction types, parameters, and metrics. 1. INTRODUCTION The problem of retrieving information from natural language databases has been studied during the past quarter century. In traditional context, retrospective information retrieval (IR) systems are those in which a user initiates the search process by means of a set of active queries and receives a set of references to items of potential interest. One difficult problem in such systems is the transformation of the user’s information need to the form of an explicit query which accurately matches the original intention, and retrieves all items of interest in the database being searched, and only those. Therefore, users often have great difficulty in using an IR system successfully regardless of the query language implementation (e.g., a vector form, a boolean expression of terms, a combination of both [1,2,3], or other retrieval models [4,5,6,7,8]). As a result, user queries are not completely satisfactory in expressing the needs in most retrieval situations. It seems natural that the output of a system based on such a query is necessarily incomplete and unsatisfactory. One reason underlying this query formulation problem is the mismatch between terms used in a query and those used in documents. Blair and Maron [9] analyzed the poor performance of a large-scale IR system and contended that it is exceedingly difficult for users to predict the exact words, word combinations, and phrases that are used by all (or most) relevant documents and only (or primarily) by those documents. This difficulty is usually *All editorial correspondence should be sent to Robert R. Korfhage. 719 GOOG-WRD-00195301

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