Case 1:13-cv-00919-LPS Document 306-9 Filed 03/10/21 Page 1 of 998 PageID #: 24828
`Case 1:13-cv-00919—LPS Document 306-9 Filed 03/10/21 Page 1 of 998 PageID #: 24828
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`EXHIBIT 9 PART 1
`
`EXHIBIT 9 PART 1
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`

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`Case 1:13-cv-00919-LPS Document 306-9 Filed 03/10/21 Page 2 of 998 PageID #: 24829
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`
`
`
`
`
`
`
`Expert Report of Edward Fox, Ph.D.
`On the Invalidity of
`U.S. Patent No. 7,917,843
`
`Arendi S.A.R.L. v. Google LLC, Case No. 13-0919-LPS (D. Del.)
`Arendi S.A.R.L. v. Motorola Mobility LLC, Case No. 12-1601-LPS (D. Del.)
`
`
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`

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`Case 1:13-cv-00919-LPS Document 306-9 Filed 03/10/21 Page 3 of 998 PageID #: 24830
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`TABLE OF CONTENTS
`
`
`Page
`
`I.
`
`II.
`
`Introduction ........................................................................................................................ 1 
`A.
`My Assignment ...................................................................................................... 1 
`B.
`Background and CV Materials............................................................................... 2 
`C.
`Previous Testimony ............................................................................................... 9 
`D.
`Compensation ........................................................................................................ 9 
`The Law Of Patent Invalidity ............................................................................................ 9 
`A.
`Anticipation.......................................................................................................... 10 
`B.
`Obviousness ......................................................................................................... 12 
`C.
`Secondary Considerations of Non-Obviousness .................................................. 14 
`D.
`Ineligibility (35 U.S.C. § 101) ............................................................................. 15 
`E.
`Written Description and Enablement ................................................................... 17 
`F.
`Indefiniteness ....................................................................................................... 19 
`G.
`The Person of Ordinary Skill in the Art ............................................................... 19 
`H.
`Critical Date and Priority Date ............................................................................ 20 
`The ‘843 Patent ................................................................................................................ 20 
`A.
`The Specification of the ‘843 Patent .................................................................... 21 
`B.
`The Asserted Claims of the ‘843 Patent .............................................................. 27 
`C.
`The Prosecution of the ‘843 patent ...................................................................... 28 
`D.
`Inter Partes Review .............................................................................................. 32 
`E.
`Claim Construction .............................................................................................. 35 
`Accelerated Examination Support Documents ................................................................ 36 
`IV.
`The State Of The Art In 1997-1998 ................................................................................. 39 
`V.
`The Person Of Ordinary Skill In The Art As To The ‘843 Patent ................................... 44 
`VI.
`VII. The Inventor’s Purported Commercial Embodiments ..................................................... 44 
`A.
`Postnummer ......................................................................................................... 44 
`B.
`OneButton Contact Manager ............................................................................... 46 
`VIII. The Prior Art .................................................................................................................... 47 
`A.
`The CyberDesk System........................................................................................ 49 
`B.
`Apple Data Detector System ................................................................................ 61 
`C.
`LiveDoc System ................................................................................................... 66 
`
`III.
`
`1
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`

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`
`
`IX.
`
`D.
`
`I.
`
`J.
`
`Apple Newton MessagePad 2000 with Intelligent Assistant System
`(“Newton System”) .............................................................................................. 69 
`Eudora PRO (“Eudora System”) .......................................................................... 72 
`E.
`Microsoft Word 97 ............................................................................................... 74 
`F.
`Microsoft Outlook 97 ........................................................................................... 74 
`G.
`U.S. Patent No. 6,085,201 (“Tso”) ...................................................................... 75 
`H.
`U.S. Patent No. 6,085,206 (“Domini”) ................................................................ 76 
`I.
`U.S. Patent No. 6,377,965 (“Hachamovitch”) ..................................................... 77 
`J.
`U.S. Patent No. 5,392,386 (“Chalas”) ................................................................. 78 
`K.
`Selection Recognition Agent/Pandit .................................................................... 79 
`L.
`On-site Inspection ................................................................................................ 80 
`M.
`The Invalidity Of The Asserted Claims Of The ‘843 Patent Under 35 U.S.C.
`§§ 102 And/Or 103 .......................................................................................................... 81 
`A.
`Pandit + CyberDesk System ................................................................................ 82 
`B.
`Pandit + Eudora System ....................................................................................... 82 
`C.
`Pandit + Apple Data Detector System ................................................................. 82 
`D.
`Pandit + LiveDoc System .................................................................................... 82 
`E.
`Pandit + Newton System ...................................................................................... 82 
`F.
`Pandit + Microsoft Outlook 97 ............................................................................ 82 
`G.
`CyberDesk System + Chalas ................................................................................ 82 
`H.
`CyberDesk System + Eudora System [and/or specific publications
`describing aspects of Eudora] .............................................................................. 82 
`CyberDesk System + Apple Data Detector System [and/or specific
`publications describing aspects of the Apple Data Detector System] ................. 82 
`CyberDesk System + Newton System [and/or specific publications
`describing aspects of the Newton System] .......................................................... 83 
`CyberDesk System + LiveDoc System [and/or specific publications
`describing aspects of the LiveDoc System] ......................................................... 83 
`CyberDesk System + Selection Recognition Agent System [and/or
`specific publications describing aspects of the Selection Recognition
`Agent System, including Pandit] ......................................................................... 83 
`CyberDesk System + Domini .............................................................................. 83 
`CyberDesk System + Microsoft Word 97 ............................................................ 83 
`Apple Data Detector System + Chalas ................................................................ 83 
`
`K.
`
`L.
`
`M.
`N.
`O.
`
`2
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`

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`
`
`P.
`
`Q.
`
`R.
`
`S.
`
`T.
`
`Apple Data Detector System + Eudora System [and/or specific
`publications describing aspects of the Eudora System] ....................................... 83 
`Apple Data Detector System + CyberDesk System [and/or specific
`publications describing aspects of the CyberDesk System] ................................ 83 
`Apple Data Detector System + Newton System [and/or specific
`publications describing aspects of the Newton System] ...................................... 83 
`Apple Data Detector System + LiveDoc System [and/or specific
`publications describing aspects of the LiveDoc System] .................................... 83 
`Apple Data Detector System + Selection Recognition Agent System
`[and/or specific publications describing aspects of the Selection
`Recognition Agent System, including Pandit] ..................................................... 83 
`Apple Data Detector System + Domini ............................................................... 83 
`Apple Data Detector System + Microsoft Word 97............................................. 83 
`Apple Data Detector System + Microsoft Outlook 97 ........................................ 83 
`Eudora System + CyberDesk System [and/or specific publications
`describing aspects of the CyberDesk System] ..................................................... 83 
`Eudora System + Apple Data Detector System [and/or specific
`publications describing aspects of the Apple Data Detector System] ................. 83 
`Eudora System + Newton System [and/or specific publications describing
`aspects of the Newton System] ............................................................................ 83 
`AA. Eudora System + LiveDoc System [and/or specific publications describing
`aspects of the LiveDoc System] ........................................................................... 83 
`BB. Eudora System + Selection Recognition Agent System [and/or specific
`publications describing aspects of the Selection Recognition Agent
`System, including Pandit] .................................................................................... 84 
`CC. Chalas + CyberDesk System ............................................................................... 84 
`DD. Chalas + Apple Data Detector System ................................................................ 84 
`EE. Chalas + LiveDoc System .................................................................................... 84 
`FF.
`Chalas + NewtonSystem ...................................................................................... 84 
`GG. Chalas + Selection Recognition Agent System ................................................... 84 
`The Asserted Claims Lack Support In The Patent’s Written Description ....................... 93 
`X.
`The Value Of The Asserted Claims With Respect To The Prior Art .............................. 98 
`XI.
`EXHIBIT LIST .......................................................................................................................... 102 
`
`U.
`V.
`W.
`X.
`
`Y.
`
`Z.
`
`3
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`Case 1:13-cv-00919-LPS Document 306-9 Filed 03/10/21 Page 6 of 998 PageID #: 24833
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`
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`I.
`
`INTRODUCTION
`A. My Assignment
`
`1.
`
`I have been retained as an expert in this case by counsel for Defendants Google
`
`LLC (“Google”) and Motorola Mobility LLC (“Motorola”). Although this report contains my
`
`opinions with regard to the asserted claims against both Google and Motorola, I intend to offer
`
`testimony at trial as to Google and Motorola, individually. I expect to testify at trial regarding
`
`the matters set forth in this report, including the technical background and state of the art
`
`relevant to the asserted claims of U.S. Patent No. 7,917,843 (“the ‘843 patent”), if asked about
`
`these matters by the Court or by the parties’ attorneys. Additionally, I may discuss my own
`
`work in the field, and knowledge of the state of the art in the relevant time period. I may rely on
`
`handbooks, textbooks, technical literature, and the like to demonstrate the state of the art in the
`
`relevant period and the evolution of the relevant technologies. I may also rely upon witness
`
`testimony or any other evidence that I obtained during the pendency of this case or was
`
`introduced at trial. A list of the materials I have considered in preparing this report is identified
`
`in my report or is listed in Ex. A.
`
`2.
`
`I have been asked for my expert opinion concerning the validity of the asserted
`
`claims and related issues presented in this report. I conclude that the asserted claims are invalid
`
`for the reasons stated below.
`
`3.
`
`I understand that the Plaintiff Arendi S.A.R.L. (“Arendi”) may submit one or
`
`more expert reports responding to this report. I reserve the right to rebut any positions taken in
`
`those reports and to consider any new evidence presented in the case. I also reserve the right to
`
`supplement my opinions based on any new or clarified claim constructions provided by the Court
`
`or any other rulings from the Court impacting the scope of the asserted claims.
`
`1
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`
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`B.
`
`4.
`
`Background and CV Materials
`
`As shown by a copy of my CV attached as Ex. B, my professional career has
`
`spanned over 36 years. Based on my academic and work experience with information retrieval,
`
`interactive information systems, web archiving, digital libraries, hypertext/hypermedia, and
`
`Web/Internet technologies, I believe I am well-positioned to understand and address the skills
`
`and mindset of a person of ordinary skill in the art (“POSITA”) in this field circa 1997-1998.1
`
`5.
`
`My education includes a B.S. in Electrical Engineering (Computer Science
`
`Option) from the Massachusetts Institute of Technology (MIT) completed in 1972, followed by
`
`an M.S. in Computer Science from Cornell University in 1981. I received a Ph.D. in Computer
`
`Science from Cornell University in 1983. My undergraduate advisor was J. C. R. Licklider, then
`
`Director of Project MAC, who, when working at DARPA, managed projects that led to the
`
`Internet. My graduate advisor was Gerard Salton, often called the father of information retrieval
`
`(the field that works with search engines). My doctoral dissertation (1983) considered
`
`bibliographic records with author names, document text analysis, text matching, and database
`
`calls in systems with multiple interacting programs.
`
`6.
`
`Before college, starting in 1965, I took courses about computing, first at
`
`Columbia University on Saturdays, and then at Stevens Institute of Technology in the summer,
`
`working with parsing and analysis of text files. As an undergraduate at MIT, I worked with early
`
`editors and text processors. During one summer job, I worked to explore how to automate
`
`newspapers, including studying the latest electronic publishing technologies. My B.S. thesis
`
`concerned collecting electronic texts, document text analysis, searching over a collection, and
`
`text matching such as of queries with documents. During another summer I programmed a
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`PDP‑8 with display processor and light pen, exploring early human-computer interaction
`
`1 I provide the definition of a POSITA later in my report.
`
`2
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`

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`
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`methods and user interfaces. During the academic year I was paid to help users of early time-
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`sharing computers such as CTSS. As founder of the Student Information Processing Board
`
`(SIPB, still operating at MIT), I interacted with many around campus with computing systems,
`
`helping students gain access.
`
`7.
`
`I have been a professor of Computer Science for more than 36 years, teaching
`
`courses each year, including about information retrieval, digital libraries, hypertext, database
`
`management, data structures, artificial intelligence, networked information, big data, text
`
`summarization, computational linguistics / natural language processing, and multimedia as well
`
`as textual information. From September 1983 through May 1988, I served as an Assistant
`
`Professor of Computer Science at Virginia Polytechnic Institute and State University (Virginia
`
`Tech). I served Virginia Tech as an Associate Professor until April 1995, when I was promoted
`
`to Professor. I have continued in that capacity since, but also became a Professor, by courtesy, in
`
`Virginia Tech’s Department of Electrical and Computer Engineering, in February 2016. Since
`
`January 1998, I have been the Director of the Digital Library Research Laboratory at Virginia
`
`Tech. From June 1990 to June 2014, I was the Associate Director for Research at Virginia
`
`Tech’s Computing Center, a position that evolved to Faculty Advisor to Information
`
`Technology. I received an award on 16 October 2015 for Research Impact in Human-Computer
`
`Interaction, conferred by the VT Center for HCI, for which I served as a founding member; my
`
`relevant activities included working on information visualization, user interfaces, forms for
`
`managing information, and connections with database and information retrieval systems.
`
`8.
`
`Before that, from August 1982 to April 1983, I was Manager of Information
`
`Systems at the International Institute of Tropical Agriculture, in Ibadan, Nigeria, where I helped
`
`with automation of library operations. From September 1978 to August 1982, I was Instructor,
`
`3
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`

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`
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`Research Assistant, and Teaching Assistant at the Department of Computer Science at Cornell
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`University. From September 1972 to August 1978, in Florence, SC, I was the Data Processing
`
`Manager in the Vulcraft Division of NUCOR Corporation. From September 1971 to June 1972,
`
`I was a Data Processing Instructor at Florence Darlington Technical College.
`
`9.
`
`While at Vulcraft, I led implementation of a system for payroll, and supported the
`
`sales department. These activities involved working with names and addresses, pulling that
`
`information from databases, inserting names and addresses into documents and forms, and
`
`allowing editing and updating of those names and addresses.
`
`10.
`
`During the summer of 1979, I worked at IBM FSD in Owego, NY. There I
`
`served as assistant to the database administrator. I worked with System R, often regarded as the
`
`first large relational database system, which was a precursor to other IBM products like DB2.
`
`Also during my period at Cornell, I served as graduate teaching assistant for a course on database
`
`management. By 1982 I had led implementation of a new version of the SMART system, a
`
`research vehicle for study of search engines. This stored information in the INGRES database
`
`management system, allowing pulling out from the database of information like names. It
`
`supported document text analysis, text matching, and database calls.
`
`11.
`
`I am a member of the Association for Computing Machinery (ACM) (since 1967)
`
`and its Special Interest Group on Information Retrieval (SIGIR), which I served from 1987-1995
`
`as vice chairman and then chairman. I served from 1988-1991 on the ACM Publications Board,
`
`and again in 2018-2019 on that Board as co-chair of its Digital Libraries Committee. ACM has
`
`awarded me seven recognition of service awards. I am a Fellow of ACM (cited for contributions
`
`in information retrieval and digital libraries) and a Fellow of the Institute of Electrical and
`
`Electronics Engineers (IEEE) (cited for leadership in digital libraries and information retrieval),
`
`4
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`
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`as well as a member of IEEE-CS. Regarding its Technical Committee on Digital Libraries, I
`
`served through 2018 on its Executive Committee, and was its chairman 2004-2008. I also am a
`
`member of the Association for Information Science & Technology and Sigma Xi (since 1972).
`
`12.
`
`Since 1987, I have led activities so that theses and dissertations could be prepared,
`
`archived, and made accessible in electronic forms (e.g., over the World Wide Web). Since 1996,
`
`I have served as Executive Director of the Networked Digital Library of Theses and
`
`Dissertations (NDLTD), which was incorporated in 2003. I also serve as Founder and Chairman
`
`of the Board for NDLTD, which now has over 5.9 million records for theses and dissertations in
`
`its Union Catalog. Since the beginning, this work has concerned electronic publishing, including
`
`use of word processors, with varied formats of textual documents, including Word and PDF, and
`
`related handling of metadata, including author names, as well as related search and archiving
`
`technologies and standards. In addition, I have been involved since 1983 in another part of
`
`widespread sharing of scholarly works, by way of technical reports, and so can attest to their
`
`suitability as prior art publications. For example, my Cornell University Department of
`
`Computer Science technical report TR83-561, “Characterization of two new experimental
`
`collections in computer and information science containing textual and bibliographic concepts,”
`
`from 1983, has been cited more than 125 times according to Google Scholar. My expertise
`
`regarding technical reports is further documented by professional service, publication, and
`
`funded project activities such as: (a) K. Maly, E. Fox, J. French, and A. Selman. Wide Area
`
`Technical Report Service, TR_92_44, Old Dominion Univ. Dept. of Computer Science, Dec.
`
`1992; (b) E. Fox, Technical Reports / Dissertations. Invited project presentation for Monticello
`
`Electronic Library meeting, sponsored by SURA, SURAnet, SOLINET, and NSF, July 29-30,
`
`1993, Atlanta; (c) National Science Foundation CISE Grant NSF-CDA-9308259: Wide Area
`
`5
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`
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`Technical Report Server, principal investigators: K. Maly (ODU), E. Fox, J. French (UVA), and
`
`A. Selman (SUNY Buffalo); (d) Chair: Workshop for Working Group on Theses, Technical
`
`Reports, and Dissertations, in Monticello Electronic Library Initiative, sponsored by SURA and
`
`SOLINET, Aug. 12-13, 1994, Virginia Tech, Blacksburg, VA; (e) K. Maly, J. French, A. Selman
`
`and E. Fox. The Wide Area Technical Report Service. In Proc. Second International WWW ‘94:
`
`Mosaic and the Web, WWW’94, Chicago, IL, Oct. 17-20, 1994, 523-533; (f) E. Fox. World-
`
`Wide Web and Computer Science Reports. Commun. of the ACM, Apr. 1995, 38(4):43-44; (g) J.
`
`French, E. Fox, K. Maly, and A. Selman. Wide Area Technical Report Service --- technical
`
`reports online. Commun. of the ACM, Apr. 1995, 38(4):45; (h) 1995 Organizing Committee
`
`member, NSF hosted workshop on Computer Science Technical Reports, NSF, Arlington, VA,
`
`April 7-8, 1995; and (i) 1995-2001 Member, NCSTRL (Networked CS Tech. Report Library)
`
`working group (part of D-Lib working group program).
`
`13.
`
`Since December 2018, I have served as Chief Technology Officer for Mayfair
`
`Group, LLC. Mayfair develops World Wide Web based services that include the application of
`
`natural language processing, machine learning, and other technologies to summarizing text
`
`documents, in support of the insurance and legal industries.
`
`14.
`
`I have been the recipient of a number of honors and awards relating to my work in
`
`information retrieval and other areas. One related honor, at Virginia Tech, is the Xcaliber
`
`Award 2016 “for extraordinary contributions to technology-enriched learning activities” for the
`
`project “Enhanced problem-based learning connecting big data research with classes.” I have
`
`taught
`
`classes
`
`on
`
`information
`
`retrieval
`
`since
`
`the
`
`early 1980s
`
`and
`
`about
`
`multimedia/hypertext/information access since the early 1990s. I am one of the inaugural
`
`inductees to the ACM SIGIR Academy, class of 2020, aimed “to honor and recognize
`
`6
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`Case 1:13-cv-00919-LPS Document 306-9 Filed 03/10/21 Page 12 of 998 PageID #: 24839
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`
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`individuals who have made significant, cumulative contributions to the development of the field
`
`of information retrieval (IR). Inductees to the SIGIR Academy are the principal leaders in IR,
`
`whose efforts have shaped the discipline and/or industry through significant research, innovation,
`
`and/or service.” (See Announcement and Call for Nominations: ACM SIGIR Academy, Ryen
`
`W. White, ACM SIGIR Forum Vol. 54 No. 1 (June 2020).)
`
`15.
`
`I have held numerous board positions in various editorial, professional, and
`
`industry organizations and groups. For example, I served from 2010-2013 as an elected member
`
`of the Computing Research Association Board, broadly representing the U.S. computing research
`
`community.
`
`16.
`
`I have a background in many of the key areas related to handling information with
`
`computers, including information retrieval, digital libraries, Web archiving, and related human-
`
`computer interaction. This work involves theory, algorithms, systems, interfaces, and user
`
`studies, specifically involving search engines, database management, big data, data analytics,
`
`machine learning, and natural language processing.
`
`17.
`
`In these areas, I have participated in, organized, and presented at numerous
`
`conferences and workshops, and have conducted 87 tutorials in over 28 countries. I have
`
`received 135 grants to fund my research and have (co)authored 19 books and edited book series
`
`for two publishers. I have (co)supervised over 80 graduate students for their dissertation, thesis,
`
`or project. In addition, I have (co)authored 136 journal or magazine articles. I have 634 related
`
`keynotes, papers, book chapters, posters, demonstrations, and reports as well as over 350 other
`
`presentations. Google Scholar has reported that my works have been cited over 18,160 times,
`
`with an h-index of 60 and i10-index of 253. Topics covered in the above-mentioned works
`
`include: computers, programs, files, memory, access, communication, networks, links, linked
`
`7
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`

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`
`
`data, representations, tables, databases, servers, World Wide Web, HTML, proxies, hypertext,
`
`hypermedia, and queries. Since the late 1980s, my research has dealt with document text
`
`analysis, text matching, hypertext creation, distributed processing including Application
`
`Programming Interfaces (“APIs”) and other communication mechanisms, building and using
`
`database systems, and applications with user interfaces.
`
`18.
`
`I have been involved in numerous software and information systems projects and
`
`products over the years and have supervised hundreds of student team projects of these types. I
`
`have managed workstations since 1982, have worked with Apple Macintosh computers since
`
`1985, and have employed WWW browsers since 1993.
`
`19.
`
`I am an inventor on U.S. Patent No. 7,346,621, issued March 18, 2008, titled
`
`“Method and System for Ranking Objects Based on Intra-type and Inter-type Relationships.” I
`
`am lead inventor on U.S. Provisional Patent Application Serial No. 62/945,202; filed
`
`December 8, 2019; titled “Methods and Systems for Generating Declarative Statements Given
`
`Documents with Questions and Answers,” as well as U.S. Provisional Patent Application Serial
`
`No. 63/039,725; filed June 16, 2020; titled “Methods and Systems for Generating Summaries
`
`Given Documents with Questions and Answers.” I have a general understanding of the
`
`U.S. patent prosecution process and of the novelty and non-obviousness requirements for
`
`patentability.
`
`20.
`
`I am not, and have never been, an employee of the Plaintiff Arendi S.A.R.L., or of
`
`any of the defendants of the cases captioned above.
`
`21.
`
`I have received no compensation for this Declaration beyond my normal hourly
`
`compensation based on my time actually spent studying the matter and working on the
`
`8
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`Case 1:13-cv-00919-LPS Document 306-9 Filed 03/10/21 Page 14 of 998 PageID #: 24841
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`
`
`Declaration, and I will not receive any added compensation based on the outcome of the above-
`
`mentioned patent infringement suit.
`
`C.
`
`Previous Testimony
`
`22. My Consulting Summary List (Ex. C) includes a list of all cases during which in
`
`the past 5 years I have testified as an expert at trial or deposition.
`
`D.
`
`23.
`
`Compensation
`
`I am being compensated for my time for all work in conjunction with this expert
`
`report at $500/hour, but $600/hour for time spent testifying in deposition or trial. This was my
`
`customary rate for this kind of work at the time I was engaged on this matter.
`
`24.
`
`The opinions expressed in this report are my own, unless specifically otherwise
`
`stated in this report. My compensation does not depend on my testimony, nor on the outcome of
`
`this matter.
`
`II.
`
`THE LAW OF PATENT INVALIDITY
`
`25.
`
`The ‘843 patent relates back to an application filed in 1998; therefore, I
`
`understand that pre-AIA law applies to this patent.
`
`26.
`
`I am not an attorney and will offer no opinions on the law. I have relied on
`
`instructions from counsel as to the applicable legal standards to use in arriving at my opinions in
`
`this report.
`
`27.
`
`Below is my understanding regarding the applicable legal standards related to
`
`anticipation, obviousness, written description, enablement and related topics. I have been
`
`informed of the same by counsel.
`
`28.
`
`I understand that a patent is presumed valid. A party asserting invalidity of a
`
`U.S. Patent bears the burden of proving invalidity by clear and convincing evidence. Clear and
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`convincing evidence is an evidentiary standard that is higher than a preponderance of the
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`evidence but lower than beyond a reasonable doubt. Such questions of validity are applied from
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`the perspective of a POSITA at the time of the alleged invention, using the claim language and
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`the Court’s claim constructions.
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`A.
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`29.
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`Anticipation
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`Evaluation of whether a patent claim is “anticipated” is a two-step process. In the
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`first step, the language of the claim is construed as it would be understood by one of ordinary
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`skill in the art at the time of the filing of the patent application. The claim is construed by
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`referring to intrinsic evidence, which includes the claim language, the patent specification, and
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`the prosecution history. The words of patent claims are to be given their ordinary or customary
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`meaning unless the inventor has defined them (acted as his/her own lexicographer) or used them
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`differently (i.e., in a manner inconsistent with the ordinary and customary meaning). The
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`prosecution history of a patent, and related patents and applications, including the history of
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`post-grant proceedings like reexaminations, may limit the interpretation of the claim, especially
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`if the patentee disavowed or disclaimed any claim scope in order to obtain allowance of the
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`claim.
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`30.
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`I understand that the Court has issued a Markman Opinion and Order in which it
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`has construed a number of claim terms in the patent, and if there are any remaining disputed
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`claim terms, the Court may construe those as well. My testimony is based upon a review of, and
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`application of, the Court’s claim constructions. In the absence of a guiding claim construction as
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`to a particular term, I have applied my understanding of how one of ordinary skill in the art
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`would have interpreted the term. As I explain further later in my report, in some instances I have
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`used Arendi’s application of a claim term.
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`31.
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`The second step of the anticipation evaluation, after the language of the patent
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`claims has been construed, is a comparison of the properly construed claim language to the prior
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`art on a limitation-by-limitation basis.
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`32.
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`A claimed invention is “anticipated” if each and every limitation of the claim, as
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`properly construed, has been disclosed in a single prior art reference, or has been embodied in a
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`single prior art device, system, or practice, either explicitly or inherently (i.e., necessarily present
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`even if not expressly disclosed), and the claimed arrangement or combination of those limitations
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`was also disclosed either expressly or inherently, in the same prior art reference.
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`33.
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`I have been informed by counsel that anticipation cannot be established b