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`UNITED STATES PATENT AND TRADEMARK OFFICE
`______________________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`______________________
`
`TWITTER, INC.,
`Petitioner
`
`v.
`
`PALO ALTO RESEARCH CENTER INC.,
`Patent Owner
`______________________
`Case IPR2021-01459
`Patent 8,489,599
`______________________
`
`EXPERT DECLARATION OF DON TURNBULL PHD IN SUPPORT
`FOR INTER PARTES REVIEW OF U.S. PATENT No. 8,489,599
`
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`Twitter Exhibit 1003
`Page 00001
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`IPR2021-01459
`U.S. Patent 8,489,599
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`TABLE OF CONTENTS
`Introduction ...................................................................................................... 4 
`I. 
`Background and Qualifications ....................................................................... 5 
`II. 
`Priority Date and One of Ordinary Skill ........................................................ 13 
`III. 
`IV.  Materials Relied Upon ................................................................................... 14 
`V. 
`Background on the State of the Art ............................................................... 15 
`VI.  The ’599 Patent .............................................................................................. 21 
`A.  Overview of the ’599 Patent ................................................................ 21 
`B. 
`Overview of the ’599 Patent Prosecution History .............................. 30 
`C. 
`Claim Construction of the ’599 Patent Claims ................................... 31 
`VII.  The Challenged Claims are Invalid ............................................................... 33 
`A. 
`Legal Standards ................................................................................... 33 
`B. 
`Ground 1: Claims 1, 6, 7, 9-12, 17-19, 24, and 25 are obvious
`over PALLAS; Ground 2: Claims 1, 4, 6, 7, 9-12, 15, 17-19, 22,
`24, and 25 are obvious over PALLAS in view of Yau; Ground
`3: Claims 1, 4, 6, 7, 9-12, 15, 17-19, 22, 24, and 25 are obvious
`over PALLAS in view of Kim; Ground 4: Claims 1, 4, 6, 7, 9-
`12, 15, 17-19, 22, 24, and 25 are obvious over PALLAS in view
`of Yau and Kim. .................................................................................. 39 
`Overview of “PALLAS: Personalised Language Learning
` 
`on Mobile Devices” (“PALLAS”) ............................................ 39 
`Overview of “A Context-aware and Adaptive Learning
`Schedule framework for supporting learners’ daily
`routines” (“Yau”) ...................................................................... 47 
`Overview of “CASTmiddleware: Security Middleware of
`Context-Awareness Simulation Toolkit for Ubiquitous
`Computing Research Environment” (“Kim”) ........................... 50 
`PALLAS, Yau, and Kim Are Analogous Art ........................... 52 
`Claim 12 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, or (c) PALLAS in view Kim,
`or (d) PALLAS in view of Yau and Kim. ................................. 55 
`
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`Claim 15 is Rendered Obvious Over (a) PALLAS in
`view of Yau, (c) PALLAS in view of Kim, or (c)
`PALLAS in view of Yau and Kim. ......................................... 149 
`Claim 17 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, (c) PALLAS in view of Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 167 
`Claim 18 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, (c) PALLAS in view of Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 170 
`Claim 19 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, or (c) PALLAS in view Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 173 
`  Claim 22 is Rendered Obvious Over (a) PALLAS in
`view of Yau, (b) PALLAS in view of Kim, or (c)
`PALLAS in view of Yau and Kim. ......................................... 271 
`  Claim 24 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, (c) PALLAS in view of Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 289 
`  Claim 25 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, (c) PALLAS in view of Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 293 
`  Claim 1 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, (c) PALLAS in view of Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 296 
`  Claim 4 is Rendered Obvious Over (a) PALLAS in view
`of Yau, (b) PALLAS in view of Kim, or (c) PALLAS in
`view of Yau and Kim. ............................................................. 302 
`  Claim 6 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, (c) PALLAS in view of Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 304 
`  Claim 7 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, (c) PALLAS in view of Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 319 
`  Claim 9 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, (c) PALLAS in view of Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 330 
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`  Claim 10 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, (c) PALLAS in view of Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 338 
`  Claim 11 is Rendered Obvious Over (a) PALLAS, (b)
`PALLAS in view of Yau, (c) PALLAS in view of Kim,
`or (d) PALLAS in view of Yau and Kim. ............................... 339 
`VIII.  Secondary Considerations ........................................................................... 340 
`IX.  Conclusion ................................................................................................... 341 
`
`APPENDIX A (C.V., List of Publications, List of Testifying Experience)
`APPENDIX B (List of Materials Considered)
`APPENDIX C (Claim Charts)
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`I, Dr. Don Turnbull, hereby declare under penalty of perjury under the laws
`
`
`
`of the United States of America:
`
`I. INTRODUCTION
`1.
`I have been retained to provide assistance regarding U.S. Patent
`
`No. 8,489,599 (“the ’599 patent”). Specifically, I have been asked to consider the
`
`validity of claims 1, 4, 6, 7, 9-12, 15, 17-19, 22, 24 and 25 of the ’599 patent (the
`
`“Challenged Claims”). Except as otherwise indicated, I have personal knowledge
`
`of the facts and opinions set forth in this declaration, and believe them to be true. If
`
`called upon to do so, I would testify competently thereto. I have been warned that
`
`willful false statements and the like are punishable by fine or imprisonment, or both.
`
`2.
`
`I am being compensated for my time at my standard consulting rate of
`
`$725 per hour. I am also being reimbursed for expenses that I incur during the
`
`course of this work. My compensation is not contingent upon the results of my
`
`study, the substance of my opinions, or the outcome of any proceeding involving the
`
`challenged claims. I have no financial interest in the outcome of this matter or in
`
`the pending litigation between Petitioner Twitter, Inc. and Patent Owner Palo Alto
`
`Research Center Inc.
`
`3.
`
`A table of contents and a list of exhibits referenced herein are included
`
`above.
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`
`
`4
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`II. BACKGROUND AND QUALIFICATIONS
`4.
`I offer statements and opinions on behalf of Twitter, Inc. (“Twitter”),
`
`generally regarding the validity, novelty, prior art, obviousness considerations, and
`
`understanding of a person of ordinary skill in the art as it relates to U.S. Patent No.
`
`8,489,599. Attached hereto as Appendix A is a true and correct copy of my
`
`Curriculum Vitae describing my background and experience.
`
`5.
`
`I am an expert in software design and architecture, including Internet,
`
`Web and mobile systems, with over 30 years of research and development
`
`experience. My research and development endeavors cover various technologies
`
`related
`
`to
`
`information retrieval, quantitative behavioral modeling, mobile
`
`computing, algorithmic advertising optimization, personalization, human-computer
`
`interaction design, and information system analytics, some of which are subject to
`
`patent and trade-secret protection.
`
`6. My current work centers on software research and design in the areas
`
`of information systems. This work includes consumer and enterprise applications
`
`such as web-centric and mobile technologies with functionality implemented as
`
`mobile applications, software as a service (SaaS) analytics systems, and web-based
`
`applications such as e-Commerce platforms. These applications utilize data science
`
`and machine learning to collect user behavior and categorize advertising campaign
`
`data accordingly.
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`I am also involved in helping software companies, from small startups
`
`
`
`7.
`
`to large corporations, create new technologies and applications. To advise these
`
`companies, I research and monitor academic and industry technology developments
`
`to keep up-to-date regarding advances in the field. I am also aware of the history of
`
`software development from my professional and academic experience over the past
`
`30 years.
`
`8. My academic career concentrated on advances
`
`in computing
`
`technology including hypertext systems and data-centric empirical systems design.
`
`I received a B.A. in General Studies (in “Knowledge Engineering,” i.e., computer
`
`science, psychology, and philosophy) from The University of Texas at Arlington in
`
`1988 with an early focus on artificial intelligence and expert systems and networked
`
`systems. My career in industry began in 1989, as a software developer creating
`
`mainframe application expert system software to format hypertext documents. I
`
`followed the technology advancement into personal computing and subsequently
`
`designed and built Macintosh, Microsoft Windows, and IBM OS/2 software for
`
`client/server applications that worked with (relational) databases over networks,
`
`which proved to be much of the supporting technology for Internet and Web
`
`applications. This included programming and working as a database administrator
`
`and using early Internet networking tools. I also designed and built early hypertext
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`(SGML) authoring tools, which led to a more commercial use of the Internet
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`
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`beginning in the mid 1990’s. This also allowed me to become familiar with Web
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`
`
`technology including browsers and server applications by 1993.
`
`9.
`
`In 1995, I earned an M.S. in Information, Design and Technology from
`
`the Georgia Institute of Technology where my concentration was on Internet
`
`technologies and Web systems in their early days. My work at Georgia Tech
`
`included researching digital media, researching Web server technology (including
`
`Proxy Servers), building Web sites, designing Web-based content management
`
`systems and software development methodologies, as well as Web-based
`
`information retrieval systems. In 1994, I was a very early adopter of Web
`
`technologies. I configured and ran one of the first Web sites on the World Wide
`
`Web (“the Web”) - 1 out of the first 10,000 sites, compared to an estimated
`
`1,000,000,000+ sites to date.
`
`10. My graduate studies at Georgia Tech let me use and experiment with
`
`many cutting-edge technologies, including early handheld computing platforms such
`
`as the Apple Newton Message Pad and SONY Magic Link systems and piqued my
`
`interest in researching how mobile and networked computing would change how we
`
`use computers. My research work at Georgia Tech included deploying Web servers
`
`and running early Web sites, as well as researching Web sites as applications for
`
`user interaction. My Master’s research project at Georgia Tech also involved
`
`architecture and design of what I coined an “Object-Oriented Information
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`Development” methodology and platform to build and organize information into a
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`
`
`Web site (hyperdocument) based on a user profile and content analysis and
`
`categorization.
`
`11. This Web-based work led to my working at IBM, where I was a
`
`researcher and a Lead Technical Architect and worked on building an Internet
`
`client/server platform for a multimedia client application combined with a database-
`
`driven Web site—the IBM-World Book Interactive Encyclopedia. I also contributed
`
`to designs and advised on numerous other ongoing Internet-focused projects at IBM,
`
`including Web site development tools for eCommerce small business Web sites,
`
`large enterprise (intranet) Web sites including portals, as well as the foundations for
`
`a Web site usability practice at IBM to evaluate Web use of IBM software and
`
`server-based applications.
`
`12. While I began my doctoral work at the University of Toronto in 1996,
`
`I also worked at the IBM Centre for Advanced Studies in Toronto where I researched
`
`database technologies (such as improving statistical and algorithmic database
`
`functionality) and Web Analytics in their earliest incarnations, including collecting
`
`data with proxy servers and using early versions of groupware communication
`
`systems. I continued my Internet information system work as a researcher at the
`
`University of Toronto where I investigated Web browser technologies and Web
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`server applications.
`
` I conducted research into large-scale digital content
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`repositories, enterprise Web systems interaction, early work into Web Data Mining
`
`
`
`and Web Analytics and data capture solutions for understanding Web use. I installed
`
`and configured many different Web servers and Web application development tools
`
`and frameworks on various operating systems and experimented with Web server
`
`techniques, programming tools, platforms, architectures, protocols and data
`
`collection methods. While in Toronto, I also designed and developed an application
`
`to collect Web browser user activity and a platform for analyzing the activity to
`
`predict Web use and build experimental user interest profiles.
`
`13.
`
`In 2000, I built upon these ideas and helped to start a company in 2000
`
`called Outride, which was a spin-out from Xerox PARC, to collect Web user activity
`
`and provide personalized Web search results. Our work was focused on Web
`
`browser data collection via browser toolbars, bookmarking add-ons or other
`
`networking applications to build a behavioral model of an individual user’s Web
`
`surfing behavior, preferences and user attributes (such as location, with a strategy to
`
`evolve into personalizing mobile information network use) and topics of interest to
`
`deliver augmented, personalized, contextually-relevant information such as search
`
`results and bookmarks. Outride was quickly acquired by one of our business
`
`partners, Google, in 2001, including Outride’s systems, data and intellectual
`
`property including trade secrets and filed patents such as my patent on an “Interface
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`and System for Providing Persistent Contextual Relevance for Commerce Activities
`
`
`
`in a Network Environment” (U.S. Patent No. 7,089,237).
`
`14. After the sale of Outride, I returned to Toronto, and, in 2002, I received
`
`a Ph.D. in Information Studies from the University of Toronto where my research
`
`centered on building software and analyzing data collected from Web information
`
`systems, culminating with a dissertation focused on “Knowledge Discovery in
`
`Databases of Web Use: A Search for Informetric and Behavioral Models of Web
`
`Information Seeking.” This work comprised large-scale data collection of Web user
`
`behavior and a custom-programmed data mining and analysis system to characterize
`
`Web users’ activities and preferences to enable personalization systems for
`
`providing customized information that could include advertisements.
`
`15. From 2002-2009, I was an Assistant Professor at the School of
`
`Information at The University of Texas at Austin where I created and taught a variety
`
`of graduate-level courses including: Information Architecture and Web Design; Web
`
`Information Retrieval, Evaluation & Design; the Semantic Web; Information
`
`System Analytics; and Web Information System Design and Knowledge
`
`Management Systems. As faculty, principal investigator, and research team director,
`
`my areas of exploration included designing information system interfaces and
`
`architectures; large-scale data mining and algorithms (including Web use data for
`
`personalization); techniques for interface design for multimedia access; mobile
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`interaction designs; Web content classification; and the design of Web search
`
`
`
`engines, as well as studying their use.
`
`16. While at UT Austin, I created and managed a number of research
`
`projects. These projects included information architecture and design for Web pages
`
`and Web sites; a survey of the history of technologies and functionality in Web
`
`browsers; a Web content classification system; and a set of methods for Web blog
`
`content analysis and topic distillation. One set of research projects, begun in 2003,
`
`involved mobile application design including mobile device network access
`
`applications (such as Web browsers and email applications) with industry partners
`
`such as Motorola, Compaq and Microsoft.
`
`17.
`
`I also advised graduate students and coordinated research and
`
`development of prototype systems including targeted and location-based advertising
`
`techniques, algorithms and platforms. I also authored papers and presented at both
`
`industry and academic conferences on mobile technologies. Additionally, I directed
`
`graduate-level research groups focused on Knowledge Management Systems (KMS)
`
`and Computer Supported Cooperative Work (CSCW) that encompassed group
`
`communication technologies including email and other collaborative tools ranging
`
`from shared document systems to management of email content in personal and
`
`organizational contexts. I also authored academic papers and presented at both
`
`industry and academic conferences on KMS topics.
`
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`I am also the author of numerous academic publications including: a
`
`
`
`18.
`
`textbook on Web-based information seeking and knowledge work; articles on
`
`human-computer interaction design; personalization for Web-information-retrieval
`
`and recommender systems; and numerous definitive works on information-
`
`architecture (Web site) methodologies, designs, and implementations. In addition, I
`
`am the named inventor on at least one United States patent “Interface and system for
`
`providing persistent contextual relevance for commerce activities in a networked
`
`environment” (U.S. Patent No. 7,089,237) involving Web technologies focused on
`
`content delivery and personalization.
`
`19.
`
`I have also continued to consult with large companies and small startups
`
`in these areas of research with a more recent focus in the last decade on mobile
`
`technologies. One example is my work with a startup called Wyley Interactive, in
`
`which I designed and built part of a system to analyze mobile application usage and
`
`to deconstruct usage into a taxonomy of activities and then personalize advertising
`
`campaigns around this mobile application usage.
`
`20.
`
`In the last few years I have also been advising another startup,
`
`ThinkCX, to help design an entire machine intelligence data collection and analysis
`
`platform for mobile Web usage and mobile advertising attribution focused on
`
`network location and other mobile user characteristics, including detecting mobile
`
`device type. I continue to research and review academic literature on topics of
`
`
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`interest and still participate in academic work, such as my recent work as the Chair
`
`
`
`for the Canadian Artificial Intelligence Conference Industry Track in 2018.
`
`21. Other details concerning my background, academic work, and
`
`professional history are set forth in my curriculum vitae, which is attached as
`
`Appendix A to this declaration.
`
`22. A complete listing of the papers that I have authored and co-authored
`
`and a list of my testifying experience is included in Appendix A.
`
`III. PRIORITY DATE AND ONE OF ORDINARY SKILL
`23.
`I understand that a person of ordinary skill in the art is a hypothetical
`
`person who is presumed to have known the relevant art at the time of the invention.
`
`I further understand that a person of skill in the art is also a person of ordinary
`
`creativity. I understand that in many cases a person of ordinary skill will be able to
`
`fit the teachings of multiple patents together. I further understand that the factors
`
`that may be considered in determining the ordinary level of skill in a field of art
`
`include the level of education and experience of persons working in the field; the
`
`types of problems encountered in the field; and the sophistication of the technology
`
`at the time of the invention, which I understand is asserted to be December 2, 2008.
`
`I understand that not every factor may be present in a particular case. I understand
`
`that a person of ordinary skill in the art is not a specific real individual, but rather is
`
`a hypothetical individual having the qualities reflected by the factors above. I
`
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`understand that a person of ordinary skill in the art would also have knowledge from
`
`
`
`the teachings of the prior art, including the art cited below.
`
`24.
`
`In my opinion, on or before December 2, 2008, persons of ordinary skill
`
`in the art (“POSITA”) relating to the technology of the ’599 patent would have had
`
`a bachelor’s degree in software, computer, or electrical engineering or computer
`
`science with at least two years’ experience in software development, including with
`
`respect to context-aware devices and systems, or the equivalent. Additional graduate
`
`education could substitute for professional experience, or significant experience in
`
`electronic messaging could substitute for formal education. I understand that
`
`POSITA are presumed to have knowledge of all relevant prior art, and would thus
`
`have been familiar with each of the references cited herein and the full range of
`
`teachings they contain.
`
`25. Well before December 2, 2008, my level of skill in the art was at least
`
`that of POSITA. I am qualified to provide opinions concerning what POSITA would
`
`have known and understood at that time, and unless otherwise stated, my analysis
`
`and conclusions herein are from the perspective of POSITA as of December 2, 2008.
`
`IV. MATERIALS RELIED UPON
`26.
`In reaching the conclusions described in this declaration, I have relied
`
`on the documents and materials cited herein as well as those identified in Appendix
`
`B attached to this declaration. These materials comprise patents, related documents,
`
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`and printed publications. Each of these is a type of document that experts in my
`
`
`
`field would reasonably rely upon when forming their opinions.
`
`27. My opinions are also based upon my education, training, research,
`
`knowledge, and personal and professional experience.
`
`V. BACKGROUND ON THE STATE OF THE ART
`28.
`In my opinion, prior to December 2, 2008, the prior art had already
`
`disclosed context-aware systems, including context-aware systems that presented
`
`content to a user based on the user’s context and performed an action based on the
`
`user’s response to the presented content.
`
`29. As discussed below, receiving a user response and determining
`
`whether the user response matches an expected response and performing an
`
`action based on the outcome of the determination was added to the claims to
`
`overcome the prior art. EX1002 (Prosecution History), 360. And, the claims were
`
`allowed based on Applicant’s argument that the prior art did not disclose
`
`determining whether a received response matches an expected response, and
`
`performing an action based on the outcome of the determination. EX1002
`
`(Prosecution History), 420-424, 449-450. But these limitations were well-known
`
`before the ’599 patent.
`
`30. For example, Petersen, et al., “PALLAS: Personalised Language
`
`Learning on Mobile Devices” (“PALLAS”) (the primary reference herein), which
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`published March 26, 2008 (see §VII.B.1) disclosed, “personalised and
`
`
`
`contextualised access to learning resources via a mobile device” and, inter alia,
`
`learners taking exercises/tests/quizzes and “automatically updat[ing]” the learner’s
`
`“skill level” and adjusting the “difficulty level” of later-presented content depending
`
`on how the learner performs, noting “feedback should be provided to learner
`
`responses.” E.g., EX1004 (PALLAS), Abstract, 54, 55.
`
`31. WO 2006/104345 (“Lee”), which published October 5, 2006, disclosed
`
`an alarm clock system that, e.g., “output[s] a request for confirming whether or not
`
`the user is fully awake,” “receiv[es the user’s] reply in response… and confirm[s]
`
`whether or not the reply meets a requirement” (e.g., matches a “predetermined
`
`sentence”) and “play[s] the morning call music again when the reply does not meet
`
`the requirement.” E.g., EX1010 (Lee), 6:2-19, 15:12-25.
`
`32. U.S. Patent No. 7,130,622 (“Vänskä”), which issued issued October
`
`31, 2006, disclosed, inter alia, deleting disposable mini-applications based on a
`
`user’s response: “if a trigger condition for deletion of the executable software item
`
`is satisfied, delet[e] the executable software item.” E.g., EX1011 (Vänskä), Abstract
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`(“activation, deactivation and deletion in a mobile terminal are defined by trigger
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`parameters and rules,” including location), 2:1-4.
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`33. As discussed below, the ’599 patent’s other claimed features were also
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`well-known long before its filing, and combining them would have been obvious.
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`34. For example, receiving a content package and receiving information
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`
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`that includes content, a trigger condition, and expected response was well-known
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`long before the ’599 patent.
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`35. PALLAS disclosed, for example, a server receiving a content package
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`including an “exercise”/“test”/“Quiz”; “context triggers” for displaying it; and the
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`correct answers. E.g., EX1004 (PALLAS), 56, 57, 58, Fig.2. PALLAS’s content
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`package is also received by, e.g., a mobile phone or PDA whose “mobile client…
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`displays triggers that are fired based on the context information. For example, the
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`learner is in the vicinity of an exhibition that fits the [learner’s] profile.” E.g.,
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`EX1004 (PALLAS), 57, Fig.6:
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`36. Yau, et al., “A Context-aware and Adaptive Learning Schedule
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`framework for supporting learners’ daily routines” (“Yau”), which published May
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`7, 2007, and is one of the secondary references herein, discloses, for example
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`receiving content (e.g., “formal assessments,”); rules including a trigger condition
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`
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`(e.g.,“IF-THEN rules” and “context-triggered actions,” such as displaying the
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`formal assessments); and answers to the assessments. E.g., EX1005 (Yau), 4, 5.
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`37. Lee discloses, e.g., receiving a package including content (e.g., “pre-
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`selected morning call music”); rules including a trigger condition (e.g., “morning
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`call time” at which music is played); and an expected response (e.g., “predetermined
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`sentence” that a user must “accurately pronounce” to deactivate the morning call
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`music). E.g., EX1010 (Lee), 6:2-19, 14:2-10, 15:12-25.
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`38. Vänskä discloses, for example, a package including content (e.g.,
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`“disposable mini-application”) and rules (e.g., “trigger conditions”) “downloaded
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`together with the disposable mini-application….” E.g., EX1011 (Vänskä), 3:37-46,
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`4:3-10, Fig.5.
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`39. Additionally, collecting user contextual information and determining
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`user context was well-known long before the ’599 patent.
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`40. For example, PALLAS discloses, e.g., a learner’s mobile device
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`“us[ing] a GPS unit to automatically obtain location information” and determine user
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`context. E.g., EX1004 (PALLAS), 54, 56-57, Fig.6:
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`41. Yau discloses, e.g., “retriev[ing] the contextual information from the
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`scheduled events database… and two sensors, namely GPS for location detection
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`and a microphone for noise detection” and “[a] context adaptation module…
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`identifies the learning context which the learner is currently situated in….” E.g.,
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`EX1005 (Yau), 2, 3.
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`42. Kim et al., “CASTmiddleware: Security Middleware of Context-Awareness
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`Simulation Toolkit for Ubiquitous Computing Research Environment,” ICIC2006,
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`LNCIS 344 (2006) (“Kim”), which published in 2006 and is a secondary reference
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`herein, discloses, for example, “process[ing] context information coming from
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`sensors, stor[ing] it, and convert[ing] it into high layer’s context information.” E.g.,
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`EX1006, 510.
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`43. Vänskä discloses, for example, “RF-ID tag readers” that are associated
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`
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`with a location in a mall (e.g. a particular shop) and that detect a mobile user’s entry
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`into a shop or user’s exit from the mall. E.g., EX1011 (Vänskä), 5:47-58, 12:22-32.
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`44. Other references also disclosed this limitation. See U.S. Pub.
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`2009/0265764 (“Schultz”) (cited during ’599’s prosecution) (EX1008, ¶¶0011,
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`0024) (disclosing “systems that aggregate… ‘context information’ or ‘context’”);
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`U.S. Pub. No. 2003/0063072 (“Brandenberg”) (cited during ’599’s prosecution)
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`(EX1007, ¶0016) (disclosing “contextual user profiles [that] are continuously
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`updated”); see also e.g., Isaacs, et al., “A Field Evaluation of the User Experience
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`of a Mobile Recommender of Leisure Activities” (2008).
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`45. Additionally, presenting content based on satisfaction of a trigger
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`condition was well-known before the ’599 patent.
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`46. For example, PALLAS describes, inter alia, that, “[o]ne day while
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`passing by the art gallery, [a French-language-learner’s] location-aware Smartphone
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`starts to beep. [Learner] sees a notification from PALLAS telling her that the art
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`gallery has a French art exhibition.” E.g., EX1004 (PALLAS), 53-54.
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`47. And Yau discloses, for example, “[a] Context adaptation module…
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`recommends appropriate learning activities... based on [users’] learning context.”
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`E.g., EX1005 (Yau), 2.
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`48. Lee, for example, when the “mobile morning call device” has located
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`
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`the user and “the pre-selected morning call time arrives… [it] plays… music” and
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`“a voice request[s the user] to pronounce a predetermined sentence.” E.g., EX1010
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`(Lee), 15:6-8.
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`49. Vänskä discloses, for example, an “identification number of an RF-ID
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`tag” is a “trigger parameter for activation of a mini-application,” and “location
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`information” is used “for downloading” and presenting (e.g., “activating”) the
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`“disposable mini-application.” E.g., EX1011 (Vänskä), 2:36-38, 5:32-33.
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`50. U.S. Pub. 2004/0111477
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`(“Boss”) discloses,
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`for example,
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`“display[ing]” a location message upon satisfying “the activation trigger of ‘any visit
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`within four months to a branch of this chain of coffee shops in the 48603 zip code’.”
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`EX1012 (Boss), ¶0067.
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`VI. THE ’599 PATENT
`A. Overview of the ’599 Patent
`51. The ’599 patent relates to “techniques and systems for creating and
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`present[ing] content based on contextual information.” EX1001, 1:9-11.
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`EX1001, Fig.3.
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`52. For example, ’599 states “a user… learning Japanese can program
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`content management system 240 to play ‘good morning’ in Japanese when the user
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`is moving around the bedroom before 10 AM…. [T]he user can also program
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`content management system 240 to suspend an audio clip for a given phrase for
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`seven days if the user correctly mimics the phrase in Japanese.” EX1001, 11:21-36.
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`53.
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`’599’s claims generally conc