UNITED STATES PATENT AND TRADEMARK OFFICE
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`BEFORE THE PATENT TRIAL AND APPEAL BOARD
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`WTS Paradigm, LLC,
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`Petitioner
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`v.
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`EdgeAQ, LLC,
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`Patent Owner
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`Case IPR: Unassigned
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`Patent 7,805,461
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`DECLARATION OF DEBORAH MCGUINNESS IN SUPPORT OF
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`PETITION FOR INTER PARTES REVIEW OF U.S. PATENT NO. 7,805,461
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`WTS PARADIGM LLC EXHIBIT 1001
`1 of 94
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`BEFORE THE PATENT TRIAL AND APPEAL BOARD
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`
`
`WTS Paradigm, LLC,
`
`Petitioner
`
`v.
`
`EdgeAQ, LLC,
`
`Patent Owner
`
`
`
`Case IPR: Unassigned
`
`Patent 7,805,461
`
`
`
`
`
`
`DECLARATION OF DEBORAH MCGUINNESS IN SUPPORT OF
`
`PETITION FOR INTER PARTES REVIEW OF U.S. PATENT NO. 7,805,461
`
`
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`WTS PARADIGM LLC EXHIBIT 1001
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`Table of Contents
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`INTRODUCTION .......................................................................................... 1
`I.
`BACKGROUND AND QUALIFICATIONS ................................................ 2
`II.
`III. UNDERSTANDING OF PATENT LAW ..................................................... 6
`IV. BACKGROUND OF THE FIELD OF THE INVENTION ........................... 8
`V. OVERVIEW OF THE CHALLENGED CLAIMS ........................................ 9
`VI. LEVEL OF ORDINARY SKILL ................................................................. 12
`VII. CLAIM CONSTRUCTION ......................................................................... 12
`VIII. ANALYSIS OF THE PRIOR ART .............................................................. 14
`A. Overview of the Prior Art ................................................................... 14
`1.
`Overview of Greef ................................................................... 14
`2.
`Overview of Bader ................................................................... 16
`3.
`Overview of Weida/Carter ....................................................... 17
`4.
`Overview of Altman ................................................................ 18
`The Challenged Claims are Obvious .................................................. 19
`1.
`A person of ordinary skill would have had a reason to
`modify Greef ............................................................................ 19
`The modified version of Greef’s system would have
`contained each element of the Challenged Claims .................. 37
`Claim Chart for All Challenged Claims ............................................. 61
`C.
`IX. SECONDARY CONSIDERATIONS OF NON-OBVIOUSNESS ............. 91
`X.
`CONCLUSION ............................................................................................. 91
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`B.
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`2.
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`-i-
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`I, Deborah McGuinness, do hereby declare as follows:
`I.
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`INTRODUCTION
`1.
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`I have been retained as an expert witness on behalf of WTS Paradigm
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`LLC (“Petitioner”) for the above-captioned Petition for Inter Partes Review
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`(“IPR”) of U.S. Patent No. 7,805,461 (“the ’461 Patent”). I am being compensated
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`for my time in connection with this IPR at my standard consulting rate of $500 per
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`hour and, when working while traveling, $600. My compensation is not affected
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`by the outcome of this matter.
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`2.
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`I have been asked to provide my opinion on the validity of Claims 1–
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`11 of the ’461 Patent (“the Challenged Claims”).
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`3.
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`The ’461 Patent issued on September 28, 2010. I have been asked to
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`assume that the priority date of the’461 Patent is December 5, 2003.
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`4.
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`In preparing this Declaration, I have reviewed the ’461 Patent; the
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`related U.S. Patent No. 7,219,100 (“the ’100 patent”); the related U.S. Patent No.
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`6,810,401 (“the ’401 Patent”); the file histories of the ’461 Patent, the ’401 Patent,
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`and the ’100 Patent; various prior art references; and my knowledge of the field of
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`the invention at and before the patent’s priority date.
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`5.
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`I understand that claims in a IPR are given their broadest reasonable
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`interpretation in view of the patent specification and the understandings of one
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`having ordinary skill in the relevant art.
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`6.
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`In forming the opinions expressed in this Declaration, I relied upon
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`my education and experience in the relevant field of the art, and I have considered
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`the viewpoint of a person of ordinary skill in the relevant art, as of December 5,
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`2003.
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`II. BACKGROUND AND QUALIFICATIONS
`7. My academic training includes completing the requirements for a
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`Bachelor of Science in Computer Science and a Bachelor of Arts in Mathematics
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`from Duke University in 1980. I completed a Master of Science degree from the
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`Electrical Engineering and Computer Science Department of the University of
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`California at Berkeley in 1981. I also completed a Ph. D. in Computer Science
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`from Rutgers University in 1996.
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`8.
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`I began my professional career immediately after my Bachelor’s
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`degree and began work for AT&T Bell Laboratories in 1980. I was immediately
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`accepted into the Bell Laboratories “One Year on Campus” program which
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`supported me to be a full time Master’s student at Berkeley. Upon completion of
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`my M.S. in 1981, I returned to Bell Laboratories and began work at the Home of
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`the Future at the Home Information Systems Laboratory. In 1984, I transferred to
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`the Computing Environments and Artificial Intelligence Department in New
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`Jersey. While there, I was accepted into the Bell Laboratories Ph.D. program,
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`which supported me while I pursued a Ph.D. I simultaneously was accepted into
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`the Computer Science Ph.D. program at Rutgers. In 1985, I became the first
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`employee in the Artificial Intelligence Research department of Bell Laboratories. It
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`was during this time period that I first began to work on a type of artificial
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`intelligence system, a type of frame-representation systems, called description
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`logic-based systems. I would end up doing my dissertation in description logics
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`and I spent approximately a decade involved with description logic-based systems
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`and related artificial intelligence systems and configuration problems. In 1989 I
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`and some Bell Labs colleagues began publishing our work on description logics
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`and in the mid early 90s, we began publishing our work using frame-based systems
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`for configuration problems.
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`9.
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`Our configuration systems have been used by AT&T and Lucent to
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`configure over 6 billion dollars worth of AT&T and Lucent products. I have been
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`involved in a number of academic configuration activities including co-organizing
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`two configuration workshops and acting as a guest editor for a special journal issue
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`on configuration.
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`10.
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` While at Bell Labs and AT&T, I focused on frame-based
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`representation foundations, explanation environments for knowledge systems, and
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`application environments, including configuration application environments, for
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`frame-based systems.
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`11. As part of my work at AT&T, when populating our knowledge-based
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`systems with information, we pulled significant amounts of data by querying
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`multiple preexisting databases, most of which were relational databases, and where
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`the query language was typically SQL. This process of pulling data from the
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`relational database into the knowledge-based system was partially automated.
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`12.
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`In 1998, I left AT&T Labs research and moved to Stanford University
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`where I started as Associate Director and Senior Research Scientist of the
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`Knowledge Systems Laboratory, within the Computer Science Department. When
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`I left the lab nine years later, I was acting director of the laboratory. While at
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`Stanford, I focused on knowledge based systems. The work included creating
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`languages for representing information, designing frame representation and
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`reasoning systems for deducing information, creating explanation environments,
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`next generation web languages and environments, and building many frame-based
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`and generally AI-based applications.
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`13.
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`In 2007, I accepted an endowed chair at Rensselaer Polytechnic
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`Institute (RPI). I am the Tetherless World Senior Constellation Chair and Professor
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`of Computer Science and Cognitive Science. I am also the founding director of the
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`Web Science Research Center at RPI and I also am on the senior leadership team
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`of the RPI Institute for Data Exploration and Application. The RPI press release
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`introduces me as Web Language and Artificial
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`Intelligence Expert –
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`http://www.rpi.edu/about/inside/issue/v1n7/web.html. I am also about to become
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`an adjunct professor in the Icahn School of Medicine at Mount Sinai’s Department
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`of Preventive Medicine.
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`14.
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`I have published over 250 articles in peer-reviewed journals and
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`conferences as well as being an inventor on patents on artificial intelligence,
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`frame-based reasoning, knowledge representation, configuration, data translation
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`and integration, and applications of artificial intelligence. I have also been program
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`chair for well-respected conferences in artificial intelligence (AAAI in 2004),
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`knowledge representation (KR&R in 2002), and information and knowledge
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`management (CIKM in 2007). I am routinely on the senior program committees for
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`conferences, and I have served on editorial boards for AI journals. I have been on
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`the executive council of the Association for the Advancement of Artificial
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`Intelligence as well as on the executive boards of Knowledge Representation,
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`Description Logics, and the Semantic Web Science Foundation. I also have served
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`on Technical Advisory Boards for a number of startup companies that use artificial
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`intelligence technologies (including frame-based reasoning) including Applied
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`Semantics, Blue Chip Expert, Cerebra, Radar Networks, and Sandpiper Software.
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`15.
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`I have been recognized with honors including being made a fellow of
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`the American Association for the Advancement of Science (in 2013) for
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`“contributions to the Semantic Web, knowledge representation, and reasoning
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`environments.” I also have received the Robert Engelmore Memorial Lifetime
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`Achievement Award from the Association for the Advancement of Artificial
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`Intelligence (AAAI) Award, 2013 “for leadership in Semantic Web research and in
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`bridging AI and eScience, significant contributions to deployed AI applications,
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`and extensive service to the AI community.”
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`16. A copy of my curriculum vitae is provided in Ex. 1002, and it
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`provides a comprehensive description of my relevant experience, including
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`academic and employment history, publications, conference participation, and
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`issued and pending U.S. patents.
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`III. UNDERSTANDING OF PATENT LAW
`17.
`I understand that prior art to the ’461 Patent includes patents and
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`printed publications in the relevant art that predate the December 5, 2003, effective
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`filing date of the ’461 Patent.
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`18.
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`I understand that a claim is invalid if it is anticipated or obvious.
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`Anticipation of a claim requires that every element of a claim be disclosed
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`expressly or inherently in a single prior art reference, in combination, as claimed.
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`Obviousness of a claim requires that the claim be obvious from the perspective of a
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`person of ordinary skill in the relevant art at the time the alleged invention was
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`made. I understand that a claim may be obvious from a combination of two or
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`more prior art references.
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`19.
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`I understand that an obviousness analysis requires an understanding of
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`the scope and content of the prior art, any differences between the alleged
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`invention and the prior art, and the level of ordinary skill in evaluating the
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`pertinent art.
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`20.
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`I further understand that certain factors may support or rebut the
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`obviousness of a claim. I understand that such secondary considerations include,
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`among other things, commercial success of the patented invention, skepticism of
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`those having ordinary skill in the art at the time of invention, unexpected results of
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`the invention, any long-felt but unsolved need in the art that was satisfied by the
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`alleged invention, the failure of others to make the alleged invention, praise of the
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`alleged invention by those having ordinary skill in the art, and copying of the
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`alleged invention by others in the field. I understand that there must be a nexus—a
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`connection—between any such secondary considerations and the alleged invention.
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`I also understand that contemporaneous and independent invention by others is a
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`secondary consideration tending to show obviousness.
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`21.
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`I further understand that a claim is obvious if it unites old elements
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`with no change to their respective functions, or alters prior art by mere substitution
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`of one element for another known in the field and that combination yields
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`predictable results. While it may be helpful to identify a reason for this
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`combination, common sense should guide and no rigid requirement of finding a
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`teaching, suggestion or motivation to combine is required. When a product is
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`available, design incentives and other market forces can prompt variations of it,
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`either in the same field or different one. If a person of ordinary skill in the relevant
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`art can implement a predictable variation, obviousness likely bars its patentability.
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`For the same reason, if a technique has been used to improve one device and a
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`person of ordinary skill in the art would recognize that it would improve similar
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`devices in the same way, using the technique is obvious. I understand that a claim
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`may be obvious if common sense directs one to combine multiple prior art
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`references or add missing features to reproduce the alleged invention recited in the
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`claims.
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`IV. BACKGROUND OF THE FIELD OF THE INVENTION
`22. The ’461 Patent describes the claimed inventions as an improvement
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`over a prior-art system in which a human user assembles information (specifically,
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`information about configurable products) into a tree organization. After collecting
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`the information from a variety of sources (Ex. 1004, ’461 patent at 1:33–36, 1:53–
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`58), the user rearranges the information into a hierarchy—what the patent calls, “a
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`frame based knowledge tree.” (Id. at 1:33–37, 1:53–54.)
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`23. According to the ’461 Patent’s description of the prior art, the user
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`typically constructs the tree using a computer with a graphical user interface. (See
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`id. at 1:38–37.) But the user, not the computer, decides where each piece of
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`information is placed in the tree. (Id. at 1:38–52.)
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`24. According to the ’461 Patent, the alleged invention improves upon
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`this typical prior art system by having a computer automatically perform some of
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`the tasks previously performed by the user. In particular, the ’461 Patent explains
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`that the user should still indicate certain preferences about the organization of the
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`tree, but thereafter, the computer should automatically construct the tree consistent
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`with the user’s preferences. (Id. at 1:66–2:8.)
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`25. Despite the ’461 Patent’s characterization of the prior art, prior art
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`systems existed where the computer automated functions that would otherwise
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`have been performed by the human user. For example, Greef and Bader, which are
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`described in more detail below, offer partially or more fully automated systems.
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`V. OVERVIEW OF THE CHALLENGED CLAIMS
`26. The Challenged Claims involve taking information stored in a
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`database table and rearranging it into a “frame-based knowledge tree,” which is a
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`hierarchical structure, based on input received from user. The independent method
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`claim, Claim 6, requires the following:
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`A method of automatically constructing a frame-based knowledge
`tree, the method comprising:
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`identifying a plurality of attributes within a vendor database to be
`inducted into a frame-based knowledge tree by querying at least one
`vendor-supplied product knowledge database table for data regarding
`the attributes;
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`presenting pre-defined questions about the data to a user to identify a
`set of SQL queries to be answered to construct the frame-based
`knowledge tree;
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`automatically determining respective locations of the plurality of
`attributes within the frame-based knowledge tree based upon input
`answers received from a user regarding the data, wherein the input
`answers are provided in response to the pre-defined questions about
`the data provided to the user; and
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`inserting at least one of the attributes into the frame-based knowledge
`tree based on the determined respective locations, whereby the frame-
`based knowledge tree is constructed.
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`(Ex. 1004 at 12:13–31.)
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`27. The patent provides an example based on Table 1A. It contains eight
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`products defined by three different attributes, which are color, size, and shape:
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`(Id. at 8:38–60.) This tabular information is reorganized into a frame-based
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`knowledge tree:
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`(Id. at 10:7–50, Fig. 6.)
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`28. The construction of the tree requires a user’s input. Different
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`hierarchical arrangements could be formed from the information in Table 1A. For
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`example, although Figure 6 shows that color is the highest-level node (and shape is
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`the lowest-level node), the data could have been organized, for example, with
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`shape as the highest-level node. The user’s input determines where each attribute
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`should be located. (Id. at 5:38–7:21.)
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`29. Once the user’s instructions are known, the process creates SQL
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`queries that extract information from the table and place it in the correct location in
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`the tree. (Id. at 9:43–52.)
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`30. The other independent claim, Claim 1, claims a system with the same
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`functionality as Claim 6, but written in system form. Each has dependent claims.
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`31. The elements of the Challenged Claims are presented in Section
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`VIII.B.2 below.
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`VI. LEVEL OF ORDINARY SKILL
`32.
`I have been advised that there are multiple factors relevant to
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`determining the level of ordinary skill in the pertinent art, including the educational
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`level of active workers in the field at the time of the invention, the sophistication of
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`the technology, the type of problems encountered in the art, and the prior art
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`solutions to those problems.
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`33.
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`It is my opinion that a person of ordinary skill in the relevant art at the
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`time of invention (late 2003) is a person with a bachelor’s degree in Computer
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`Science with experience with relational database systems, frame-based systems,
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`and their interfaces.
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`VII. CLAIM CONSTRUCTION
`34.
`I understand that claim terms should be given their broadest
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`reasonable interpretation.
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`35.
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`I understand that Petitioner has proposed that, for the ’461 Patent’s
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`claims, “frame” means “a structured representation of an object or a class of
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`objects.” This is consistent with how the term is used on the patent:
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`Such GUI tools allow the user (typically, a knowledge engineer) to
`model the product knowledge in a tree like structure where each node
`of the tree is known as a frame. The attributes that describe and
`specialize the frame are represented using slots. The node at each
`level in a tree inherits properties from its parent node(s) and allows
`the user to override, extend or specialize these properties at the current
`level. The level in a tree at which certain attributes are placed depends
`on the generality of those attributes. For example, attributes that are
`common to a number of configurable items are placed closer to the
`top of the tree. Attributes that specialize a configurable item are
`placed at the lower levels of the tree.
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`(Ex. 1004, ’461 Patent at 1:37–52.) This is consistent with how the term is used in
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`the ’401 patent, which is incorporated by references into the ’461 patent. (Ex.
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`1006, ’401 Patent at 4:67–5:3 (“Frame Engine 104 represents knowledge in a
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`hierarchical tree-like structure. The nodes of the tree are generally called ‘frames’
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`(e.g., corresponding to product categories)”.) This is also consistent with how the
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`term would have been understood by a person of ordinary skill in the art at the time
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`of the claimed invention. (See Ex. 1007, Fikes at 904 col.2 (“a frame provides a
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`structured representation of an object or a class of objects”); Ex. 1008, Cawsey at
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`180 (“Frame: Record-like structure used to represent knowledge. A frame is used
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`to represent simple facts about an object or class as slots and slot values, and
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`inheritance used to make inferences.”).)
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`VIII. ANALYSIS OF THE PRIOR ART
`A. Overview of the Prior Art
`36.
`I understand that U.S. Patent No. 6,397,221 to Greef et al. (Ex. 1005,
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`“Greef”), U.S. Patent No. 5,467,471 to Bader (Ex. 1011, “Bader”), U.S. Patent
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`No. 6,108,670 to Weida et al. (Ex. 1009, “Weida”), U.S. Parent No. 5,953,726 to
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`Carter et al. (Ex. 1010, “Carter”), and U.S. Patent No. 6,442,566 to Altman et al.
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`(Ex. 1012, “Altman”) are prior art under 35 USC § 102(b) because they issued
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`more than one year prior to the filing date of the application to which the ’461
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`Patent claims priority (December 5, 2003).
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`1. Overview of Greef
`37. Greef discloses a prior art system and method concerning the
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`rearrangement of data from a database table to a frame-based hierarchy.
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`38. Greef—in particular, Greef’s second embodiment—discloses (among
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`other things) that it (1) accesses product data from a database table; (2) queries the
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`table to identify attributes; (3) identifies preferences for constructing a frame-based
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`tree of the attributes; and (4) based on those preferences, determines locations for
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`the attributes in the tree and inserts them accordingly. (See Ex. 1005, Greef at
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`28:43–33:31.)
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`39. Greef’s process begins by accessing a table of products for sale, each
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`with its own set of attributes:
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`(Id. at Fig. 17.)
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`40. Greef’s process converts the table into a hierarchy:
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`(Id. at Fig. 19 (cropped), 29:14–24.)
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`2. Overview of Bader
`41. Bader discloses “a system and method pertaining to hierarchical and
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`relational databases maintained by a computer.” (Ex. 1011, Bader at 1:8–9.)
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`Among other disclosures, Bader “teaches a system for… converting a database that
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`is maintained as relational to one that is hierarchical.” (Id. at 3:34–37; see also id.
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`at 11:44–12:40.) For example, it discloses converting the database table in Figure
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`12 into various hierarchies:
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`(Id. at Fig. 12.)
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`42. One such hierarchy is shown in Figure 14:
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`(Id. at Fig. 14a; see also id. at Fig. 14b, 12:10–40.)
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`3. Overview of Weida/Carter
`43. Weida incorporates Carter by reference. (Ex. 1009, Weida at 1:13–
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`18.) Carter discloses, among other things, a system and method for adding,
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`deleting, or modify the contents of a hierarchy of products. (Ex. 1010, Carter at
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`Abstract, 1:30–33.) Although Weida/Carter is “computer automated” (id. at 1:32),
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`its process “is an interactive one where some of the steps… are performed by the
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`computer, while the remaining steps are performed by the user in response to
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`interrogations by the computer.” (Id. at 6:42–45.) Carter’s hierarchy is maintained
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`by “a human agent using a Graphic User Interface (GUI).” (Id. at 2:30–42.)
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`44. An example of GUI screen that interrogates the user is shown below:
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`(Id. at Fig. 27, 6:59–65; see also id. at 6:32–58.)
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`4. Overview of Altman
`45. Altman provides “a frame-based knowledge representation system
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`built on a commercial relational database management system.” (Ex. 1012, Altman
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`at 3:46–49; see also id. at 4:35–50.) The frame-based system is a hierarchical
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`knowledge base, and the database includes multiple tables. (Id. at 6:21–38, 7:41–
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`54.) The relational database “is hidden from the user.” (Id. at 4:35–37.) To retrieve
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`information, the user queries the knowledge base; then the system translates the
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`query into a format that can query the relational database, applies the query to the
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`database, and transmits the output to the user. (Id. at 4:51–63.) The format for
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`querying the relational databases is “most preferably SQL.” (Id. at 4:61–63.)
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`B.
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`The Challenged Claims are Obvious
`1.
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`A person of ordinary skill would have had a reason to
`modify Greef
`46. Greef’s second embodiment discloses (among other things) that it (1)
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`accesses product data from a database table; (2) queries the table to identify
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`attributes; (3) identifies preferences for constructing a frame-based tree of the
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`attributes; and (4) based on those preferences, determines locations for the
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`attributes in the tree and inserts them accordingly. (See Ex. 1005, Greef at 28:43–
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`33:31.)
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`47. As explained below, a person of ordinary skill in the art at the time of
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`the claimed inventions would have had a reason to design a system based on Greef
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`that would have contained each element of the Challenged Claims.
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`a. Modifying Greef to ask the users for their preferences
`48. Early in its process of building a hierarchy from the attributes
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`contained in a database table, Greef identifies preferences for the structure of the
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`hierarchy. In particular, Greef looks for category-subcategory relationships for
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`organizing the hierarchy by looking for certain strings in the table’s column
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`headers; in particular columns named “Class” and “Type.” (Id. at 29:8–14.) For
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`example, Greef refers to all columns in the table below (Fig. 17) as attributes (id. at
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`28:58–67), and Greef determines preferences about the hierarchical arrangement of
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`these attributes by looking at the column headers (attribute names) in the table
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`below.
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`(Id. at Fig. 17.)
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`49. The system concludes that “Camera” should exist in a frame closest to
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`the root (sometimes referred to as the top) of the tree—it is a value of what Greef
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`calls a “category” attribute (e.g., id. at 29:17)—because its associated attribute is
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`titled, “Class.” (Id. at 29:8–14, 29:59–30:3.) Likewise, the system knows that
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`“Point & Shoot,” “SLR,” and “Digital,” should appear in frames subordinate to
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`“Camera”—they are values of what Greef calls a “subcategory” attribute (e.g.,
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`id.)—because their associated attribute is titled, “Type.” (Id. at 29:8–14, 29:59–
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`30:3.) Thus, because the table uses “Class” and “Type” as headers, the computer
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`can identify preferences for the structure of the hierarchy without explicitly
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`seeking the user’s input:
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`Upon closer consider of table 400, it will be appreciated that since
`product attributes that identify category and subcategory such as
`Class and Type are included in the table data, the tabular data contains
`information from which a frame-based hierarchical structure to
`accommodate the product records might be generated.
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`(Id. at 29:8–14.)
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`50. Additionally, the system identifies “Model Name” as “suitable
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`identifying attribute… [for] identifying the respective products.” (Id. at 30:44–47.)
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`As such, system concludes that frames for the values of “Model Name” should
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`appear subordinate to those of “Type.” (Id. at Fig. 18.)
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`51. Greef determines that the hierarchy should have the following general
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`structure:
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`(Id. at Fig. 18 (cropped).)
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`52. Thereafter, based on these preferences, Greef determines locations for
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`(and inserts) the remaining attributes “without intervention of the user”:
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`(Id. at Fig. 19 (cropped), 29:14–24.)
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`53.
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`If the table did not label columns as “Class” and “Type”—as in the
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`example above—the system would require an alternative way to identify which
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`attribute should be treated as the category attribute and which should be treated as
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`the subcategory attribute. Greef recognizes this and suggests, as one alternative,
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`the system could reference a “look up” to figure out which attributes correspond to
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`category and subcategory:
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` As will also be appreciated, if table 400 includes category and
`subcategory information under attribute names other than Class and
`Type,
`the method would
`identify
`the category subcategory
`information by comparison to a term reference look up.
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`(Id. at 30:33–42.)
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`54. A person of ordinary skill in the art would have recognized that
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`Greef’s system should be designed to present the user with a list of the attributes
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`and ask the user to identify which correspond to category and subcategory. First,
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`the person would have recognized the impracticality of depending exclusively on
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`an external lookup functionality to obtain full category and subcategory
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`information when “class” and “type” are missing. Prompting the user to make
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`selections solves that problem. Second, the person of ordinary skill in the art would
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`have known that asking the user to identify the category and subcategory attributes
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`in a modified Greef system would have provided enhanced control by the user,
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`thereby supporting potential customization of the hierarchy to suite the intended
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`use.
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`55. The disclosure of Bader make clear that a person of ordinary skill
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`would have recognized that Greef’s system should be designed to present the user
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`with a list of the attributes and ask the user to identify those that correspond to
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`attributes that indicate category and subcategory relationships in the hierarchy.
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`Bader discloses an example of building a hierarchy by asking the user to identify
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`which attributes should be “the elements on which the hierarchy to be created will
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`be based.” (Ex. 1011, Bader at 11:53–60.)
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`56. As background information, hierarchies contain nodes at various
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`levels below the root of the hierarchy. In the Greef example above, “Class”—what
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`Greef calls the category attribute—is at the first level (immediately below the root)
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`and “Type”—what Greef calls the subcategory attribute—is at the second level.
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`All hierarchies have this multi-level structure, even hierarchies based on an
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`organizing principle other than category and subcategory. Bader presents an
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`example of such a hierarchy.
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`57.
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`In particular, Bader discloses “a system and method pertaining to
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`hierarchical and relational databases maintained by a computer.” (Id. at 1:8–9.)
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`Among other disclosures, Bader “teaches a system for… converting a database that
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`is maintained as relational to one that is hierarchical.” (Id. at 3:34–37.) For
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`example, it discloses converting the database table in Figure 12 into various
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`hierarchies:
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`(Id. at Fig. 12.)
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`58. The construction of these hierarchies occurs in three principal steps.
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`First, the user selects which subset of attributes from the table (i.e., which
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`attributes among “Department,” “Company,” “Location,” “First Name,” “Last
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`Name,” and “Children’s Names”) will be used to form the general structure of the
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`hierarchy.
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`The preferred system and method for converting from a relational
`database to a hierarchical database is as follows. First, some of the
`attributes or keywords of the relational database (i.e., the column
`headers in FIG. 12) are selected by a user to be the elements on
`which the hierarchy to be created will be based. In the example…
`there are three keywords chosen on which the hierarchy will be based:
`“Department”, “Company”, and “Last Name”.
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`(Id. at 11:53–60.) Second, based upon the number of unique values for each of the
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`selected attributes, the user selects the ordering of the attributes within the
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`hierarchy (Bader also refers to attributes as “keywords”)—i.e., which attribute is
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`closest to the root (which Bader refers to as the “Level” of the attribute):
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`[T]he keyword “Company” is preferably selected as the keyword for
`records at Level 1 of the hierarchy, the keyword “Department” is
`preferably selected as the keyword for records at Level 2 of the
`hierarchy, and the keyword “Last Name” is preferably selected as the
`keyword for records at Level 3 of the hierarchy.
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`(Id. at 11:61–12:9.) Third, based on the user’s preferences the system places all
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`remaining attributes within the hierarchy, such as that of Figure 14 (the hierarchy
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`is spread over two sub-figures, and only Figure 14a is reproduced be
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