Case No.: IPR2016-01013
`Attorney Docket No.: FPGP0129IPR2
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`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`
`______________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`______________
`
`FORD MOTOR COMPANY
`Petitioner,
`
`v.
`
`VERSATA SOFTWARE, INC.
`Patent Owner.
`
`______________
`
`
`
`U.S. Patent No. 7,882,057
`
`IPR Case No.: 2016-01013
`
`
`
`______________
`
`
`
`DECLARATION OF DR. PHILIP GREENSPUN IN SUPPORT
`OF INTER PARTES REVIEW UNDER 35 U.S.C. § 311 ET SEQ.
`AND 37 C.F.R. § 42.100 ET SEQ. (CLAIMS 17, 30, AND 44-46 OF
`U.S. PATENT NO. 7,882,057)
`
`
`
`
`
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`TABLE OF CONTENTS
`
`
`
`List of Exhibits ........................................................................................................... 3
`
`I.
`
`II.
`
`Qualifications and Professional Experience .................................................... 7
`
`Relevant Legal Standards ..............................................................................13
`
`III. Level of Ordinary Skill in the Art .................................................................15
`
`IV. The ’057 Patent ..............................................................................................16
`
`V.
`
`The ‘057 Patent Prosecution History .............................................................26
`
`VI. Challenged Claims of the ’057 Patent Viewed in their Broadest
`Reasonable Interpretation ..............................................................................27
`
`VII. Scope and Content of the Prior Art (Summary) ............................................27
`
`VIII. Prior Art: Loomans, U.S. Patent 7,873,503 ...................................................42
`
`IX. Prior Art: “A Customization Approach for Structure Products in
`Electronic Shops” (“Stahl”) ...........................................................................44
`
`X. Grounds for Challenge ...................................................................................47
`
`A. Ground 1 – Claims 17, 30, 44 And 45-46 Obvious Based On
`Loomans In View Of Stahl And The General Knowledge Of A
`Person Having Ordinary Skill In The Art ...........................................47
`
`1.
`
`Analysis of Claims 17, 30, and 44 ............................................47
`
`a.
`
`b.
`
`c.
`
`d.
`
`Claim 17 ..........................................................................48
`
`Obvious to Combine Loomans with Stahl......................83
`
`Claim 30 ..........................................................................87
`
`Claim 44 ........................................................................102
`
`2.
`
`Analysis of Claims 45 and 46 .................................................108
`
`a.
`
`b.
`
`Claim 45 ........................................................................108
`
`Claim 46 ........................................................................150
`
`XI. Conclusion ...................................................................................................153
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`
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`List of Exhibits
`
`Case No.: IPR2016-01013
`Attorney Docket No.: FPGP0129IPR2
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`
`Description
`
`1102
`
`1103
`
`1104
`
`1105
`
`Exhibit
`No.
`1101 U.S. Patent No. 7,882,057
`Expert Declaration of Dr. Philip
`Greenspun
`Curriculum Vitae of Dr. Philip
`Greenspun
`U.S. Patent No. 7,882,057 File
`History
`U.S. Patent No. 7,873,503 to
`Loomans et al.
`A. Stahl, R. Bergmann, S. Schmitt,
`A Customization Approach for
`Structured Products in Electronic
`Shops, Electronic Commerce: The
`End of the Beginning, 13th
`International Bled Electronic
`Commerce Conference (June 19-21,
`2000)
`Alexander Kott, Gerald Agin, David
`Fawcett, Configuration Tree Solver:
`A Technology for Automated
`Design and Configuration, ASME
`Journal of Mechanical Design
`114(1): 187-195 (1992)
`L. Anselma, D. Magro, and P.
`Torasso, Automatically
`Decomposing Configuration
`Problems, AI*IA 2003: Advances in
`Artificial Intelligence, Lecture
`Notes in Computer Science,
`Volume 2829, pp. 39-52 (2003)
`
`1106
`
`1107
`
`1108
`
`Date
`
`Identifier
`
`Feb. 1, 2011
`
`’057 Patent
`
`n/a
`
`n/a
`
`n/a
`
`Greenspun Decl.
`
`Greenspun CV
`
`’057 Patent File
`History
`
`Jan. 18, 2011 Loomans
`
`Jun. 2000
`
`Stahl
`
`1992
`
`Kott
`
`2003
`
`Anselma
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`Exhibit
`No.
`
`Description
`
`Date
`
`Identifier
`
`Case No.: IPR2016-01013
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`
`D. Magro and P. Torasso,
`Decomposing and Distributing
`Configuration Problems, Artificial
`Intelligence: Methodology, Systems,
`and Applications, Lecture Notes in
`Computer Science, Volume 2443,
`pp. 81-90 (2002)
`Judith Bachant, John McDermott,
`R1 Revisited: Four Years in the
`Trenches, AI Magazine Volume 5,
`Number 3 (1984)
`John McDermott, R1: A Rule-Based
`Configurer of Computer Systems,
`Artificial Intelligence (1982)
`Bryan M. Kramer, Knowledge-
`Based Configuration of Computer
`Systems Using Hierarchial Partial
`Choice, IEEE (1991)
`Bei Yu and Hans Jorgen Skovgaard,
`A Configuration Tool to Increase
`Product Competitiveness, IEEE
`Intelligent Systems, 34-41
`(July/August 1998)
`U.S. Patent Application Publication
`No. 2003/0187950 to Rising
`Martin R. Wagner, Understanding
`the ICAD System, ICAD, Inc., 1990
`Oracle Configurator Developer,
`User’s Guide, Release 11i for
`Windows 95/98/2000 and Windows
`NT 4.0
`Stefan Schulz, CBR-Works A State-
`of-the-Art Shell for Case-Based
`Application Building, TECINNO
`GmbH, 1999
`
`1109
`
`1110
`
`1111
`
`1112
`
`1113
`
`1114
`
`1115
`
`1116
`
`1117
`
`2002
`
`Magro
`
`1984
`
`Bachant
`
`1982
`
`McDermott
`
`1991
`
`Kramer
`
`1998
`
`Yu
`
`Oct. 2, 2003
`
`Rising
`
`1990
`
`ICAD
`
`April 2002
`
`Oracle
`
`1999
`
`CBR
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`Description
`
`Date
`
`Identifier
`
`Richard M. Stallman and Gerald Jay
`Sussman, Forward Reasoning and
`Dependency-Directed Backtracking
`In a System for Computer-Aided
`Circuit Analysis, MIT Artificial
`Intelligence Laboratory, Memo No.
`380, Sept. 1976
`
`
`
`Sept. 1976
`
`Stallman
`
`Exhibit
`No.
`
`1118
`
`
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`I, Philip Greenspun, hereby declare as follows:
`
`1.
`
`I am making this declaration at the request of Ford Motor Company in
`
`the matter of Inter Partes Review of U.S. Patent No. 7,882,057 (“the ’057 Patent”)
`
`to Little.
`
`2.
`
`I am a salaried non-owner employee of Fifth Chance Media LLC,
`
`which is being compensated for my work in this matter at a rate of $475/hour. My
`
`compensation in no way depends on the outcome of this proceeding.
`
`3.
`
`In preparation of this declaration, I have studied the exhibits as listed
`
`in the Exhibit List shown above. Each of these exhibits is a true and accurate
`
`copy.
`
`4.
`
`
`
`In forming the opinions expressed below, I have considered:
`
`(a) The documents listed above as well as additional patents and
`
`documents referenced herein;
`
`
`
`(b) The relevant legal standards, including the standard for
`
`obviousness provided in KSR International Co. v. Teleflex, Inc., 550 U.S.
`
`398 (2007), and any additional legal standards set forth in the body of this
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`declaration; and
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`
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`(c) My knowledge and experience based upon my work and study
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`in this area as described below.
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`
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`I.
`
`Qualifications and Professional Experience
`
`5.
`
`I have provided my full background in the curriculum vitae that is
`
`attached as Exhibit 1103.
`
`6.
`
`I earned a Ph.D. in Electrical Engineering and Computer Science from
`
`Massachusetts Institute of Technology in 1999. I also obtained a Bachelor of
`
`Science Degree in Mathematics from Massachusetts Institute of Technology in
`
`1982 and a Master of Science Degree in Electrical Engineering and Computer
`
`Science from Massachusetts Institute of Technology in 1993.
`
`7. My Ph.D. dissertation concerned the engineering of large online
`
`Internet communities with a Web browser front-end and a relational database
`
`management system (RDBMS) containing site content and user data.
`
`8.
`
`I have authored five computer science textbooks in total, including
`
`Database Backed Websites (Macmillan), Software Engineering for Internet
`
`Applications, and an SQL language tutorial.
`
`9.
`
`I have served as an independent member of various advisory and
`
`corporate boards, mostly for technology companies. For example, I joined the
`
`corporate board of an MIT materials science spin-off in late 2005 during a
`
`$550,000 seed capital phase. I stepped down when the company secured $10
`
`million in venture capital in mid-2007.
`
`10.
`
`I began working full-time as a computer programmer in 1978,
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`developing a database management system for the Pioneer Venus Orbiter at the
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`National Aeronautics and Space Administration’s Goddard Space Flight Center.
`
`11.
`
`In the early 1980s, I developed computer-aided design software for
`
`electronic systems, specifically to assist digital hardware engineers designing
`
`processors at Hewlett-Packard and Symbolics. The integrated circuit design
`
`software that I built at Symbolics included the capability to automatically
`
`configure various kinds of circuits.
`
`12.
`
`I co-developed a computer program for computer-aided design of
`
`mechanical systems in the mid-1980s. This was called the ICAD System. The
`
`ICAD System enabled engineers to decompose a mechanical design into a
`
`hierarchy of subassemblies and establish configuration rules at each level of
`
`subassembly. The end-result was a system in which it was possible to go from
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`customer specifications to a finished design without human intervention. The first
`
`applications for the ICAD System involved large structures built from steel, such
`
`as house-sized air-cooled heat-exchangers used in commercial buildings and
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`industrial plants.
`
`13.
`
`ICAD went public as “Concentra” in the 1990s and was acquired by
`
`Oracle Corporation in 2002. The product’s mechanical design capabilities were
`
`deemphasized and its configuration capabilities were improved for use as a
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`general-purpose sales configuration system. The product survives today as Oracle
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`Configurator, part of the Oracle Applications suite of business software.
`
`“Understanding the ICAD System” is a 1990 marketing brochure that contains an
`
`explanation of some of the basic capabilities. Excerpts from this brochure are
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`reproduced below:
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`(Ex. 1115 [ICAD] at 4-29 – 4-31, pages 80-82.)
`
`14.
`
`In the second half of the 1980s, I was the principal developer of a
`
`computer program for computer-aided design and control of civil engineering
`
`projects, specifically earthmoving. This work was the foundation of my master’s
`
`thesis at MIT and also of U.S. Patent Nos. 5,150,310 and 5,964,298, on which I am
`
`a named inventor.
`
`15.
`
`I developed my first program using a relational database management
`
`system in 1994. It was a Web interface to the Children’s Hospital Oracle RDBMS,
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`Version 6. This application enabled doctors at the hospital to view patient clinical
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`data using any computer equipped with a Web browser.
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`16.
`
`In 1995, I led an effort by Hearst Corporation to set up an
`
`infrastructure for Internet applications across all of their newspaper, magazine,
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`radio, and television properties. This infrastructure included software for
`
`managing users, shopping carts, electronic commerce, advertising, and user
`
`tracking. One capability of the system was using private data, regarding a user’s
`
`history, to determine the (publicly available) advertisements to be shown on pages
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`viewed by that user, including pages that included order summaries and other
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`private data.
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`17. Between 1995 and 1997, I significantly expanded the photo.net online
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`community that I had started in 1993 to help people teach each other to become
`
`better photographers. I began distributing the source code behind photo.net to
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`other programmers as a free open-source toolkit, called “ArsDigita Community
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`System.” One version of this system was an add-on to AOLserver, a Web server
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`with an API.
`
`18.
`
`In May 1997, Macmillan published my first textbook on Internet
`
`Application development, Database Backed Websites. A September 1998 update
`
`to this book was published as Philip and Alex’s Guide to Web Publishing
`
`(hardcopy version published in April 1999).
`
`19.
`
`In 1997, I started a company, ArsDigita, to provide support and
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`service for the ArsDigita Community System. Between 1997 and the middle of
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`2000, I managed the growth of ArsDigita to 80 people, almost all programmers,
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`and $20 million per year in annual revenue. This involved supervising dozens of
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`software development projects, nearly all of which were Internet Applications with
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`a Web front-end and an Oracle RDBMS back-end.
`
`20.
`
`In 1999, I supervised the packaging up of much of our ecommerce-
`
`related code into the “ecommerce” module of the ArsDigita Community System.
`
`As the founder, CEO, and chief technical employee of the company, I personally
`
`developed functional specifications, SQL data models (Structured Query
`
`Language, or “SQL”, the standard programming language for relational database
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`management systems), and Web page flows that determined the user experience.
`
`21. Between 2000 and the present, I have managed software development
`
`projects for philip.greenspun.com and photo.net. Both online services are
`
`implemented as relational database management applications. For photo.net, in
`
`particular, I evaluated various Web-based comparative shopping tools that would
`
`allow readers to find the best delivered prices, given a zip code, for camera
`
`equipment. In addition, I am currently developing a Facebook application that
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`allows parents to create electronic baby books.
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`22. Separately from this commercial and public work, I have been
`
`involved as a part-time teacher within the MIT Department of Electrical
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`Engineering and Computer Science, educating students in how to develop Internet
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`Applications with an RDBMS back-end. In the spring of 1999, I taught 6.916,
`
`Software Engineering of Innovative Web Services, with Professors Hal Abelson
`
`and Michael Dertouzos. In the spring of 2002, this course was adopted into the
`
`standard MIT curriculum as 6.171. I wrote 15 chapters of a new textbook for this
`
`class, Software Engineering for Internet Applications. This book was published on
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`the Web at http://philip.greenspun.com/seia/ starting in 2002 and 2003 and also in
`
`hardcopy from MIT Press in 2006. I am the sole author of a supplementary
`
`textbook for the class, SQL for Web Nerds, a succinct SQL programming language
`
`tutorial available only on the Web at http://philip.greenspun.com/sql/. I use this
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`book when I teach an intensive course in database programming at MIT, as I did
`
`most recently in January 2015.
`
`23. Based at least on my education and experience, I consider myself to
`
`be an expert in software engineering, including the development of configuration
`
`systems such as the system described in the ’057 Patent.
`
`II. Relevant Legal Standards
`
`24.
`
`I have been asked to provide opinions regarding the validity of claims
`
`of the ’057 Patent in light of the prior art.
`
`25.
`
`It is my understanding that a claimed invention is unpatentable under
`
`35 USC § 102 if a prior art reference teaches every element of the claim. This is
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`sometimes referred to as “anticipation.”
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`26.
`
`It is my understanding that a claimed invention is unpatentable under
`
`35 U.S.C. § 103 if the differences between the invention and the prior art are such
`
`that the subject matter as a whole would have been obvious at the time the alleged
`
`invention was made to a person having ordinary skill in the art to which the subject
`
`matter pertains. This is sometimes described as “obviousness.” I understand that
`
`an obviousness analysis takes into account the level of ordinary skill in the art, the
`
`scope and content of the prior art, and the differences between the prior art and the
`
`claimed subject matter.
`
`27.
`
`It is my understanding that the Supreme Court, in KSR Int’l Co. v.
`
`Teleflex Inc., 550 U.S. 398 (2007) and other cases, has recognized several
`
`rationales for combining references or modifying a reference to show obviousness
`
`of the claimed subject matter. Some of these rationales include the following:
`
`combining prior art elements according to known methods to yield predictable
`
`results; simple substitution of one known element for another to obtain predictable
`
`results; a predictable use of prior art elements according to their established
`
`functions; applying a known technique to a known device to yield predictable
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`results; choosing from a finite number of identified, predictable solutions, with a
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`reasonable expectation of success; and some teaching, suggestion, or motivation in
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`the prior art that would have led one of ordinary skill to modify the prior art
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`reference or to combine prior art reference teachings to arrive at the claimed
`
`invention.
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`III. Level of Ordinary Skill in the Art
`
`28.
`
`I have reviewed the ’057 Patent, as well as the pertinent prior art
`
`documents discussed below. Based on this review and my knowledge of the
`
`configuration system field, including my work on ICAD system in the 1980s, it is
`
`my opinion that a person having ordinary skill in the art would have the following:
`
`(1) a bachelor’s degree in computer science, electrical engineering, computer
`
`engineering, or similar technical field, or (2) equivalent experience in the design or
`
`implementation of configuration systems. The relevant field of art is product
`
`configuration software.
`
`29.
`
`I understand that this determination is made at the time of the
`
`invention, which I understand that the patentee states as being the October 4, 2004
`
`filing of U.S. Application No. 10/957,919, which ultimately issued as the ’057
`
`Patent.
`
`30. As I also discussed
`
`in my “Qualifications and Professional
`
`Experience” section above, I am familiar with the level of knowledge and the
`
`abilities of a person having ordinary skill in the art at the time of the claimed
`
`invention based on my education and work experience.
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`IV. The ’057 Patent
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`31. The ’057 Patent discloses a configuration system and method for
`
`“processing complex configuration problems using configuration sub-models.”
`
`(Ex. 1101 [‘057 Patent] at 1:8-10.)
`
`32.
`
`In the Background of the Invention, the ‘057 Patent discloses a
`
`conventional product configuration process known in the prior art:
`
`In one embodiment of a conventional
`
`inference procedure,
`
`configuration query 102 is formulated based on user configuration
`
`input, a configuration engine performs the configuration query 102
`
`using a configuration model 104, and the configuration engine
`
`provides an answer 106 to the configuration query 102 based on the
`
`configuration query 102 and the contents of the configuration model
`
`104. The answer 106 represents a particular response to the
`
`configuration query 102.
`
`(Ex. 1101 [‘057 Patent] at 1:16-25.)
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`(Ex. 1101 [‘057 Patent] at Figure 1.)
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`33. The ‘057 Patent further discloses the complex relationships and
`
`
`
`queries that make-up a configuration model of a product:
`
`A configuration model 104 uses, for example, data, rules, and/or
`
`constraints
`
`(collectively referred
`
`to as "data")
`
`to define
`
`compatibility relationships between parts
`
`(also commonly
`
`referred to as "features") contained in a specific type of product.
`
`A part represents a single component or attribute from a larger, more
`
`complex system. Parts may be combined in different ways in
`
`accordance with rules and/or constraints to define different instances
`
`of the more complex system. For example, "V6 engine" or the exterior
`
`color "red" can be parts on a vehicle, and a specific hard disk drive
`
`can be a part on a computer. A part group, also called a group,
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`represents a collection of related parts. For example, an "Engines"
`
`group might contain the parts "V6 engine" and "4 cylinder engine". A
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`product configuration is a set of parts that define a product. For
`
`example, a vehicle configuration containing the parts "V6 engine" and
`
`"red" represents a physical vehicle that has a red exterior and a V6
`
`engine. A product can be a physical product such as a vehicle,
`
`computer, or any other product that consists of a number of
`
`configurable features such as an insurance product. Additionally, a
`
`product can also represent a service. A configuration query (also
`
`referred to as a "query") is essentially a question that is asked
`
`about the parts and relationships in a configuration model. The
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`answer returned from a configuration query will depend on the
`
`data in the configuration model, the approach used for answering
`
`the question, and the specifics of the question itself. For example,
`
`one possible configuration query, translated to an English sentence, is
`
`the following: For the given configuration model, are the parts "red"
`
`and "V6 engine" compatible with each other.
`
`(Ex. 1101 [‘057 Patent] at 1:26-54, emphasis added.)
`
`34. The ‘057 Patent next acknowledges that the achievable complexity of
`
`configuration models has been limited because of computer processing limitations:
`
`Solving configuration problems using computer assisted
`
`technology often requires a significant amount of data processing
`
`capabilities. Consequently,
`
`configuration
`
`technologies
`
`have
`
`attempted to exploit increased data processing capabilities, memory
`
`capacities, and network data transfer throughput rates by increasing
`
`the capabilities of the configuration engines and/or enhancing the
`
`complexity of configuration models and configuration queries. The
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`complexity of a configuration model can be defined in any number of
`
`ways, such as by the diversity of parts, part groups, rules, and
`
`constraints supported by the configuration model, by the number of
`
`parts, rules, and constraints, and by the complexity of part and part
`
`group relationships defined by configuration rules and constraints. In
`
`any event, the practical complexity achievable for configuration
`
`models has been limited by the ability of computer systems to
`
`process data within a given period of time, T, and/or limited by
`
`other processing constraints, such as a lack of memory. The time
`
`period, T, represents an amount of time considered reasonable to
`
`perform a configuration task. Time T can vary depending upon the
`
`application and expectation of configuration system users.
`
`(Ex. 1101 [‘057 Patent] at 2:37-57, emphasis added.)
`
`35. Figure 3 of the ‘057 Patent illustrates limitations on configuration
`
`models/configuration queries because of limited data processing capabilities
`
`known in the prior art. As complexity goes up, shown from left-to-right on the x-
`
`axis of the graphic in Figure 3 (and specifically depicted in line 302), the
`
`maximum data processing capability is reached (depicted by dashed line 304).
`
`Thus, the graphic in Figure 3 indicates that there is sufficient data processing
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`capability to process the configuration model represented as “A” (below dashed
`
`line 304), but insufficient data processing capability to process the configuration
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`model represented as “B” (above dashed line 304).
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`(Ex. 1101 [‘057 Patent] at Fig. 3.)
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`36. To overcome the limitations on data processing capabilities known in
`
`
`
`the prior art, the ‘057 Patent discloses:
`
`A configuration model dividing and configuration sub-model
`
`inference processing system and procedure addresses the issue of
`
`configuration model and query complexity by breaking a
`
`configuration problem down into a set of smaller problems,
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`solving them individually and recombining the results into a
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`single result that is equivalent to a conventional inference
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`procedure. In one embodiment, a configuration model is divided into
`
`configuration sub-models that can respectively be processed using
`
`existing data processing
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`resources. The sub-model
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`inference
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`procedure does not change the exponential nature of configuration
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`model and query complexity but instead generates configuration sub-
`
`models on the side of the achievable performance curve. Accordingly,
`
`a sub-model inference procedure provides a way to scale queries to
`
`larger and more complicated configuration models. Embodiments of
`
`the configuration model dividing and configuration sub-model
`
`processing system and inference procedure allows processing by a
`
`data processing system of configuration models and queries whose
`
`collective complexity exceeds
`
`the complexity of otherwise
`
`unprocessable conventional, consolidated configuration models and
`
`queries.
`
`(Ex. 1101 [‘057 Patent] at 4:18-40, emphasis added.)
`
`37. The ‘057 Patent discusses an embodiment where a consolidated
`
`configuration model is divided into several sub-models.
`
`FIG. 4 depicts the configuration model dividing and configuration
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`sub-model inference processing system 400 (referred to herein as
`
`"sub-model processing system 400") that performs configuration
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`model dividing and configuration sub-model inference procedure 402
`
`(referred to herein as "sub-model inference procedure 402"). The sub-
`
`model inference procedure 402 includes operations 404, 406, 408, and
`
`410. The sub-model processing system 400 can include software code
`
`that is executable by a processor of a computer system, such as a
`
`server computer system. In a network environment, the sub-model
`
`processing system 400 can be accessed by and communicates with
`
`any number client systems 401(1) through 401(n).
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`Operation 404 receives, as an input, a conventional, consolidated
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`configuration model 412 and divides the consolidated configuration
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`model 412 into a set of configuration sub-models CM1 through CMn,
`
`where n is an integer representing the number of configuration sub-
`
`models. The configuration sub-models are an input to this process. In
`
`one embodiment, the configuration sub-models meet the following
`
`criteria: a. Each configuration sub-model should represent a portion of
`
`the source configuration model 412; b. The data collectively contained
`
`in the configuration sub-models should be sufficient to provide an
`
`answer for each of the sub-queries Q1 through Qn or query being
`
`processed; and c. The configuration sub-models should be divided in
`
`such a way that the results of the sub-queries or query can be
`
`recombined to provide an answer to the input configuration query
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`414.
`
`(Ex. 1101 [‘057 Patent] at 4:40-5:4.)
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`(Ex. 1101 [‘057 Patent] at Fig. 4.)
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`
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`38. Figure 6 of the ‘057 Patent illustrates an example of a consolidated
`
`configuration model (602), which has been divided into configuration sub-models
`
`CM1, CM2 and CM3.
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`(Ex. 1101 [‘057 Patent] at Fig. 6.)
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`
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`39. Figure 5 of the ‘057 Patent illustrates the data processing capability of
`
`a computer system when processing a consolidated configuration model (412)
`
`compared to the data processing capability of a computer system when processing
`
`sub-models CM1, CM2 and CMn are divided out of the consolidated configuration
`
`model (412). “In general, the consolidated configuration model 412 is divided
`
`sufficiently so that the complexity of each configuration sub-model CM1, CM2,
`
`through CMn is low enough to allow processing using available data processing
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`capabilities while still representing the relationships included in the consolidated
`
`configuration model 412, which, in this embodiment, would otherwise not be cable
`
`(sic) of being processed by the computer system.” (Ex. 1101 [‘057 Patent] at 5:11-
`
`18.)
`
`(Ex. 1101 [‘057 Patent] at Fig. 5.)
`
`
`
`40. As I discuss in the “Scope and Content of the Prior Art” section and
`
`the Ground for Challenge below, it is my opinion that this methodology for
`
`processing configuration models was well-known and practiced in the prior art
`
`before 2004. It is my opinion that by 2004 a person of ordinary skill would have
`
`considered this to be an obvious method for processing data from configuration
`
`models.
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`V. The ‘057 Patent Prosecution History
`
`41.
`
`I have reviewed the prosecution history of the ‘057 Patent. In the
`
`Reasons for Allowance, the only item that the Examiner’s identified as missing
`
`from the prior art references was the following:
`
`
`(Ex. 1104 [‘057 Patent File History] at 428-429, Notice of Allowability p. 2-3.)
`
`42. The prior art considered most directly during examination was Rising,
`
`Patent Application Publication 2003/0187950.
`
` (U.S. Patent Application
`
`Publication No. 2003/0187950 to Rising; attached as Exhibit 1114.) This is not a
`
`configuration or design tool, but a tool for finding digital content by querying into
`
`a database of MPEG-7 descriptions. Following a request for continuing
`
`examination, the Examiner rejected the claims based on Henson, U.S. Patent
`
`6,167,383, a Dell Computer system that assisted customers with ordering PCs. (Ex.
`
`1104 at 174-195.) The Applicant responded that Henson failed to teach the division
`
`of configuration rules for a PC, and therefore the processing of those rules in
`
`response to queries, into sub-models. (Ex. 1104 at 227-229.)
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`VI. Challenged Claims of the ’057 Patent Viewed in their Broadest
`Reasonable Interpretation
`
`43.
`
`I understand that in an inter partes review at the Patent Office, claims
`
`are to be given their broadest reasonable interpretation in light of the specification
`
`as would be read by a person of ordinary skill in the relevant art.
`
`44.
`
`In applying the claims at issue to the prior art, I have given all of the
`
`claim terms their broadest reasonable interpretation in light of the specification, as
`
`would be commonly understood by those of ordinary skill in the art at the time the
`
`patent was filed.
`
`VII. Scope and Content of the Prior Art (Summary)
`
`45. The ‘057 Patent acknowledges that prior art systems would perform
`
`configuration queries.
`
`Computer assisted product configuration continues to offer substantial
`
`benefits to a wide range of users and industries. FIG. 1 depicts a
`
`conventional product configuration process 100 performed by a
`
`configuration engine 101. The configuration process 100 represents
`
`one embodiment of an inference procedure. In one embodiment of a
`
`conventional
`
`inference procedure, configuration query 102
`
`is
`
`formulated based on user configuration input, a configuration engine
`
`performs the configuration query 102 using a configuration model
`
`104, and the configura