UNITED STATES PATENT AND TRADEMARK OFFICE
`
`______________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`______________
`
`AMERICAN EXPRESS COMPANY, AMERICAN EXPRESS TRAVEL
`RELATED SERVICES COMPANY, INC., EXPEDIA, INC., HOTELS.COM LP,
`HOTELS.COM GP, LLC, HOTWIRE, INC., ORBITZ WORLDWIDE, INC.,
`PRICELINE.COM, INC., TRAVELOCITY.COM LP, and YAHOO! INC.
`
`Petitioner,
`
`
`v.
`
`
`METASEARCH SYSTEMS, LLC,
`Patent Owner
`
`______________
`
`Case CBM2014-00001
`Patent 8,326,924
`
`______________
`
`SUPPLEMENTAL DECLARATION OF GARY LIAO IN SUPPORT OF
`PETITION FOR POST-GRANT REVIEW OF A COVERED
`BUSINESS METHOD UNDER 35 U.S.C. § 321 AND AIA, § 18
`
`
`
`
`
`
`
`
`
`
`______________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`______________
`
`AMERICAN EXPRESS COMPANY, AMERICAN EXPRESS TRAVEL
`RELATED SERVICES COMPANY, INC., EXPEDIA, INC., HOTELS.COM LP,
`HOTELS.COM GP, LLC, HOTWIRE, INC., ORBITZ WORLDWIDE, INC.,
`PRICELINE.COM, INC., TRAVELOCITY.COM LP, and YAHOO! INC.
`
`Petitioner,
`
`
`v.
`
`
`METASEARCH SYSTEMS, LLC,
`Patent Owner
`
`______________
`
`Case CBM2014-00001
`Patent 8,326,924
`
`______________
`
`SUPPLEMENTAL DECLARATION OF GARY LIAO IN SUPPORT OF
`PETITION FOR POST-GRANT REVIEW OF A COVERED
`BUSINESS METHOD UNDER 35 U.S.C. § 321 AND AIA, § 18
`
`
`
`
`
`
`
`
`
`
`
`
`1. My name is Gary Liao. I am currently President and owner of
`
`WhereExactly, Inc., an Oregon Corporation founded in 2005, providing software
`
`consulting, computer and software forensics, and location specific advertising
`
`services. I have a Bachelor of Science degree in Electrical Engineering from
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`University of California, San Diego (1988), and a Master of Business
`
`Administration degree from Portland State University (1999).
`
`2.
`
`I have spent the last 25 years working either as a software engineer, or
`
`as a consultant focused on analyzing software. From 1988 to 2005, I worked for a
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`range of companies as a software engineer including Advanced Micro Devices,
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`The Scripps Research Institute, Biosym Technologies, Charles Schwab & Co.,
`
`Inc., Integrated Surgical Systems, Inc., DAT Services, Inc., Intel Corp., Step
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`Technology, Webridge, Inc., and SoftSource Consulting. In 2005, I started my own
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`internet advertising and consulting company, WhereExactly, Inc.
`
`3.
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`In 1996, I designed and implemented a message oriented middleware
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`protocol for a distributed database client-server Internet based application.
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`Through 1999, I was the technical lead providing architectural guidance and/or
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`software developer for e-commerce stores including model.com, clique.com,
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`forbes.clique.com, animalfairboutique.com, skinet.clique.com, gear.com,
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`danner.com, and 800.com. These various websites provided e-commerce
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`functionality using various technologies including Microsoft Site Server
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`Commerce Edition, Microsoft SQL Server, and Cybercash for credit card
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`transactions. I was also the technical lead and architect for the Oregon Department
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`of Fish and Wildlife (ODFW) Point of Sale (POS) system. This project enabled the
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`sale of all Oregon Department of Fish and Wildlife fishing and hunting licenses,
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`tags, parking permits, and raffle tickets throughout the state of Oregon. This
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`system utilized a 3-tier client-server architecture over the Internet with each client
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`computer utilizing an Internet Browser at all Point-of-sale locations to conduct the
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`transactions to a central server. Through 2004, I joined an Internet startup,
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`Webridge. As the name suggests, Webridge provided technology using the Web
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`(Internet) to create a Bridge between businesses and consumers, and between
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`businesses and businesses. Among other tasks, I was tasked to incorporate various
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`technologies into the product solutions including Microsoft Commerce Server
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`2000 and Biztalk Server. Webridge, as well as many other technology companies
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`of the early 2000’s, struggled to address the challenges of scale; how to increase
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`the number of client computers and still provide adequate performance. So, I am
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`well aware of the technical challenges for accomplishing scale at that time.
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`Currently, I provide Internet advertising and consulting services. I provide Search
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`Engine Optimization (SEO) and other consulting services to various websites and
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`currently provide software development consulting services to Johns Hopkins
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`University School of Medicine, Johns Hopkins University School of Public Health,
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`Huron Consulting Group, and Ochsner Health Systems, and I provide litigation
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`consulting services for a number of clients as well.
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`4.
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`Based on the above experience and qualifications, I have a solid
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`understanding of the knowledge and perspective of a person of ordinary skill in
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`this technical field in 1999-2001.
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`5.
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`I am being compensated for my time spent in connection with this
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`matter at my standard consulting rate of $150/hr. I have no financial interest in the
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`outcome of the related litigations or this proceeding.
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`
`
`Knowledge Broker was a Metasearch Engine
`
`6.
`
`The opinions that follow in this section are responsive to the Patent
`
`Owner’s contention that Knowledge Broker was not a metasearch engine.
`
`Knowledge Broker was a metasearch engine by definition using either the Board’s
`
`Preliminary Construction or the Patent Owner’s Proposed Construction for
`
`metasearching. The definition I used for metasearch engine is an application or
`
`other instructions on a hardware device that performs metasearching as defined
`
`below (CBM2014-00001 – Patent Owner’s Response to Petition, p. 25):
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`
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`Page 3
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`Board’s Preliminary
`Construction
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`[sending] an unstructured keyword
`query or queries to plural hosts, as
`requested by a user, and grouping,
`sorting, and returning to the user the
`results received from each host
`
`
`Patent Owner’s Proposed
`Construction
`
`
`sending at least one search query
`to plural hosts, and returning the results
`received from each host
`
`
`
`7.
`
`Exhibit 1006, “Constraint-based Information Gathering for a Network
`
`Publication System,” and Exhibit 1007, “Agent-Based Document Retrieval for the
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`European Physicists: A Project Overview,” together describe both a “framework”
`
`with varied applications as well as a particular example of an “application
`
`environment, namely the Physicists Network Publishing System (PNPS), that
`
`serves as a testbed for the knowledge broker framework.” (Ex 1006, p. 4.) Also,
`
`in this example application, the “CBKB system acts as a front-end to a printing-on-
`
`demand system, originally called Physicists Network Publishing System (PNPS).”
`
`(Ex 1007, p. 4.) In part, it is this exemplary application environment, including but
`
`not limited to the web query interface, brokers, wrappers, constraints, data
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`repositories (aka search engines), and integration with print service backend, which
`
`is also described as “a uniform meta-search interface with clear semantics,
`
`developed on top of different search engines” (Ex 1007, p. 4), which I refer to as
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`“Knowledge Broker,” and which was a metasearch engine. These papers, Exhibits
`
`1006 and 1007, describe this specific example of Knowledge Broker with
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`Page 4
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`particular data repositories representing a broad range of heterogeneous data
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`sources and a specific print service backend, but these papers also describe other
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`possible applications of the Knowledge Broker framework, such as bargain finding
`
`and virtual catalog systems. (Ex. 1006, p. 2). This broader framework and variety
`
`of applications described in these references is encompassed by what I refer to as
`
`the “Knowledge Broker” metasearch engine as well.
`
`8.
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`Knowledge Broker accepts a search query request from a user.
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`Exhibit 1006, p. 10, Figure 2: “Form-based dialogue for request specifications,”
`
`shows an example of a user search query request. Exhibit 1006, p. 10, continues:
`
`“The user-friendly request specification is easy to learn and does not require
`
`background information on the internally used constraint format, the request
`
`syntax of particular data repositories nor on their internal data format.”
`
`9.
`
`Knowledge Broker then decomposes and transforms the query request
`
`as necessary and then sends the request real-time (Ex. 1007, p. 12) to plural unique
`
`hosts (aka data repositories).
`
`“After the user has specified the request (via the form-based dialogues, as
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`illustrated in Fig. 2), the specifications are automatically transformed into a
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`corresponding constraint structure. The generated constraint-based query is
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`then communicated to the generic broker, which further initiates all steps
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`Page 5
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`(decomposition of
`
`requests
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`into
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`subrequests,
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`threshold
`
`checks,
`
`recomposition of answers, etc.) to answer the specified request.
`
`Apart from this, the homogenization of the request specification is
`
`achieved by presenting a set of possibilities which depend only on the search
`
`domain, no matter which of the included data repository and external search
`
`tools are contacted to answer the request (e.g. fields for author, title, date,
`
`etc., for bibliographical searches). This is achieved by transforming the
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`request into a possibly more general, less precise, external search format of
`
`the corresponding external data repository, and by later filtering out the
`
`inappropriate results in the constraint solver.” (Ex. 1006, pp. 10-11.)
`
`10. Knowledge Broker provides the service of searching plural unique
`
`hosts. Exhibit 1007, p. 8, describes the specific implementation of Knowledge
`
`Broker as follows:
`
`
`“The CBKB system already serves as a testbed for research activities in the
`
`area of digital libraries at RXRC Grenoble. Our second project was to
`
`respond to the physics community’s need for integrated services by
`
`connecting PhysDoc, Physdis, and the Augsburg mirror of LANL.
`
`
`These repositories are distinct and heterogeneous enough to test the ability
`
`of CBKB to integrate new backends.”
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`
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`Page 6
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`These repositories are the plural unique hosts also referred to in Exhibit
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`1007 as “different search engines.” (Ex. 1007, p. 4.) These repositories represent a
`
`broad range of heterogeneous data sources. The references disclose Knowledge
`
`Broker searching: heterogeneous backend data sources (Ex. 1006, pp. 2, 9),
`
`including “several document databases” (Ex. 1006, p. 4); different external archive
`
`systems, each managed by its own management software (Ex. 1006, p. 4, Fig. 1;
`
`Ex. 1007, p. 8); different kinds of indexes and search tools (Ex. 1006, p. 7);
`
`interdisciplinary data sources (Ex. 1006, p. 11); data repositories with SQL
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`interfaces, or http interfaces, or Z39.50 interfaces (Ex. 1006, p. 13); data
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`repositories indexed by the Harvest search and index tool (Ex. 1007, pp. 4, 7); data
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`sources “no matter which” search engine or engine they use (Ex. 1007, pp. 4, 6, 9);
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`Webcrawlers (Ex. 1007, p. 11); different brokers and databases (Ex. 1007, pp. 5,
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`6); and distributed brokers, repositories and document servers (Ex. 1007, p. 13).
`
`And, these references state that the Knowledge Broker architecture and model
`
`apply generally, not just to the exemplary scientific document domains mentioned
`
`in the paper. (Ex. 1007, p. 1.)
`
`11. Knowledge Broker receives search results from plural unique hosts in
`
`response to its search queries sent to those hosts. Exhibit 1007, p. 6, states the
`
`following:
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`
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`Page 7
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`“What is missing, is distributed joint-functionality among the different data
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`repositories, and a sophisticated way of processing the search results.
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`To answer this need we have designed and implemented a heterogeneous
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`broker, which logically combine heterogeneous information retrieved from
`
`other brokers, on-line repositories, and databases (Borghoff and Schlicter
`
`1996), in reply to a physicist’s search query.”
`
`12. This clearly describes receiving search results from plural unique
`
`hosts. Further, Exhibit 1007, Section 3 “Current Implementation,” p. 12 describes
`
`the results in more detail stating how a wrapper is created for each of the plural
`
`unique hosts (aka server) and then Knowledge Broker “queries the server and
`
`receives the results in html-format.” This is described below:
`
`“Connecting an external server to the system is done by analyzing its search
`
`interface, then writing a wrapper for it. This wrapper receives the
`
`description of the constraints corresponding to the query, translates them
`
`into the query-string required by the search script, verifies that the indicated
`
`fields are accepted by the server and provides default values for required
`
`fields not specified by the user. It then queries the server and receives the
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`results in html-format. Finally it parses the results and translates them into
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`the constraint format accepted by the CBKB system.”
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`
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`Page 8
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`13. Knowledge Broker groups, sorts and returns to the user the search
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`results received from the plural unique hosts. “The final output can be displayed in
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`any of a number of formats selectable by the user: readable on screen as
`
`bibliographical data (authors, title, status, link, abstract); in summary form
`
`(ranking or sorting the results alphabetically by title or author for example); or
`
`displaying the complete information found about each matched document.” (Ex
`
`1007, p. 9.) Knowledge Broker queries the plural unique hosts in real-time in
`
`response to a user query request (which is different than how a Search Engine
`
`works ) as described in Exhibit 1007, p. 7, Section 2.2 “Features of the Constraint-
`
`Based Knowledge Brokers” (see excerpt below):
`
`“The key features on the Constraint-Based Knowledge Brokers are:
`
`…
`
`2. Concurrent Asynchronous Searches – A broker search engine can launch
`
`many concurrent searches that in principle could go on forever, be checked,
`
`refined and re-launched periodically. This is a radically different user
`
`paradigm (and a complementary one) than the “one query at a time” kind of
`
`interaction with which Web search engines support today.
`
`…
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`4. Knowledge Combination – The broker search engine allows combination
`
`of information returned by different information sources. Thus, this feature
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`Page 9
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`introduces a form of “joining,” similar to that provided by database systems
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`in the context of information gathering from multiple sources in distributed
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`domains.”
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`14. Knowledge Broker allows the user to pose both structured and
`
`unstructured (aka free-text) keyword queries. Exhibit 1006, p. 11, describes the
`
`user interface to include:
`
` “default set of structured search attributes depending on the search
`
`domain with supplementary precedence operators.
`
` A “free-text” entry field which allows additional attributes or untyped
`
`keywords as well as combinations of them.”
`
`15.
`
`In summary, Knowledge Broker was a metasearch engine, and the
`
`Knowledge Broker references, Exhibits 1006 and 1007, disclose “metasearching.”
`
`These Knowledge Broker references disclose, in response to receiving a search
`
`query from a user, sending the query in parallel to multiple backend data
`
`repositories, and, in real-time in response to a user’s search query, contacting
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`external data sources (search engines, databases, etc.) to answer the query. (Ex.
`
`1006, pp. 2, 7, 11-12; Ex. 1007, pp. 7, 10, 12.) These Knowledge Broker
`
`references disclose: sending http requests to the data archives (Ex. 1006, p. 12);
`
`completing an external search (Ex. 1006, p. 12); sending concurrent subrequests
`
`and requests (Ex. 1006, p. 2; Ex. 1007, p. 7); providing concurrency control among
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`
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`Page 10
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`related requests (Ex. 1006, p. 7); contacting external search tools to answer a user’s
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`search query (Ex. 1006, p. 11); sending partial requests in parallel (Ex. 1006, p.
`
`11); and performing some initial checks before an external search is initiated (Ex.
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`1006, p. 12); receiving 12 search hits collectively from two external data archives
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`in response to a user query (Ex. 1007, p. 10); generating a search query string for
`
`querying an external data source in response to a user’s search request (Ex. 1007,
`
`p. 12), after which “it then queries the server” (Ex. 1007, p. 12).
`
`16. Knowledge Broker is a metasearch engine using the Board’s
`
`preliminary construction because, as described above in paragraph 14, Knowledge
`
`Broker discloses “an unstructured keyword query or queries,” Knowledge Broker
`
`discloses sending those queries “to plural hosts” (see paragraphs 9-10 above),
`
`Knowledge Broker discloses sending the queries “as requested by a user” (see
`
`paragraphs 8-9 & 14 above), Knowledge Broker discloses “grouping, sorting, and
`
`returning to the user” the results (see paragraph 13 above), and Knowledge Broker
`
`discloses returning to the user “the results received from each host” (see
`
`paragraphs 11-13 above).
`
`17. Knowledge Broker is a metasearch engine using Patent Owner’s
`
`broader Proposed Construction because, as described above in paragraphs 9 and
`
`10, Knowledge Broker discloses “sending at least one search query to plural
`
`
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`Page 11
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`hosts,” and Knowledge Broker discloses “returning the results received from each
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`host” (see paragraphs 11-13 above).
`
`18. Dr. Carbonell came to a contrary conclusion. To the extent that Dr.
`
`Carbonell purports to describe the disclosures and teachings of the Knowledge
`
`Broker references, Exhibits 1006 and 1007, to a person of skill in the art in 1999-
`
`2000, I respectfully disagree on a number of levels, and I refute his conclusion for
`
`a number of reasons described in further detail below:
`
`a) Misinterprets use of Harvest System and omits non-Harvest
`
`servers.
`
`b)
`
`No support for statements that Knowledge Broker pre-processes
`
`data and searches internal indexed version of crawled data.
`
`c) Mischaracterizes Knowledge Broker as a Search Engine.
`
`d) Mischaracterizes external archives as web servers, using a
`
`narrow definition of Search Engine in the wrong time frame.
`
`e)
`
`Introduces irrelevant information (e.g. specific data types,
`
`crawling, search engines).
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`
`
`Misinterprets use of Harvest System and omits non-Harvest servers
`
`19. Dr. Carbonell states in Exhibit 2006, p 14-15:
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`
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`Page 12
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`“Knowledge Broker was not a metasearch engine. It was a single
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`search engine. At information ingestion time, it accessed different data
`
`sources, via its Harvester module, corresponding to a crawler of an
`
`individual search. The Harvester operated much like a standard search
`
`engine’s crawler in accessing different information sources and/or websites
`
`at information ingestion time (Petitioner’s Exhibit 1007, pp. 3-4).”
`
`20.
`
` Dr. Carbonell states that Knowledge Broker had a “Harvester
`
`module,” but this is not supported by the references. Dr. Carbonell cites to pages
`
`3-4 of Exhibit 1007, which state that the “PhysDep” service “supports the use of
`
`the Harvest search engine over a network of about 1000 local web-servers
`
`maintained at different European physics departments. The documents to be
`
`searched only need to be deposited on the department servers which are regularly
`
`searched and indexed by the Harvest system.”
`
`21. Dr. Carbonell’s referenced “Harvester module” is not part of
`
`Knowledge Broker. Rather, it is part of an entirely separate system referred to as
`
`“Harvest search engine” and “Harvest system” (NOT Knowledge Broker). The
`
`references do not state that Knowledge Broker contains a Harvest Module.
`
`PhysDoc and PhysDiss, both external archives searchable via Knowledge Broker,
`
`were merely part of the Harvest system.
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`
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`Page 13
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`22. Also, even if Knowledge Broker included a Harvest Module as Dr.
`
`Carbonell contends (which it does not), Dr. Carbonell ignores/omits the clear
`
`disclosure in the Knowledge Broker references of other non-Harvest servers and
`
`other real-time querying of backend external archives:
`
`a)
`
` “Harvest” was one, among other, backend external archives
`
`supported. See Ex. 1007, p. 8, Fig. 1:
`
`b)
`
`Also Exhibit 1007, p. 7, states, “At the backend, the service will
`
`connect, among others, to the Harvest servers within the European Physical
`
`
`
`Society,” see below:
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`
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`
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`Page 14
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`c)
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`Also, although some backend external archives searched by
`
`Knowledge Broker supported “harvest” servers, this did not require
`
`Knowledge Broker or the client of the external archive to crawl to access the
`
`data. In fact, Exhibit 1006, p. 12, describes not crawling but rather querying
`
`based on a user request, see below:
`
`d)
`
`This passage describes each of the supported external archives
`
`as including backend interfaces that encapsulate the following: generating a
`
`search request from the user initiated constraint-based query specification,
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`Page 15
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`submitting the request, parsing the results, and retranslating them for each
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`search hit. This describes real-time querying based on a user request rather
`
`than automated crawling.
`
`23. So Dr. Carbonell’s statement that Knowledge Broker accessed data
`
`sources “via its Harvester Module” is not supported by the references, and Dr.
`
`Carbonell’s conclusions that Knowledge Broker was not a metasearch engine
`
`based on this statement ignore clear disclosure in Exhibits 1006 and 1007 that
`
`Knowledge Broker performed real-time querying of other non-Harvest,
`
`heterogeneous sources such as Augsburg and Karlsruhe in addition to real-time
`
`querying of Harvest servers (and querying of Harvest servers did not require
`
`Knowledge Broker to crawl the information sources).
`
`
`
`No support for statement that Knowledge Broker pre-processes data
`
`24. Dr. Carbonell states in Exhibit 2006, p. 15:
`
`“Then, Knowledge Broker pre-processed
`
`that
`
`information,
`
`in part
`
`automatically and in part manually, to formulate and link to the constraints
`
`and relations of the domain (physics articles). When responding to queries,
`
`Knowledge Broker accessed its pre-processed internal version of the
`
`collected information, much like a search engine accesses its internal pre-
`
`processed index of the crawled web-sites at query processing time. The pre-
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`Page 16
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`processing includes the establishment and extension of domain-specific
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`physics “constraints” to relate the various information sources in the domain
`
`to create the broker.”
`
`25. However, there is no mention or use of the term “pre-process” in
`
`either Exhibit 1006 or Exhibit 1007. Dr. Carbonell’s cites for the above point to
`
`the following excerpt from Exhibit 1006, p. 7:
`
`“Using this broker system to exploit a wide range of physics-specific
`
`archives, many of the above mentioned shortcomings can be overcome by
`
`flexibly adding missing functionalities to the individual data access
`
`interfaces. First of all, it is possible to homogenize or even extend the
`
`admissible types of requests with respect to the different data repositories to
`
`be accessed, even when the accessed data repositories do not exactly match
`
`the type of request specification.”
`
`26. But this passage discusses homogenizing “data access interfaces” not
`
`pre-processing data. What this passage is actually describing is creating an
`
`abstraction layer so that different/heterogeneous data repositories can respond to
`
`user queries even when a data repository’s interface specification doesn’t exactly
`
`match the user query request.
`
`27. Thus, the passage in the Knowledge Broker references cited by Dr.
`
`Carbonell does not support his statements. Nor do the Knowledge Broker
`
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`Page 17
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`
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`references otherwise support Dr. Carbonell’s statement that “[w]hen responding to
`
`queries, Knowledge Broker accessed its pre-processed internal version of the
`
`collected information, much like a search engine accesses its internal pre-processed
`
`index of the crawled web-sites at query processing time.” I do not see any
`
`disclosure in Exhibits 1006 and 1007 that indicates Knowledge Broker searched an
`
`internal indexed version of crawled data instead of external data sources when
`
`responding to a user’s search query.
`
`
`
`Mischaracterizes Knowledge Broker as a Search Engine
`
`28.
`
`It’s unnecessary to define “Search Engine” for the purpose of
`
`establishing if “metasearching” is performed because neither the Board’s
`
`preliminary construction nor the Patent Owner’s proposed construction of
`
`“metasearching” requires querying a “Search Engine” but rather simply requires
`
`querying a “host.” However, Dr. Carbonell repeatedly calls Knowledge Broker a
`
`search engine and not a metasearch engine. I believe Dr. Carbonell is defining
`
`search engine to be an application that includes a crawler and pre-processes
`
`crawled information. But there is no use of the term crawl or pre-process in either
`
`Exhibit 1006 or Exhibit 1007 (other than Webcrawlers being external searched
`
`repositories). As explained above, Dr. Carbonell’s statements that Knowledge
`
`Broker included a Harvest Module to crawl information and that Knowledge
`
`
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`Page 18
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`
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`Broker pre-processed data to create an internal index are not supported by the
`
`references. Dr. Carbonell’s characterization of Knowledge Broker as a search
`
`engine is based on these unsupported statements, and is therefore also unsupported.
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`Exhibits 1006 and 1007 do not teach a person having ordinary skill in the art in
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`1999-2000 that Knowledge Broker was a search engine rather than a metasearch
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`engine. To the contrary, and as stated in further detail above, Exhibit 1006 and
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`Exhibit 1007 clearly show to a person having ordinary skill in the art in 1999-2000
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`that Knowledge Broker performed metasearching.
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`
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`Mischaracterizes external archives as web servers
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`29. Dr. Carbonell’s statement that Knowledge Broker was not a
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`metasearch engine appears to be based on a narrow interpretation of the term
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`“search engine” today as opposed to the meaning a person having ordinary skill in
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`the art in 1999-2000 would have given that phrase. In Exhibit 2006, p. 16, Dr.
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`Carbonell states:
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`“But Knowledge Broker’s “search engines” are only what we would call
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`today web servers, repositories of information that must be ingested
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`(crawled or otherwise downloaded) as done by a simple search engine’s
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`crawling capability.”
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`Page 19
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`30.
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`I do not agree that a person having ordinary skill in the art in 1999-
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`2000 would read the Knowledge Broker references and understand “search
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`engines,” as used in Exhibit 1007, to mean “web servers, repositories of
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`information that must be ingested (crawled or otherwise downloaded),” nor would
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`the person having ordinary skill in the art characterize all Knowledge Broker
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`external archives—which Knowledge Broker self-described as “different search
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`engines” (Ex. 1007, p 4; see also Ex. 1007, p. 9)—as “web servers.” As described
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`in the particular implementation above, Knowledge Broker queried and searched in
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`real-time various heterogeneous sources such as Augsburg and Karlsruhe, as well
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`as Harvest servers. Knowledge Broker also discloses accessing its external
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`archives via http protocol, a Z39.50 interface or SQL queries. (Ex. 1006, p. 13.)
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`Therefore, the person having ordinary skill in the art in 1999-2000 would not have
`
`understood “search engine” as used in Exhibit 1007 to be limited to “web servers”
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`“today,” but would have instead understood that term to include the various
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`heterogeneous data repositories and external archives searched by Knowledge
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`Broker in the implementations described in Exhibits 1006 and 1007.
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`
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`Introduces irrelevant information (e.g. specific data types, crawling …)
`
`31. Dr. Carbonell’s conclusions regarding whether or not Knowledge
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`Broker performs metasearching and/or performs the elements of the challenged
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`
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`Page 20
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`
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`claims are based on features not required by the definition of metasearch or by the
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`challenged claims. (Ex. 2006, pp. 10-13, 20.) For instance, the claims don’t
`
`require retrieving any particular type of data (e.g., the claims don’t require the data
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`be current and up-to-date, structured, unstructured or semistructured), so the types
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`of data stored in the repositories is irrelevant. Also, the claims don’t require a
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`particular type of host, so it’s irrelevant if the data repositories are search engines
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`or not, or crawl or not, or are called search engines or web servers. What is
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`relevant with regard to the data repositories and the definition of metasearching is
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`if there are plural unique hosts, and if plural unique hosts accept either an
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`unstructured keyword query or any query, and then return results. Knowledge
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`Broker definitely sends, in response to a user request, search queries to plural
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`unique hosts (aka plural data repositories) that accept either an unstructured
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`keyword query or any query, and returns results to the user. Knowledge Broker
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`therefore performs metasearching and is a Metasearch Engine.
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`
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`Mamma.com discloses claim elements (g) and (h)
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`32. The opinions that follow in this section are in response to Patent
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`Owner’s contention that Mamma.com does not disclose elements (g) and (h)
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`(CBM2014-00001 – Patent Owner’s Response to Petition, pp. 54-56). The
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`Page 21
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`challenged claims 2, 6, and 8 each contain identical claim elements (g) and (h) as
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`follows:
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`(g)
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`receiving another Hypertext Transfer Protocol request from the
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`client device for placing an order for the at least one item;
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`(h) processing the order.
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`33. Mamma.com provided advertising in the form of Key Word
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`advertising, Hot Buttons, and Download Now Icons. (Ex. 1005, p. 8.) In addition,
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`Mamma.com tracked every ad view and ad click. (Ex. 1005, p. 4)
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`34. Download Now Icons allowed software companies the possibility to
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`electronically distribute their application. (Ex. 1005, p. 8.) This allowed users the
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`ability to order the software companies’ software directly from Mamma.com.
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`35. When a user clicks on a Download Now Icon, the user is ordering the
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`software company’s application. First, however, the user click sends a Hypertext
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`Page 22
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`
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`Transfer Protocol Request to Mamma.com, so Mamma.com can track the click and
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`record the order of the application, disclosing claim limitation (g), and then
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`subsequently process the order request for the application by redirecting the user to
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`the software company’s ftp server or download page, disclosing claim limitation
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`(h).
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`36. Ordering free software for download as disclosed in Mamma.com was
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`a well-known business practice in 1999-2000. Product availability, pricing, and
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`purchasing are not required by the claims, rather the claims only require “placing
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`an order” and “processing an order.” Mamma.com disclosed “placing an order” by
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`tracking the advertising click requesting the downloadable software and
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`“processing an order” by redirecting the client for download of the ordered
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`software. This is analogous today to when users order free apps to download onto
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`their phones. There is no question that clicking an icon on a smart phone today to
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`install a free app such as “Plants vs. Zombies” is an example of “placing an order”
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`and “processing an order” even though no product availability, pricing, or
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`purchasing is required.
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`
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`Knowledge Broker discloses claim elements (g) and (h)
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`37. The opinions in this section are in response to Patent Owner’s
`
`contention that Knowledge Broker does not disclose elements (g) and (h).
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`
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`Page 23
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`
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`Knowledge Broker discloses “receiving another Hypertext Transfer Protocol
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`request from the client device for placing an order for the at least one item” and
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`“processing the order,” where the at least one item is a document for printing-on-
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`demand on local commercial copy centers (Ex. 1006, p. 4) or a document to be
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`shipped by mail (Ex. 1007).
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`38. Further, Knowledge Broker describes a basic architecture that
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`includes “production management and controlling,” which includes both receiving
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`a request for an order and processing an order. (Ex. 1006, p. 4.)
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`
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`39. The Knowledge Broker basic architecture also includes “clients and
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`communication infrastructure,” which includes a communication infrastructure
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`Page 24
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`
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`such as Hypertext Transfer Protocol, which is the communications protocol
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`underlying the World Wide Web. (Ex. 1006, p. 5.)
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`40. The above infrastructure described in Exhibit 1006 discloses claim
`
`elements (g) and (h).
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`41. Exhibit 1007 also discloses claim elements (g) and (h) on pages 10-
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`13.
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`…
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`Page 25
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`42. This passage, and in particular the “Web-form for the order,” clearly
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`discloses “receiving another Hypertext Transfer Protocol request from the client
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`device for placing an order for the at least one item.” Also, passing the printing
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`request to Oldenburg and processing the document to finally send a printed, bound
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`document by surface mail to the customer clearly discloses “processing the order.”
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`In addition, Knowledge Broker also discloses processing orders for selected
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`documents to be printed and delivered, including integrating accounting an
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