Ex Parte Musgrove

Patent Trial and Appeal Board

Feb 27, 2014

11730930 (P.T.A.B. Feb. 27, 2014)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
11/730,930 04/04/2007 Timothy A. Musgrove 037141-13 1218
22204 7590 02/27/2014
NIXON PEABODY, LLP
401 9TH STREET, NW
SUITE 900
WASHINGTON, DC 20004-2128
EXAMINER
GOFMAN, ALEX N
ART UNIT PAPER NUMBER
2163
MAIL DATE DELIVERY MODE
02/27/2014 PAPER
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
__________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
__________

Ex parte TIMOTHY A. MUSGROVE1
__________

Appeal 2011-009241
Application 11/730,930
Technology Center 2100
__________

Before ERIC B. GRIMES, LORA M. GREEN, and
JEFFREY N. FREDMAN, Administrative Patent Judges.

GRIMES, Administrative Patent Judge.

DECISION ON APPEAL
This is an appeal under 35 U.S.C. § 134 involving claims related to
identifying documents that are most closely related to the documents
returned in response to a search query. The claims have been rejected as
obvious. We have jurisdiction under 35 U.S.C. § 6(b).
We reverse.

1 Appellant identifies the Real Party in Interest as TextDigger, Inc. (App.
Br. 3).
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STATEMENT OF THE CASE
The Specification states that
the present invention very quickly extracts the needed thematic
elements from the additional hit documents of the SERP [search
engine results page] to identify, and associate, those documents
that are very likely to be relevant to the highest ranked
reference documents. The additional documents can then be
displayed in response to the users’ selection of the “Similar
pages” hyperlink of the reference document.
(Spec. 6, ¶ 17.)
In the disclosed system and method, a “text function tagger . . .
executes a rule-based, partial parse, on the text excerpts such as sentences
and snippets of each identified document . . . and provides a variety of
speech-act and assertion-type function tags for these text excerpts” (id. at 15,
¶ 46). The Specification states that the “text excerpt, sparse though it may
be, provide[s] a crucial semantic context. Thus, . . . the text excerpt such as
the sentence or snippet can be analyzed to guide, or filter, the
recommendation of other additional documents for the user.” (Id. at 4, ¶ 9.)
Claims 1, 4-13, 16-25, and 28-36 are on appeal. Claims 1 and 12 are
illustrative and read as follows (emphasis added):
1. A computer system for identifying electronic documents stored on a
computer readable media, and providing a search result in response to a
search query, comprising:
a processor in communication with the computer readable media, the
processor comprising:
a user interface module that receives a search query from a
user;
a search engine that accesses a corpus of electronic documents
to identify a predetermined number of documents that satisfy the
search query, the identified documents including a predetermined
number of reference documents which are a subset of the identified
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documents deemed by the search engine to be most relevant to the
search query and secondary documents;
a text function tagger that parses text excerpts of the identified
documents and applies text function tags to the text excerpts of the
identified documents, wherein the text function tags identify semantic
roles of the text excerpts; and
a secondary processing module that identifies the secondary
documents that have a text function tag that matches a text function
tag of a reference document,
wherein the user interface module further generates a search
engine results page in response to the search query, the search engine
results page including a listing of the identified reference documents,
each with a hyperlink to at least one secondary document identified by
the secondary processing module as having a matching text function
tag.

12. A computer system for identifying electronic documents stored on a
computer readable media, and providing a search result in response to a
search query, comprising:
a processor in communication with the computer readable media, the
processor comprising:
a user interface module that receives a search query from a
user; and
a search engine that accesses a corpus of electronic documents
to identify documents that satisfy the search query;
wherein the user interface module further generates a display of
a search engine results page in response to the search query, the
search engine results page including a listing of a subset of the
identified documents deemed by the search engine to be most relevant
to the search query, each of the listed documents having a hyperlink to
at least one similar document identified using text function tags,
wherein the text function tags identify semantic roles of the identified
documents and the similar documents, the similar document being
selected from the documents that satisfy the search query which were
identified by the search engine.

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DISCUSSION
The Examiner has rejected all of the claims on appeal under 35 U.S.C.
§ 103(a) as obvious based on Copperman2 and Marchisio3 (Ans. 4). The
Examiner finds that Copperman discloses most of the limitations of claim 1,
including
c. parsing text excerpts of the identified documents and
applying text function tags to the text excerpts [0044].
[Copperman parses and tags documents prior to a query being
received. As such, when a user identifies specific documents
for retrieval, they are already parsed and tagged.]
d. identifying the secondary documents that have text
function tags that matches a text function tag of a reference
document [Figure 9c, Figure 9d, 0052].
(Id. at 5, alterations in original.)
The Examiner also finds that Copperman discloses most of the
limitations of claim 12, including “listed documents having a hyperlink to a
similar document; wherein the similar document is selected from the
identified documents that satisfy the search query [Figure 8, Figure 9C,
Figure 9D, 0076]. [The ‘related’ feature as seen in Figures 8, 9C and 9D,
retrieves similar documents via a hyperlink.].” (Id. at 9, alterations in
original.)
The Examiner finds that Marchisio discloses text function tags that
identify semantic roles (id. at 5, 9) and concludes that it would have been
obvious to modify Copperman with Marchisio “in order to identify parts of

2 US 2003/0115191 A1, published June 19, 2003.
3 US 2005/0267871 A1, published Dec. 1, 2005.
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documents based on their tags” (id. at 6) or “in order to identify documents
based on their tags” (id. at 9).
Appellant argues, among other things, that Copperman does not teach
the “text function tagger” and “secondary processing module” required by
claim 1 (App. Br. 16). In particular, Appellant argues that “Copperman . . .
fails to disclose parsing text excerpts of the identified documents and
applying text function tags to the text excerpts of the identified documents”
(id. at 17).
With regard to claim 12, Appellant argues that “Copperman and
Marchisio fail to disclose that the at least one similar document is selected
from a document that also satisfies the search query, and that the similar
document is identified based on text function tags that identify semantic
roles commonly found in the documents that satisfy the search result” (id. at
18). Specifically, Appellant argues that, in Copperman, “the similar
document is not identified based on whether the document satisfies the
search query. Instead, relevant concepts (or topics) are identified in [the]
Copperman [ ] search results based on the document tags.” (Id.)
We agree with Appellant that the Examiner has not provided evidence
sufficient to show that the cited references disclose or would have made
obvious all of the limitations of claims 1 and 12. The Examiner points to
Copperman’s paragraphs 44 and 52, and its Figures 9C and 9D, as disclosing
the text function tagger of claim 1 and identifying documents based on text
function tags (Ans. 5).
Copperman states that “in an automated customer relationship
management (CRM) system, the user is typically a customer of a product or
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service who has a specific question about a problem or other aspect of that
product or service” (Copperman 1, ¶ 4). “To increase the effectiveness of a
CRM system or other content provider, intelligence can be added to the
content” (id. at 1, ¶ 6). Copperman discloses “a system 400 for assisting a
knowledge engineer in associating intelligence with content” (id. at 4, ¶ 43).
Copperman discloses that “documents or other pieces of content
(referred to as knowledge containers 201) are mapped by appropriately-
weighted tags 202 to concept nodes 205 in multiple taxonomies 210 (i.e.,
classification systems)” (id. at 3, ¶ 37). In Copperman’s system, “candidate
feature selector 420 automatically extracts from a document possible
candidate features (e.g., text words or phrases . . .) that could potentially be
useful in classifying the document to one or more concept nodes 205 in the
taxonomies 210 of knowledge map 200” (id. at 5, ¶ 44). Copperman also
discloses a “content provider 500 for providing a guided search for needed
information by constraining the documents to ‘documents in play’ that
include concept features from the user query and other related concept
features suggested to, and selected by, the user” (id. at 6, ¶ 52).
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Copperman’s Figure 9C is reproduced below:

Figure 9C shows a web page with a list of documents returned in
response to a user query (id. at 10, ¶ 81). The web page also includes a list
of searches (835) related to the initial query and “[b]y clicking on the ‘More’
link 905, user 105 can bring up for display other choices of related features,
as illustrated in FIG. 9D” (id. at 11, ¶ 81).
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Copperman’s Figure 9D is reproduced below:

Figure 9D shows the web page of Figure 9C with additional searches
related to the initial query displayed.
None of the cited passages or figures of Copperman describes
applying text function tags to excerpts of the identified documents or
identifying similar documents using text function tags. Copperman refers to
mapping documents to concept nodes “by appropriately-weighted tags 202”
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(Copperman 3, ¶ 37), but those “tags” are merely associations of the
document with different subject matter classifications. Similarly,
Copperman refers to extracting candidate features such as “text words or
phrases” from a document to aid in classifying the subject matter of the
document (id. at 5, ¶ 44).
The claims, however, require applying “text function tags to the text
excerpts” of documents identified in response to a search query. The
Specification clarifies that text function tags identify “a variety of speech-
act and assertion-type function[s]” such as Interrogative, Supporting
example, Description, etc. (Spec. 15, ¶ 46). The Examiner has not identified
any disclosure in Copperman of tags that identify text functions, as required
by the claims.
In addition, as Appellant has pointed out (App. Br. 17), the tags
disclosed by Copperman are not applied to excerpts of the identified
documents. Rather, they are applied to the documents themselves, in order
to map them into a classification system before a search query is submitted
by a user (see Copperman 3, ¶ 37: “documents . . . are mapped . . . to
concept nodes 205 in multiple taxonomies 210 (i.e., classification
systems)”). The Examiner has not identified any disclosure in Copperman
of any sort of tagging being carried out on, for example, the text excerpts of
the results (820) shown in Copperman’s Figure 9C or 9D.
Similar to claim 1, claim 12 on appeal requires “a hyperlink to at least
one similar document identified using text function tags” (emphasis added).
As discussed above, Copperman does not disclose tagging documents with
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text function tags, and therefore also does not disclose identifying documents
using such tags.
Finally, we also agree with Appellant (App. Br. 12) that the Examiner
has not established that a person of ordinary skill in the art would have
considered it obvious to combine Copperman and Marchisio. The Examiner
concluded that it would have been obvious to combine the references “in
order to identify parts of documents based on their tags” (Ans. 6) or “in
order to identify documents based on their tags” (id. at 9). The Examiner
did not, however, provide any reasoned explanation of how combining
Copperman’s system for mapping documents in a classification system with
Marchisio’s Enhanced Natural Language Parser (id. at 5-6) would have
furthered the goal of identifying documents, or parts of them, based on their
tags. The Examiner’s rejection therefore lacks “articulated reasoning with
some rational underpinning [as required] to support the legal conclusion of
obviousness.” KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 418 (2007)
(quoting In re Kahn, 441 F.3d 977, 988 (Fed. Cir. 2006)).
SUMMARY
We reverse the rejection of claims 1, 4-13, 16-25, and 28-36 as
obvious based on Copperman and Marchisio.

REVERSED

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