Ex Parte BEACH

Patent Trial and Appeal Board

Jul 11, 2018

13599070 (P.T.A.B. Jul. 11, 2018)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE
13/599,070 08/30/2012
100462 7590 07/13/2018
Dority & Manning P.A. and Google LLC
Post Office Box 1449
Greenville, SC 29602
UNITED ST A TES OF AMERICA
FIRST NAMED INVENTOR
Nathan Dickerson BEACH
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
ATTORNEY DOCKET NO. CONFIRMATION NO.
GGL-1080 2963
EXAMINER
SPRATT,BEAUD
ART UNIT PAPER NUMBER
2143
NOTIFICATION DATE DELIVERY MODE
07/13/2018 ELECTRONIC
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.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
usdocketing@dority-manning.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte NATHAN DICKERSON
Appeal2018-001000
Application 13/599,070 1
Technology Center 2100
Before TERRENCE W. McMILLIN, KARA L. SZPONDOWSKI, and
SCOTT B. HOWARD, Administrative Patent Judges.
HOWARD, Administrative Patent Judge.
DECISION ON APPEAL
Appellant appeals under 35 U.S.C. § 134(a) from the Examiner's
Final Rejection of claims 1-5, 7-12, 14--18, and 20, which constitute all of
the claims pending in this application. We have jurisdiction under 35 U.S.C.
§ 6(b).
We affirm.
1 Appellant identifies Google Inc. as the real party in interest. App. Br. 3.
Appeal2018-001000
Application 13/599,070
THE INVENTION
The disclosed and claimed invention is directed to detecting a hover
event using cursor sequences based on information associated with cursor
movements. See Spec. ,r 35.2
Claim 1, reproduced below with the disputed limitations italicized, is
illustrative of the claimed subject matter:
1. A method comprising:
storing, by one or more computer devices, information
regarding a first cursor sequence that resulted in an occurrence
of a hover event, and information regarding a second cursor
sequence that did not result in an occurrence of the hover
event, the first cursor sequence and the second cursor sequence
identifying a manner in which a particular cursor was moved
relative to a display of a particular document;
obtaining, by the one or more computer devices, cursor
information that identifies a manner in which a cursor is moved
relative to a display of a search results document;
comparing, by the one or more computer devices, the
cursor information to the first cursor sequence and the second
cursor sequence, wherein comparing the cursor information to
the first cursor sequence and the second cursor sequence
includes generating a sequence based on the cursor
information and calculating a first difference between the
sequence and the first cursor sequence, calculating a second
difference between the sequence and the second cursor
sequence, and comparing the first difference and the second
difference to determine whether the hover event occurred, the
hover event occurring when the first difference is smaller than
the second difference;
2 We refer to the Specification filed Aug. 30, 2012 ("Spec."); Final Office
Action mailed Dec. 22, 2016 ("Final Act."); Appeal Brief filed June 26,
2017 ("App. Br."); and Examiner's Answer mailed Sept. 5, 2017 ("Ans.").
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Application 13/599,070
determining, by the one or more computer devices and
based on a result of comparing the cursor information to the
first cursor sequence and the second cursor sequence, that the
hover event occurred with respect to a search result, of the
search results document, when the cursor information more
closely matches the first cursor sequence than the second
cursor sequence; and
peiforming, by the one or more computer devices, an
action based on determining that the hover event occurred,
performing the action including changing an
appearance of the search results document and providing,
with the search results document, information that
describes the search result, the information, that describes
the search result, including a snippet associated with the
search result.
REFERENCES
The prior art relied upon by the Examiner as evidence in rejecting the
claims on appeal is:
Abrams US 7,240,299 B2
Gupta et al. US 2010/0191856 Al
(hereinafter "Gupta")
White et al. US 2013/0246383 Al
(hereinafter "White")
Silber et al. US 2013/0275422 Al
(hereinafter "Silber")
REJECTIONS
July 3, 2007
July 29, 2010
Sept. 19, 2013
Oct. 17, 2013
Claims 1-5, 7-12, 14--16, 18, and 20 stand rejected under pre-AIA 35
U.S.C. § I03(a) as being unpatentable over White, Abrams, and Silber.
Ans. 2-27.
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Application 13/599,070
Claim 17 stand rejected under pre-AIA 35 U.S.C. § 103(a) as being
unpatentable over White, Abrams, Silber, and Gupta. Ans. 27-29.
ANALYSIS
We have reviewed the Examiner's rejections in light of Appellant's
arguments that the Examiner erred. In reaching this decision, we have
considered all evidence presented and all arguments made by Appellant. We
are not persuaded by Appellant's arguments.
Appellant argues White's classifying features into specific user
actions and defining features as cursor-related events including hover views
does not teach or suggest "storing ... information regarding a first cursor
sequence that resulted in an occurrence of a hover event, and information
regarding a second cursor sequence that did not result in an occurrence of
the hover event," as recited in claim 1. App. Br. 9-10.
During examination of a patent application, a claim is given its
broadest reasonable construction "in light of the specification as it would be
interpreted by one of ordinary skill in the art." In re Am. Acad. of Sci. Tech
Ctr., 367 F.3d 1359, 1364 (Fed. Cir. 2004) (internal citations and quotations
omitted). There is a presumption that a claim term carries its ordinary and
customary meaning. In re Translogic Tech., Inc., 504 F.3d 1249, 1257 (Fed.
Cir. 2007). An applicant may rebut this presumption, however, by acting as
his own lexicographer, providing a definition of the term in the specification
with "reasonable clarity, deliberateness, and precision." See In re Paulsen,
30 F.3d 1475, 1480 (Fed. Cir. 1994). In the absence of such a definition,
limitations are not to be read from the specification into the claims. In re
Van Geuns, 988 F.2d 1181, 1184 (Fed. Cir. 1993). "[A]lthough the
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Application 13/599,070
specification often describes very specific embodiments of the invention, we
have repeatedly warned against confining the claims to those
embodiments .... [C]laims may embrace 'different subject matter than is
illustrated in the specific embodiments in the specification."' Phillips v.
AWH Corp., 415 F.3d 1303, 1323 (Fed. Cir. 2005) (en bane) (citations
omitted).
Claim 1 does not distinguish the two types of information stored
except that some information "regard[ s] a first cursor sequence that resulted
in an occurrence of a hover event" and some information "regard[ s] a second
cursor sequence that did not result in an occurrence of the hover event."
Neither claim 1 nor Appellant's Specification provides any limiting
definition for the claimed first and second "cursor sequence." Rather,
Appellant's Specification merely provides examples describing
"generat[ing] a cursor sequence based on the information that identifies the
manner in which the user moves the cursor," "monitor[ing] cursor
movements within a search results document" and "generat[ing] a cursor
sequence based on information associated with the cursor movements."
Spec. ,r,r 34--35. Accordingly, applying the broadest reasonable
construction, we agree with the Examiner's interpretation that information
regarding a cursor sequence from a hover event is taught by White's
tracking cursor movement and comparing extracted features from cursor
data to the user behavior category of hover events; and we also agree with
the Examiner's interpretation that information regarding a cursor sequence
not from a hover event is taught by White's tracking cursor movement and
comparing extracted features from cursor data to user behavior categories
that are not hover events (i.e., highlighting). See Ans. 30-31 ( citing White
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,r,r 14, 44, 50, 52, 61). Because Appellant's arguments are not
commensurate with the scope of the claims, they are unpersuasive. See In re
Self, 671 F.2d 1344, 1348 (CCPA 1982).
As cited by the Examiner (Ans. 30-31 ), White teaches "browser
agents on the user computer may capture cursor activity data 302
corresponding to the user interactions with the current search result page
and, such as cursor movements ... from which a user behavior extraction
module 3 04 may extract cursor events representing user interactions with
the current search result page." White ,r 61 ( emphasis added). White also
discloses "the extraction mechanism 106 may define specific user actions
based upon feature data," and"[ e Jach feature may be defined as a set of
various cursor-related events, such as cursor trails, reading patterns, pointer
clicks, scrolls, hover views, text selections (e.g., highlighting), search box
interactions and/or the like over a pre-established time period." White ,r 28.
With regard to hover events, White teaches "relevance/click prediction
features may include hover-related features" and "[t]he example hover-
related feature may include a vector storing a set of cursor position
coordinates, search result element( s) within the particular area, a time
interval and/or the like." White ,r 50. In other words, as found by the
Examiner, White teaches monitoring cursor activity and using the monitored
information to extract cursor events that represent user interactions and
define cursor events that are hover events as well as cursor events that are
not hover events (i.e., cursor trails, reading patterns, pointer clicks, scrolls),
and subsequently using these cursor events in prediction models.
Appellant has not persuasively argued why White's monitoring cursor
activity and extracting events that are hover events does not teach the
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claimed "storing ... information regarding a first cursor sequence that
resulted in an occurrence of a hover event." Appellant has also not
persuasively argued why White's monitoring cursor activity and extracting
events that are not hover events (i.e., cursor trails, reading patterns, pointer
clicks, scrolls) does not teach the claimed "storing ... information regarding
a second cursor sequence that did not result in an occurrence of the hover
event."
Appellant further contends White's producing a correlation result that
stores the classification between the feature data and set of user actions, used
to generate and update a user prediction model, does not teach or suggest
"comparing ... the cursor information to the first cursor sequence and the
second cursor sequence ... includ[ ing] generating a sequence based on the
cursor information," as recited in claim 1. App. Br. 10-11.
We agree with the Examiner's finding that White's comparing
extracted features from cursor data to user behavior categories teaches
comparing cursor information to a first and sequence cursor sequence. Ans.
31 ( citing White ,r,r 15, 28). As discussed above, White teaches monitoring
cursor activity and using the monitored information to extract cursor events
that represent user interactions and define cursor events that are hover events
as well as cursor events that are not hover events (i.e., cursor trails, reading
patterns, pointer clicks, scrolls), and subsequently using these cursor events
in prediction models. See White ,r,r 28, 50, 61. Appellant has not
persuasively argued why White's storage and prediction using extracted
cursor data features and defined user behavior categories does not teach the
claimed comparing the cursor information to the first cursor sequence and
the second cursor sequence generated based on the cursor information.
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Appellant further contends Abrams' use of motion vectors associated
with the movement of a pointing device, and use of the learned motion
vectors to predict the user's destination icons, does not teach or suggest
"calculating a first difference between the sequence and the first cursor
sequence, calculating a second difference between the sequence and the
second cursor sequence, and comparing the first difference and the second
difference to determine whether the hover event occurred," as recited in
claim 1. App. Br. 13. Appellant argues White's defining user actions for a
user intent prediction model does not teach or suggest "determining ...
based on a result of comparing the cursor information to the first cursor
sequence and the second cursor sequence, that the hover event occurred with
respect to a search result, of the search results document, when the cursor
information more closely matches the first cursor sequence than the second
cursor sequence," as recited in claim 1. App. Br. 14.
Appellant's argument against Abrams separately from White does not
persuasively rebut the combination made by the Examiner. One cannot
show non-obviousness by attacking references individually, where the
rejections are based on combinations of references. In re Merck & Co., Inc.,
800 F.2d 1091, 1097 (Fed. Cir. 1986); In re Keller, 642 F.2d 413,425
(CCPA 1981); see Ans. 32.
Specifically, we agree with the Examiner's finding that White teaches
matching a cursor sequence with a hover event, and Abrams' comparing an
input cursor vector to stored vectors to see which vector the input vector is
more closely associated with in order to predict a destination teaches or
otherwise suggests calculating differences and comparing them to know
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which vector is more associated with the input vector. Ans. 31 ( citing
Abrams, col. 5); Ans. 32 (citing Abrams, col. 5; White ,r,r 15, 28, 44).
For example, as cited by the Examiner (Ans. 31 ), Abrams discloses:
While the actual motion of the pointing cursor 450, generated
by the user's movement of the pointing device (e.g., 726), may
more closely follow motion vectors 414, 415, 416, 417 and 418,
the user would see the pointing device motion indication
(pointing cursor 450) on the screen (e.g., 739) follow a motion
vector more similar to 602. Likewise, if after generation of a
motion vector similar to motion vector 414 the motion of the
pointing cursor 450 more closely followed a motion vector 420,
then the pointing device program may indicate that destination
point icon 608 was the most likely destination point icon.
Abrams, col. 5, 11. 55---66 ( emphasis added). As discussed above, White
teaches monitoring cursor activity and using the monitored information to
extract cursor events that represent user interactions and define cursor events
that are hover events, and subsequently using these cursor events in
prediction models. See White ,r,r 28, 50, 61.
Appellant has not persuasively argued why Abrams' comparing the
actual motion of a cursor (i.e., cursor sequence) to motion vectors (i.e., first
and second cursor sequence) to determine if the cursor is more closely
following a specific motion vector (i.e., more similar to with less difference
from one cursor sequence than the other) does not teach or otherwise suggest
the claimed "calculating a first difference between the sequence and the first
cursor sequence, calculating a second difference between the sequence and
the second cursor sequence, and comparing the first difference and the
second difference" or "determining ... based on a result of comparing the
cursor information to the first cursor sequence and the second cursor
sequence ... when the cursor information more closely matches the first
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cursor sequence than the second cursor sequence." Appellant has also not
argued why White's prediction using cursor events including hover events
does not teach the claimed comparison to "determine whether the hover
event occurred," or "determining ... based on a result of comparing the
cursor information to the first cursor sequence and the second cursor
sequence, that the hover event occurred with respect to a search result, of the
search results document."
Appellant further contends White's producing a correlation result that
stores the classifications between features data and user actions, and using
the correlation result to update a user intent prediction model, does not teach
or suggest "performing ... an action based on determining that the hover
event occurred," as recited in claim 1. App. Br. 15.
We agree with the Examiner's finding that White teaches a prediction
model performing actions based on categorized user events such as
hovering. Ans. 33 ( citing White ,r,r 5, 17, 28).
As cited by the Examiner (Ans. 33), White teaches "the extraction
mechanism 108 may classify one or more features, into the specific user
actions, such as a re-query (e.g., a search request for another search query),
user attention (e.g., reading, gazing and/or the like), an electronic document
selection and/or the like." White ,r 28 ( emphasis added). In other words,
White further classifies features (i.e., hover event) with further actions such
as user attention (i.e., reading). Appellant has not persuasively argued why
White's association of features, such as a hover event (see White ,r,r 28, 50,
61 ), with user actions, such as user attention or reading information (see
White ,r 28), does not teach the claimed performing an action based on
determining a hover event occurred.
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Accordingly, we sustain the Examiner's rejection of claim 1, along
with the rejection of commensurate independent claims 8 and 15, for which
Appellant relies on the same arguments as discussed above for claim 1 (see
App. Br. 15-18), as well as the rejections of dependent claims 2-5, 7, 9-12,
14, 16-18, and 20, which are not argued separately (id. at 19).
DECISION
For the above reasons, we affirm the Examiner's decisions rejecting
claims 1-5, 7-12, 14--18, and 20.
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(l )(iv). See 37
C.F.R. § 4I.50(f).
AFFIRMED
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