Ex Parte Yang

Patent Trial and Appeal Board

Feb 27, 2017

12508924 (P.T.A.B. Feb. 27, 2017)

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.
12/508,924 07/24/2009 Guang YANG P2789US00 8944
11764 7590
Ditthavong & Steiner, P.C.
44 Canal Center Plaza
Suite 322
Alexandria, VA 22314
EXAMINER
TSUI, WILSON W
ART UNIT PAPER NUMBER
2178
NOTIFICATION DATE DELIVERY MODE
03/01/2017 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):
docket@dcpatent.com
Nokia. IPR @ nokia. com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte GUANG YANG
Appeal 2016-000281
Application 12/508,924
Technology Center 2100
Before ERIC B. CHEN, MICHAEL M. BARRY, and
MICHAEL J. ENGLE, Administrative Patent Judges.
CHEN, Administrative Patent Judge.
DECISION ON APPEAL
Appeal 2016-000281
Application 12/508,924
This is an appeal under 35 U.S.C. § 134(a) from the final rejection of
claims 1—4, 7—11, 14—18, and 21—26. Claims 5, 6, 12, 13, 19, and 20 have
been cancelled. We have jurisdiction under 35 U.S.C. § 6(b). We affirm.
STATEMENT OF THE CASE
Appellant’s invention relates to modeling browsing, including
collecting data corresponding to navigating a page of a browser application
and predicting an area within the page or another page of the browser, based
on such collected data.
Claim 1 is exemplary, with the disputed limitations in italics:
1. A method comprising:
collecting data corresponding to navigation behavior relating to
navigating a page of a browser application;
initiating storing of the data;
generating a model, based on the stored data, to predict an
area within the page or another page of the browser application;
executing the model to predict the area within the page or
another page;
generating a presentation of a shortcut to the area within the
page or another page; and
initiating presenting of the shortcut upon navigating to the page
or the another page, wherein the model is updated periodically or
when a predetermined threshold amount of the data is collected.
Claims 1, 2, 7—9, 14—16, and 21—26 stand rejected under 35 U.S.C.
§ 103(a) as unpatentable over Denoue (US 2005/0071864 Al; Mar. 31,
2005), Priogin (US 2005/0177414 Al; Aug. 11, 2005), and Beckman
(US 7,859,539 B2; Dec. 28, 2010).
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Claims 3, 4, 10, 11, 17, and 18 stand rejected under 35 U.S.C.
§ 103(a) as unpatentable over Denoue, Priogin, Beckman, and Fukuda
(US 7,225,397 B2; May 29, 2007).
ANALYSIS
§103 Rejection—Denoue, Priogin, and Beckman
Claims L 2, 7—9, 14—16, 22, 24, and 26
We are unpersuaded by Appellant’s arguments that the combination
of Denoue, Priogin, and Beckman would not have rendered obvious
independent claim 1 based on the purported failure to teach or suggest the
limitations “generating a model, based on the stored data, to predict an area
within the page or another page of the browser application” and “executing
the model to predict the area within the page or another page.” (App. Br. 7—
8; see also Reply Br. 4—8.)
The Examiner found that the “deformation” of interaction areas of
Denoue in a second representation, based on monitoring past user
interactions in a first representation, corresponds to the limitation
“generating a model, based on the stored data, to predict an area within the
page or another page of the browser application” and “executing the model
to predict the area within the page or another page.” (Ans. 17—18, Adv.
Act. 2; see also Final Act. 3 4.) We agree with the Examiner.
Denoue relates to “rendering representations of digital content.” (| 6.)
In particular, Denoue explains that “past and current user interaction with a
first representation of digital content can be used to improve presentation
and interaction with a second representation of the same digital content or of
other digital content.” (| 37.) Moreover, Denoue explains that such
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Application 12/508,924
“interaction information can be . . . used to deform a second representation
of digital content” and “[u]ser behavior can also be monitored over periods
of time” (| 42). Figure 5a of Denoue illustrates first representation 502 of
digital content (e.g., a word processing program or a web page), including
“active areas as shown by the boxed lines,” such that “[i]f representation 502
is of a web page, e.g., the active areas may correspond to hyperlinks, text
input fields, or other selectable areas” and “active areas 508<2-508<2 have
been determined to be interaction areas.” (1105.) Figure 5b illustrates
second representation 552, a scaled version of first representation 502, in
which “active interaction areas 558a-d have been expanded relative to the
overall size of the representation.” (| 106.) Because first representation 502
of Denoue is monitored to produce second representation 552 with a
“deformation” or expansion of active interaction areas, an ordinarily skilled
artisan would have understood Denoue teaches the limitations “generating a
model, based on the stored data, to predict an area within the page or another
page of the browser application” and “executing the model to predict the
area within the page or another page.”
Appellant argues that “Denoue’s ‘deforming’ portions of one
page/device on a second page/device is not equivalent to the claimed subject
matter ‘generating a model, based on the stored data, to predict an area
within the page or another page of the browser application’” because
“Denoue does not teach predicting or prediction of an area within the page
or another page” but “instead Denoue . . . deforms a selected area of one
page to, generally, enlarge that selected area on another page (that may be on
another device).” (App. Br. 8; see also Reply Br. 4—6.) However, as found
by the Examiner (Adv. Act. 2), Denoue provides an explanation of
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Application 12/508,924
“monitoring past and current user interaction with representations of digital
content to improve the presentation of and interaction with representations
of digital content,” and accordingly, Denoue predicts which active areas
should be deformed (e.g., interaction areas 558a-d is illustrated in Figure 5b)
in the second representation (see, e.g., 137).
Appellant further argues “[t]he Application discloses several models
that may be use to ‘predict an area within the page or another page of the
browser application’ ... for example Markov Chains, or using a Tree Edit
Distance method to compare Document Object Models (DOM).” (App.
Br. 8; see also Reply Br. 6—8.) However, as found by the Examiner,
Appellant’s arguments are not commensurate in scope with claim 1, because
the claim does not recite Markov Chains or using a Tree Edit Distance
method to compare Document Object Models (DOM). (Ans. 18—19, Adv.
Act. 2.)
Thus, we agree with the Examiner that the combination of Denoue,
Priogin, and Beckman would have rendered obvious independent claim 1,
which includes the limitations “generating a model, based on the stored data,
to predict an area within the page or another page of the browser
application” and “executing the model to predict the area within the page or
another page.”
We are further unpersuaded by Appellant’s arguments that the
Examiner improperly combined Denoue, Priogin, and Beckman. (App.
Br. 8-10.)
The Examiner found that the generation of a new prediction model of
Priogin, which updates data, corresponds to the limitation “wherein the
model is updated periodically or when a predetermined threshold amount of
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Application 12/508,924
the data is collected.” (Final Act. 4; see also Ans. 19—20.) The Examiner
concluded that “[i]t would have been obvious ... to have modified Denoue
et al’s method for updating a navigation based model, such that the model is
updated periodically, as similarly taught by Priogin” and “[t]he combination
would have allowed Denoue to have ‘efficiently updated prediction models
. . . and minimized resource overhead.’” (Final Act. 4; see also Ans. 3 4.)
We agree with the Examiner.
Priogin relates to prediction modeling (| 3), in particular modeling
interactions between various entities (12). Priogin explains that “it would
be preferable to minimize the resource overhead for retaining and executing
such prediction models and their plurality of inputs.” (19.) Priogin explains
that “a new prediction model may be generated when a particular amount of
data has been collected or after a particular time period” and “[i]f a new or
modified prediction model is required, the learning model is pruned to
remove any unnecessary input attributes.” (143.) Accordingly, Priogin
teaches the limitation “wherein the model is updated . . . when a
predetermined threshold amount of the data is collected.”
A person of ordinary skill in the art would have recognized that
incorporating the prediction modeling of Priogin, in which prediction
models are generated after a particular amount of data has been collected
and pruned if a new model is required, with the representations of Denoue
for digital content would, improve Denoue by providing the ability to update
prediction modeling and minimizing resource overhead. See KSR Int 7 Co.
v. Teleflex Inc., 550 U.S. 398, 417 (2007) (“[I]f a technique has been used to
improve one device, and a person of ordinary skill in the art would recognize
that it would improve similar devices in the same way, using the technique is
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obvious unless its actual application is beyond his or her skill.”). Thus, we
agree with the Examiner (Final Act. 4) that modifying Denoue to incorporate
the prediction modeling of Priogin would have been obvious.
Appellant argues that “there would be no motivation or teaching to
modify Denoue in view of Priogin” because
time (time differentials) are irrelevant in Denoue — it doesn’t
matter how much time a user spends in, for example, completing
requested information in one text box over another text box (e.g.,
see FIGS. 7a—7c of Denoue), each text box would be deformed
on a second device to permit viewing and completion of those
text boxes.
(App. Br. 9.) Similarly, Appellant argues that “there is no reason to modify
Denoue with Priogin and further in view of Beckman” because “[a]s
discussed above, Denoue merely deforms a portion of one page for viewing
on another page; any time based factor is irrelevant and any time ranking of
portions to be deformed over another portion to be deformed may defeat the
intention of Denoue.” (Id. at 10.) However, the Examiner cited to Priogin
for teaching the limitation “wherein the model is updated . . . when a
predetermined threshold amount of the data is collected,” which is an
alternative to the limitation “wherein the model is updated periodically.”
(Ans. 19—20; Final Act. 4.) Additionally, contrary to Appellant’s arguments
that “time (time differentials) are irrelevant in Denoue’’ (App. Br. 9) and that
“any time based factor is irrelevant” (id. at 10), Denoue states that “[u]ser
behavior can also be monitored over periods of time” (142).
Therefore, Appellant does not persuade us of error in the Examiner’s
combination of Denoue, Priogin, and Beckman to reject independent claim 1
under 35 U.S.C. § 103(a).
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Accordingly, we sustain the rejection of independent claim 1 under 35
U.S.C. § 103(a). Claims 2 and 7 depend from claim 1, and Appellant has
not presented any additional substantive arguments with respect to these
claims. Therefore, we sustain the rejection of claims 2 and 7 under 35
U.S.C. § 103(a) for the same reasons discussed with respect to independent
claim 1.
Independent claims 8 and 15 recite limitations similar to those
discussed with respect to independent claim 1, and Appellant has not
presented any additional substantive arguments with respect to these claims.
We sustain the rejection of claims 8 and 15, as well as dependent claims 9,
14, 16, 22, 24, and 26, for the same reasons discussed with respect to
claim 1.
Claims 21, 23, and 25
Although Appellant nominally argues the rejection of dependent
claims 21, 23, and 25 separately (App. Br. 11), the arguments presented do
not point out with particularity or explain why the limitations of these
dependent claims are separately patentable. Instead, Appellant merely
reiterates the argument that
time (time differentials) are irrelevant in Denoue — it doesn’t
matter how much time a user spends in, for example, completing
requested information in one text box over another text box (e.g.,
see FIGS. 7a—7c of Denoue), each text box would be deformed
on a second device to permit viewing and completion of those
text boxes.
{Id.) We are not persuaded by these arguments for the reasons discussed
with respect to claims 1, 8, and 15, from which claims 21, 23, and 25
depend. Accordingly, we sustain this rejection.
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Appeal 2016-000281
Application 12/508,924
§103 Rejection—Denoue, Priogin, Beckman, and Fukuda
Although Appellant nominally argues the rejection of dependent
claims 3,4, 10, 11, 17, and 18 separately (App. Br. 13), the arguments
presented do not point out with particularity or explain why the limitations
of theses dependent claims are separately patentable. Instead, Appellant
merely reiterates the argument that “Fukuda fails to overcome the
deficiencies set forth above with respect to Denoue, Priogin and Beckman
{Id.) We are not persuaded by these arguments for the reasons discussed
with respect to claims 1, 8, and 15, from which claims 3, 4, 10, 11, 17, and
18 depend. Accordingly, we sustain this rejection.
DECISION
The Examiner’s decision rejecting claims 1—4, 7—11, 14—18, and 21—
26 is affirmed.
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).
AFFIRMED
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