Ex Parte Brownholtz et al

Patent Trials and Appeals Board

Mar 15, 2019

11967637 - (D) (P.T.A.B. Mar. 15, 2019)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR
11/967,637 12/31/2007 Elizabeth A. Brownholtz
46321 7590 03/19/2019
Shutts & Bowen LLP
STEVEN M. GREENBERG
525 Okeechobee Blvd
# 1100
West Palm Beach, FL 33401
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.
CAM920070146US1 (198) 7375
EXAMINER
HEFFINGTON, JOHN M
ART UNIT PAPER NUMBER
2177
NOTIFICATION DATE DELIVERY MODE
03/19/2019 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):
docketing@crgolaw.com
sgreenberg@shutts.com
aschneider@shutts.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte ELIZABETH A. BROWNHOL TZ, CASEY DUGAN,
WERNER GEYER, MICHAEL MULLER,
and JIANQIANG SHEN 1
Appeal2017-009987
Application 11/967,637
Technology Center 2100
Before ERIC B. GRIMES, KENNETH G. SCHOPPER, and
KRISTI L. R. SA WERT Administrative Patent Judges.
GRIMES, Administrative Patent Judge.
DECISION ON APPEAL
This is an appeal under 35 U.S.C. § 134 involving claims related to a
method for recommending computer resources based on a user's activity,
which have been rejected as anticipated or obvious. We have jurisdiction
under 35 U.S.C. § 6(b ).
We affirm-in-part.
1 Appellants identify the Real Party in Interest as International Business
Machines Corporation. Appeal Br. 2.
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Application 11/967,637
STATEMENT OF THE CASE
Appellants' "invention relates to automated content discovery and
search engine use in a computer communications network and more
particularly to context-sensitive resource recommendation." Spec. ,r 1.
Claims 1-19 are on appeal. Claims 1 and 2 are illustrative and read as
follows:
1. An activity-centric resource recommendation method comprising:
retrieving into memory of a computer contextual data provided by
different graphical user interface elements disposed within a workspace in a
graphical user interface;
inferring an activity based upon deduction from the retrieved
contextual data provided by different graphical user interface elements
disposed within the workspace in the graphical user interface;
identifying resources from amongst a set of resources that are relevant
to the inferred activity; and,
displaying the identified resources in the graphical user interface.
2. The method of claim 1, wherein inferring an activity from a
workspace in a graphical user interface, comprises:
training a Bayesian predictor with words known to appear in
connection with different activities;
monitoring active windows in the workspace to extract window titles
from the active windows and to place the window titles in a finite queue;
and,
providing the titles in the finite queue to the Bayesian predictor to
compute a probability set of activities for the window titles.
Appeal Br. 8-9 (Claims Appendix).
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The claims stand rejected as follows:
Claims 1, 10, and 11 under 35 U.S.C. § 102(e) as anticipated based on
Macbeth2 (Final Action3 4);
Claims 2, 3, 12, and 13 under 35 U.S.C. § 103(a) as obvious based on
Macbeth and Friedlander4 (Final Action 1 O);
Claims 4--7 and 14--17 under 35 U.S.C. § 103(a) as obvious based on
Macbeth, Friedlander, and Ramer5 (Final Action 14 );
Claims 8 and 18 under 35 U.S.C. § 103(a) as obvious based on
Macbeth, Friedlander, and Bates6 (Final Action 18);
Claims 9 and 19 under 35 U.S.C. § 103(a) as obvious based on
Macbeth, Friedlander, and Bayesway 7 (Final Action 20).
I
The Examiner has rejected claims 1, 10, and 11 as anticipated based
on Macbeth. Appellants present no arguments directed to the rejection of
claims 1, 10, and 11. Because Appellants have waived arguments directed to
claims 1, 10, and 11, we affirm the rejection under 35 U.S.C. § 102(e). See
37 C.F.R. § 4I.37(c)(l)(iv); Hyatt v. Dudas, 551 F.3d 1307, 1314 (Fed. Cir.
2008) ("When the appellant fails to contest a ground of rejection to the
Board, ... the Board may treat any argument with respect to that ground of
2 Macbeth et al., US 2007/0300185 Al, published December 27, 2007.
3 Office Action mailed April 20, 2016.
4 US 2007/0300179 Al, published December 27, 2007.
5 Ramer et al., US 2007/0060109 Al, published March 15, 2007.
6 Bates et al., US 6,184,883 Bl, issued February 6, 2001.
7 www.princeton.edu/-bayesway/probthink/ch1part2.htm, last December 9,
2010.
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Application 11/967,637
rejection as waived. In the event of such a waiver, the PTO may affirm the
rejection of the group of claims that the examiner rejected on that ground
without considering the merits of those rejections.").
Similarly, Appellants do not present any arguments directed to the
rejections of claims 3, 13, 18, and 19 (which depend directly from either
claim 1 or claim 11) under 35 U.S.C. § 103(a). We therefore affirm the
rejection of claims 3 and 13 under 35 U.S.C. § 103(a) based on Macbeth and
Friedlander; the rejection of claim 18 under 35 U.S.C. § 103(a) based on
Macbeth, Friedlander, and Bates; and the rejection of claim 19 under 35
U.S.C. § 103(a) based on Macbeth, Friedlander, and Bayesway.
II
The Examiner has rejected claims 2, 3, 12, and 13 as obvious based on
Macbeth and Friedlander. As noted above, Appellants' arguments with
respect to this rejection are limited to claims 2 and 12 (see, e.g., Appeal Br.
7), so we will limit our discussion of this rejection to those claims.
The Examiner finds that Macbeth discloses all the limitations of claim
1, and also discloses the limitations of claim 2 requiring "training a Bayesian
predictor with words known to appear in connection with different
activities" and "monitoring active windows in the workspace to extract
window titles from the active windows." Final Action 10-11.
The Examiner finds that Macbeth does not "disclose placing the
window titles in a finite queue, and providing the titles in the finite queue to
the Bayesian predictor to compute a probability set of activities for the
window titles." Id. at 11. The Examiner finds, however, that Friedlander
does teach these limitations, and concludes that
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Application 11/967,637
it would have been obvious ... to add placing the window titles
in a finite queue, and providing the titles in the finite queue to
the Bayesian predictor to compute a probability set of activities
for the window titles to the teachings of Mac[b Jeth ... in order
to facilitate retrieval of application widow(s) [sic] (by using
stored window identifier(s)) (Friedlander: Paragraph 0063).
Id. at 12.
Appellants argue that the "Examiner does not indicate that the
Bayesian network of paragraph [0100] ofMac[b]eth is trained with words
known to appear in connection with different activities." Appeal Br. 5.
Appellants also argue that "there is no mention of any Bayesian predictor" in
Friedlander, and "[t]herefore, it is not possible that Friedlander teaches the
receipt in a Bayesian predictor of titles that are present in a finite queue."
Id. at 6. Appellants conclude that "Mac[b]eth and Friedlander to [sic] not in
combination account for all claimed limitations present in claims 2 and 12."
Id. at 7. 8
We agree with Appellants that the Examiner has not shown that the
inventions of claims 2 and 12 would have been obvious to a person of
ordinary skill in the art based on Macbeth and Friedlander. As noted above,
the Examiner finds that Macbeth does not disclose placing window titles in a
queue and providing the titles to a Bayesian predictor to compute a
probability set of activities for the window titles. Final Action 11. The
Examiner relies on Friedlander to teach these limitations and to provide a
reason for modifying Macbeth's method to include them "in order to
8 Claim 2 is reproduced above. Claim 12 is directed to a computer program
product that comprises computer usable program code for carrying out the
steps recited in claim 2.
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Application 11/967,637
facilitate retrieval of application widow( s) [sic] (by using stored window
identifier(s))." Id. at 12.
However, Macbeth states that its invention "comprises a system for
dynamically changing the user interface (UI) of a system level shell
('desktop'), of applications, and of standalone UI parts ('gadgets' or
'widgets'), based upon a current ( or future) activity of the user and other
context data." Macbeth ,r 9. Macbeth states that "preprogrammed and/or
inferred rules can be used to decide how to adapt the UI based upon the
activity." Id. ,r 10.
Macbeth states that its system can include "an adaptive UI Machine
learning and reasoning (MLR) component 1202 that can be employed to
infer on behalf of a user" and "can produce (and/or update) a new set of
learned rules 1204." Id. ,r 97. Macbeth also states that "a process for
determining implicit feedback can be facilitated via an automatic classifier
system and process." Id. ,r 98. "A support vector machine (SVM) is an
example of a classifier that can be employed .... Other directed and
undirected model classification approaches ... [ such as] Bayesian networks
and other probabilistic classification models providing different patterns of
independence can be employed." Id. ,r 100.
Thus, Macbeth discloses that Bayesian networks are one type of
approach that a classifier can use to determine implicit feedback in a UI
machine learning and reasoning component to adapt the UI based on a user's
activity. In addition, the passages of Macbeth cited by the Examiner describe
metadata and Bayesian networks but, contrary to the Examiner's findings
(Final Action 10-11 ), they do not describe training a Bayesian predictor
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with words that appear in connection with different activities or extracting
window titles from active windows in a workspace.
Friedlander discloses "a method for recording user/application
interaction." Friedlander ,r 39. "The method may include intercepting, by a
user/application monitoring agent, a foreground application window running
on a computer and currently being visited by a user, and generating a unique
window identifier." Id.
The unique window identifier can be generated based on a structural
element, such as a label, of a window. Id. "The unique window identifier
may be a hash value obtained by hashing data representing structural
elements of the related application window." Id. ,r 40.
Friedlander states that "[u]nique window identifier(s) may be utilized
in visual audit trail, troubleshooting, guidance, help or assistance associated
with a running application." Id. In addition, "[s]creenshots of application
windows respectively associated with unique window identifiers may be
recorded and later played to a user, upon the user's demand, as video clip(s)
or screenshots slides, by using window identifiers to respectively retrieve
stored screenshots." Id. ,r 41.
Thus, while Friedlander states that stored window identifiers can
facilitate retrieval of application windows (id. ,r 63), the window identifiers
are not described as the window titles themselves, but as hash values
obtained by hashing data representing structural elements ( such as labels) of
windows. The Examiner's finding that Friedlander discloses placing window
titles in a finite queue is therefore not supported by the cited evidence.
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In addition, the Examiner's reason for combining the cited references
does not adequately support the conclusion that the inventions of claims 2
and 12 would have been obvious to a person of ordinary skill in the art.
Specifically, the Examiner has not persuasively explained the nexus between
"placing the window titles in a finite queue, and providing the titles in the
finite queue to the Bayesian predictor" of Macbeth, on the one hand, and
"facilitat[ing] retrieval of application widow(s) [sic] (by using stored
window identifier(s))," on the other. See Final Action 12.
In summary, we agree with Appellants that the Examiner has not
shown that the inventions of claims 2 and 12 would have been prima facie
obvious based on Macbeth and Friedlander.
The Examiner rejected claims 4--9 and 14--17 as obvious based on
Macbeth and Friedlander, further combined with one of Ramer, Bates, or
Bayesway. Each of claims 4--9 and 14--17 depends from either claim 2 or
claim 12. Therefore, we reverse the rejections of claims 4--9 and 14--1 7
under 35 U.S.C. § 103(a) for the reasons discussed above.
SUMMARY
We affirm the rejection of claims 1, 10, and 11 under 35 U.S.C.
§ 102( e) based on Macbeth. We also affirm the rejection of claims 3 and 13
under 35 U.S.C. § 103(a) based on Macbeth and Friedlander; the rejection of
claim 18 under 35 U.S.C. § 103(a) based on Macbeth, Friedlander, and
Bates; and the rejection of claim 19 under 35 U.S.C. § 103(a) based on
Macbeth, Friedlander, and Bayesway.
We reverse the rejection of claims 2 and 12 under 35 U.S.C. § 103(a)
based on Macbeth and Friedlander, the rejection of claims 4--7 and 14--17
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under 35 U.S.C. § I03(a) based on Macbeth, Friedlander, and Ramer; the
rejection of claim 8 under 35 U.S.C. § I03(a) as obvious based on Macbeth,
Friedlander, and Bates; and the rejection of claim 9 under 35 U.S.C. § I03(a)
as obvious based on Macbeth, Friedlander, and Bayesway.
TIME PERIOD FOR RESPONSE
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.I36(a).
AFFIRMED-IN-PART
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