Ex Parte Smith et al

Patent Trial and Appeal Board

Nov 25, 2013

11236869 (P.T.A.B. Nov. 25, 2013)

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.
11/236,869 09/28/2005 Adam D. Smith 0026-0164 4567
44989 7590 11/26/2013
HARRITY & HARRITY, LLP
11350 Random Hills Road
SUITE 600
FAIRFAX, VA 22030
EXAMINER
FAN, HUA
ART UNIT PAPER NUMBER
2456
MAIL DATE DELIVERY MODE
11/26/2013 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 ADAM D. SMITH, BRIAN SINGERMAN, and
NAGA SRIDHAR KATARU
____________

Appeal 2011-007140
Application 11/236,869
Technology Center 2400
____________

Before KARL D. EASTHOM, RICHARD E. RICE, and
SCOTT E. KAMHOLZ, Administrative Patent Judges.

EASTHOM, Administrative Patent Judge.

DECISION ON APPEAL
Appellants appeal under 35 U.S.C. § 134 from the Examiner’s
decision to reject claims 1-7 and 9-34. Claim 8 has been cancelled. See
App. Br. 5. We have jurisdiction under 35 U.S.C. § 6(b).
We affirm.
Appeal 2011-007140
Application 11/236,869

2
STATEMENT OF THE CASE
Background
The Specification describes a search term notification system. Users
may register to receive “alerts,” via email, or otherwise. See Spec., ¶ 23.
The alerts may include documents or links to documents that relate to search
terms selected by the user when registering for the alert. Id. Topical alerts
generated by a topical subject generator can be used to enhance the online
experience for the user. See id. at ¶¶ 42-43. The display, or output, of a
search term, may constitute an alert. See id. at Fig. 7A, ¶ 39.
Claim 1 requires “alerts,” while claim 2 requires “email alerts.”
Claim 1 (with the alert phrases highlighted) follows:
1. A method performed by one or more server devices, the method
comprising:

receiving, by one or more processors of the one or more server
devices, a registration request to transmit alerts to a user device, where
receiving the registration request includes:

receiving one or more search terms entered by a user of the user
device;
and receiving an indication of types of documents to be
searched to generate the alerts;

storing, by the one or more processors of the one or more server
devices, the received registration request, in a memory associated with the
one or more server devices;

identifying, by the one or more processors of the one or more server
devices, a plurality of search terms that were registered in a predetermined
time frame from multiple user devices;

identifying, by the one or more processors of the one or more server
devices, one or more of the plurality of search terms that were registered
Appeal 2011-007140
Application 11/236,869

3
more than a threshold number of times;

identifying, by the one or more processors of the one or more server
devices, topical subjects based on the one or more of the plurality of search
terms that were registered more than a threshold number of times; and
providing, by a communication interface of the one or more server
devices, an alert corresponding to the received registration and one or more
of the identified topical subjects to the user device.
The following rejections are on appeal:
claims 1, 7, 9-23, 28, 30, 31, and 34, rejected under 35 U.S.C.
§ 102(e) as anticipated by Yoo, U.S. Patent No. 7,146,416 B1;
claim 6, rejected under 35 U.S.C. § 103(a) as obvious based on Yoo
and the Examiner’s Official Notice; and
claims 2-5, 24-27, 29, 32, and 33, rejected under 35 U.S.C.
§ 103(a) as obvious based on Yoo and Faudman, U.S. Pub. No.
2002/0138485 A1.
1

The Specification
Most of the claims on appeal recite “alerts,” in some fashion. For
example, as highlighted supra, claim 1 recites “receiving . . . a registration
request to transmit alerts,” and “providing . . . an alert corresponding to the
received registration.” According to the Specification, users can “enter alert
search terms that define topics in which the user is currently interested.”
Spec. ¶ 19 (emphasis added). In response, “[t]he alerts provided by alert
engine 130 may include, for example, documents or links to documents that
relate to search terms selected by the user when registering for the alert.” Id.

1
The Examiner also relies on Official Notice to reject claims 4 and 33 as
obvious over Yoo and Faudman.
Appeal 2011-007140
Application 11/236,869

4
at ¶ 23. The Specification describes identifying topical subjects based on the
number of users registering an alert search term:
For example, if an unusually large number of users register the
search terms ‘Colin Farrell,’ the alert provider may infer that
this actor is currently of particular interest to users. The alert
provider may use this information to enhance the online
experience of its users, such as by, for example, suggesting that
a user may be interested in receiving alerts about ‘Colin Ferrell’
or by more prominently featuring news articles about Colin
Ferrell on its web site.
Id. at ¶ 19.
A “topical” alert refers to a search term that has a predetermined level
of popularity, for example, “‘Westminster Dog Show’ and ‘Identify Theft’
may be output as topical alerts.” Id. at ¶ 39. “The alerts that are determined
to be topical . . . by topical subject generator 135 may be used by alert
engine 130, search engine 120, or by other processes, to enhance the user’s
online experience.” Id. at ¶ 41. “For example, the topical alerts may be
displayed to users on a web page as topics that are currently popular,
presented to users as possible alerts that they may be interested in receiving,
or used to assist in ranking search results of search engine 120.” Id.
The Specification and claims interchangeably refer to “registering” or
“entering” an “alert,” an “alert search term,” or simply a “search term,” as
the action that initiates a response by the system to an entered search term
(and possibly to other information entered with the search term during
registration). The action allows the system to “provide the alert,” in the
form of a display of information about the search term, including the results
of a search. See, e.g., Spec. ¶¶ 18-19, 23, 31, 35-36; claims 1, 13. Results
may include the number of search term hit counts, or “number of alerts.” See
Spec. Figs. 7A, 7B, ¶¶ 38-39.
Appeal 2011-007140
Application 11/236,869

5
Yoo (FF)
2

Yoo’s system counts search terms over certain time periods, and
aggregates them into categories of like search terms. See Abstract, col. 1,
ll. 66-67; col. 8, ll. 1-25; col. 16, ll. 47-48 (“incrementing [a count] every
time a user causes an event”). The system also calculates a “buzz value . . .
as the number of unique users searching for that subject.” Col. 14, ll. 9-11.
Using the counts, the system tracks a “baseline value [that] can be defined as
the average of the value for a previous period.” Col. 11, ll. 40-41.
Comparing to a baseline of a previous time period, the system merges
groups of similar search terms to form categories of terms, using a
“canonicalization” technique. Col. 11, ll. 25-27; Fig. 6. To merge a term
into a category, it must be above the baseline, or average number of hit
counts, by a certain amount. If “the value of the term being merged is within
some margin, such as 20% of its baseline,” it is not merged with another
term, because that would mean there is not much interest in that term. Col.
11, ll. 49-51.
In other words, the system merges similar terms that have rapid rises
over a certain time frame. For example, the term “U.S. Open” might be
merged with “U.S. Open Golf,” but not “U.S. Open Tennis,” if the former
two terms experience a rapid rise over a set time period, but the latter term
does not. Col. 11, ll. 59-67. Terms falling below the baseline are binned or
counted separately, rather than together in a merged group. Col. 11, l. 65 –
col. 12, l. 8. In essence, the canonicalizer can “respond to . . . change[s]
over time. . . . [and make use of] the buzz values for terms that reflect actual

2
Fact findings are not limited to this section; however, the abbreviation
“FF” hereinafter refers to facts found in this section.
Appeal 2011-007140
Application 11/236,869

6
user interests . . . to determine which topics/terms to merge and when.” Col.
12, ll. 8-14.
Figure 6 represents a flow diagram that corresponds to Yoo’s
canonicalization process. It shows, as described above, that searches are
performed and compared to baseline values, which are a function of hit
counts, i.e., the number of users searching for a search term or category. For
example, Figure 6 depicts the following sequence: “Determine Baseline
Value for New Terms,” then “Pick a Term to be Merged,” then “Is Value
within Range of Baseline,” if “No,” then “Merge Portion of Term over
Baseline to Canonical Term.” Fig. 6.
After the system tracks users’ search terms and counts and merges
them, see, e.g., id., the system generates a “buzz” report that shows, inter
alia, popular search terms based on the counts. “Buzz report users can
easily determine, for a particular demographic or overall, what types or
search terms get more attention and where the spikes in attention occur over
time.” Col. 15, ll. 42-45 (emphasis added). Buzz values can show
demographics about “users searching for a particular search term.” Col. 15,
l. 37-38.
In several examples of a “buzz report,” a user visits a web site and
enters search terms that are counted and binned according to the relative
number of counts. See Figures 9-11. The website page buzz report depicted
in Figure 10 lists top categories based on inputs by users. See Fig. 10, col.
15, ll. 21-23. Figure 11 shows a similar buzz report “where the buzz for
terms is plotted over time and relative to other terms in a category.” Col. 15,
ll. 23-25.

Appeal 2011-007140
Application 11/236,869

7
The web site buzz report example of Figure 9 follows:

Figure 9, above, shows top overall categories and top subcategories
within specific categories (movie, music, sports), “Ranked by Change –
Daily,” in terms of hit counts, and sorted by percent change relative to that
term or subcategory as counted on the previous day. “That example page [of
Figure 9] is responsive to a request for top buzz values for overall events and
events specific to the categories of movies, music, and sports.” Col. 13,
ll. 41-43. “For each section of the report, the report shows three top few
topics/terms that generate the most counts, in order of number of counts,
Appeal 2011-007140
Application 11/236,869

8
along with an indication of relative changes in buzz values.” Col. 15, ll. 10-
12. Figure 9 also depicts related links for each buzz word, including “News,
Categories, Sites.” The search button at the top of Figure 9 (and other
figures) indicates, in line with passages quoted supra and infra, that users
can obtain search results for any entered word or phrase, including a popular
search term.
In other words, users generally can obtain a search report, including a
buzz ranking, about a search term or a popular search term or topic: “[A]
buzz report generator generates buzz reports on the fly based on requests
from the buzz report generator users.” Col. 15, ll. 45-47. Users can generate
a buzz report by “issu[ing] a statistical query related to a buzz.” Col. 13,
ll. 27-28. In response to the query, the system delivers a web buzz report
page: “An example of such a delivered page is shown in FIG. 9.” Col. 13,
ll. 39-40.
“Buzz values can be presented [in a display] in various sort orders
such as a buzz score or by the % change in buzz for a specified period.”
Col. 15, ll. 39-41 (emphasis added). “In one variation, the buzz value
associated with a particular term or category is the number of users
searching with that term . . . .” Col. 14, ll. 23 -27.
The system monitors searched terms and specific users by “usage logs
generated by a Web site’s servers,” col. 13, ll. 57-59, including with the use
of unique cookies:
As shown, the categorizer would extract the search word events
(user ID, timestamp, search words) from search logs. The user
ID can be implemented as a unique cookie stored in the user’s
Web browser that is sent to the search engine and Web page
server with each request and is stored in the logs.
Col. 10, ll. 34-36.
Appeal 2011-007140
Application 11/236,869

9
The system uses the log information and similar information to
categorize terms based on the type of pages viewed that are relevant to a
specific search term. Using that log and page information, “[w]here the
search is being tracked for buzz evaluation or other counting evaluation, the
category count is incremented.” Col. 10, ll. 47-49. As noted supra, the user
information may also be used for other types of data evaluation, including
demographics of users who enter search terms.
ANALYSIS
A. Claims 1, 7, 9-23, 28, 30, 31, and 34 – Yoo, Anticipation
Appellants assert that the Examiner fails to show anticipation by Yoo
of the above-listed claims. See App. Br. 13, 33. With respect to claims 1, 7,
and 9-12, Appellants focus on claim 1, which therefore, represents these
claims on appeal. See id. at 13, 16. With respect to claims 13, 17-19, and
34, Appellants focus on claim 13, which is selected as representative of
these claims. See id. at 17, 21. With respect to claims 14 and 15, Appellants
focus on claim 14, which is representative of the two claims. App. Br. 21-
23. Similarly, with respect to the group of claims 20 and 23 and the group
of claims 21 and 22, Appellants focus on claims 20 and 21, respectively,
each of which we treat as representative of its group. See id. at 24, 27, 29.
Claim 1:
Claim 1 calls for, inter alia, “a registration request to transmit alerts”
and “providing . . . an alert.” The Examiner interprets the term “alert”
consistent with this use of the term in the Specification: “broadly construed
as . . . presenting/displaying search results on a user interface.” See Ans. 4-
5. Appellants point to their Specification to show an “example of an alert”
in the form of an email. App. Br. 13 (citing Spec. ¶ 19). Appellants assert
Appeal 2011-007140
Application 11/236,869

10
that the Examiner “relies on Fig. 6 and col. 11, lines 1-39 of Yoo as
allegedly disclosing this feature of claim 1.” Id. Appellants conclude,
without persuasive explanation, that Yoo does not disclose “the above
feature [and others] of claim 1.”
Claim 1 does not recite an email alert, and the Examiner does not rely
solely on Figure 6 to show alerts. Rather, the Examiner finds that Yoo’s
Figures 8 and 11 describe a “buzz” report alert. See Ans. 6, 19. For
example, the Examiner refers to “figure 8, [Extract Buzz Data for]
‘Particular Report’,” id. at 6, refers to “presenting/displaying search results
on a user interface,” id. at 4, and also refers to “‘web pages’: figure 11. See
examiner’s interpretation for ‘alerts’ in the first limitation,” id. Figure 8
points to generic buzz reports, including those depicted in Figures 9-14. The
presentation of this buzz report data on a web page, along with search
results, reasonably corresponds to “providing . . . an alert corresponding to
the received registration” about different search terms. See FF (see note 2).
Appellants fail to address the Examiner’s findings related to the web
page alerts of Figures 8 and 11. Appellants do not clarify the Examiner’s
interpretation of “alert” or present a countervailing definition. Appellants’
reference to an “email alert” as an example of an alert does not amount to a
definition of the claim term. In addition to Appellants’ characterization of
an email alert as a mere example, because claim 2 specifies that “the alerts
include email alerts,” this further implies that the term “alert” in claim 1 is
not so limited. For these reasons, the Examiner’s interpretation is reasonable
and consistent with the Specification. See In re Morris, 127 F.3d 1048, 1056
(Fed. Cir. 1997) (“It is the applicant’s burden to precisely define their
invention, not the PTO’s.”).
Appeal 2011-007140
Application 11/236,869

11
Appellants also argue that Yoo does not disclose the phrase,
“identifying . . . topical subjects based on one or more of the plurality of
search terms that were registered more than a threshold number of times, as
recited in claim 1.” App. Br. 13. Appellants point to other “identifying”
clauses, and related clauses, in claim 1 in the various arguments. See id. at
13-14.
These arguments appear to relate partially, at least, to the claim 1
phrase, “receiving . . . a registration request to transmit alerts,” and the
related phrases in claim 1 that define a “registration request.” The Examiner
refers to “‘the registration request’ [as including] a user entering search
terms and indicat[ing the] . . . types of documents to be searched to generate
alerts.” Ans. 5. The Examiner also describes “logged” search terms (e.g.,
“local weather”) in Yoo as part of user requests, noting that Yoo’s system
logs user information: “‘the user’s client’s IP address ... browser type, client
type, [and] network type.’” See id. (quoting Yoo, col. 7, ll. 17-18). This
logging of search term data and other user data, which ultimately results in
buzz report alerts, corresponds to “receiving . . . a registration request.”
That is, the system logs, or registers, search terms, with user ID data,
for example, demographic data, to create the registered search term alerts.
See FF, Fig. 6, Fig. 11. For example, Yoo’s system tracks demographically
related, or generically related, user buzz data, FF, showing that it tracks what
the Specification refers to as an “alert search term.” Appellants do not
address, with requisite specificity, the thrust of the Examiner’s findings
related to the “registration request” recited in claim 1.
As to the “identifying” clauses in claim 1, Appellants acknowledge
that Yoo “‘merge[s] similar-appearing terms that both have rapid rises [in
Appeal 2011-007140
Application 11/236,869

12
interest] at the same time, since they probably relate to the same concept or
topic.’” App. Br. 14 (quoting Yoo at col. 11, ll. 55-58) (second bracket set
by Appellants). Nonetheless, Appellants assert that “Fig. 6 of YOO et al.
does not disclose or suggest identifying topical subjects based on search
terms that were registered (for transmission of alerts) more than a threshold
number of times.” Id. Appellants repeat similar arguments that appear to
focus on the alleged lack, in Yoo, of what Appellants refer to as “registering
search terms for the transmission of alerts,” which is not claimed explicitly,
and “a threshold number of times,” which is claimed. Id. at 15. According
to Appellants, a threshold, as claimed, “deals with an absolute number,” but
Yoo’s rapid rise in interest “deals with a change in interest.” Id.
These and related arguments refer partially to an asserted lack in Yoo
of registering requests to transmit alerts—the arguments as addressed supra.
As to the other clauses, “registered in a predetermined time frame,” and
“registered more than a threshold number of times,” the Examiner generally
explains that Yoo’s system creates the buzz reports by merging like terms,
over certain time frames, using, inter alia, Yoo’s canonicalization and
categorization process, which groups and counts like search terms by
comparing counts in one time period to a previous baseline count. See Ans.
4-6; FF; Yoo, Figs. 6, 8, 11.
For example, the Examiner finds that Yoo’s system aggregates the
search term data to generate Yoo’s baseline and buzz data, and reasons that
Yoo’s baselines correspond to the claimed threshold comparisons. See
Ans. 5 (“figure 6, ‘Is Value within Range of Baseline?’ where ‘Baseline’ is a
threshold[.] The answer ‘No’ is equivalent to ‘more than a threshold number
Appeal 2011-007140
Application 11/236,869

13
of times’.”) The Examiner relies partially on a canonicalization or merging
process involving like search terms “Concord” and “Concorde.” Id. at 5-6.
Contrary to Appellants’ arguments, see Reply Br. 4, merging
“Concorde” into the search term group “Concord” is based on a previously
defined, time-based threshold, or baseline, for “Concorde.” See Yoo,
col. 11, ll. 33-45. As the Examiner finds, this canonicalization process
constitutes “identifying . . . topical subjects [Concord] based on the one or
more . . . search terms [Concorde or Concord] that were registered more than
a threshold number of times,” and in a “predetermined time frame,” as claim
1 requires. See Ans. 5-6.
In addition, the Examiner ties Yoo’s categorization and
canonicalization process to threshold determinations implicit in the buzz
reports. See Ans. 5-6. For example, the Examiner refers to the system
output that occurs after the categorization and canonicalization process in
Yoo’s Figure 8, i.e., a “‘Particular Report’ is generated by extracting ‘Buzz’
Data corresponding to Canonicalized events.” Ans. 6 (Examiner citing to
Figure 8). The Examiner also refers to Figure 11 and to “col. 15, lines 40-
65, buzz words generator to determine ‘what topics or search terms get more
attention and where the spikes in attention occur in time.’” Ans. 6 (quoting
Yoo). According further to the cited column 15 of Yoo, “[b]uzz values can
be presented in various sort orders such as ‘buzz score’ or by the ‘% change
in buzz’ for a specified period.” Yoo, col. 15, ll. 39-41.
The passages cited by the Examiner refer to the previously discussed
buzz reports at column 15—i.e., Figures 9-12. Figure 8 shows that Yoo’s
buzz report output (e.g., Figure 11) involves the categorization and
canonicalization of search terms generated from “Server Logs” and “Search
Appeal 2011-007140
Application 11/236,869

14
Logs.” Figure 11, like Figure 9 (reproduced supra), displays topical or
popular search terms as alerts, and includes threshold or baseline data.
In other words, a change in interest that the buzz reports generate
amounts to a change over a threshold, for the several reasons identified by
the Examiner, contrary to Appellants’ argument. In essence, Yoo’s web
page buzz report alerts include time-based buzz data (i.e., hourly, daily, etc.)
created by merging search term data that also uses time-based threshold
(baseline) data. See FF. Merging (canonicalizing) like terms to create the
reports, or simply displaying the top categories in terms of buzz values in the
various reports, corresponds to identifying search terms and topical subjects
registered in a predetermined time frame and more than a threshold number
of times, as claim 1 requires. See Figs. 9, 11 (showing top categories).
Stated differently, the time-based counts over certain thresholds
underlying the displayed buzz data in Figures 9-11 correspond to “one or
more search terms that were registered more than a threshold number of
times,” “in a predetermined time frame,” and “topical subjects based on the .
. . search terms,” as claim 1 recites. See Ans. 6; FF. As a specific buzz
report example, Figure 11 shows “Top Buzz Words for car rental,” using
daily or weekly views. The buzz values represent a simple count, over a
day, or week, of the terms or similar terms in a particular category or
subcategory, as compared to changes over a previous day or week. See FF,
Fig. 11. Displaying and ranking the top ten topics or terms, see Yoo Fig. 11,
implicitly identifies the “one or more search terms,” and “topical subjects,”
based on those terms and hit counts, as claimed—relative to the
predetermined time frame and threshold number—by comparing each
Appeal 2011-007140
Application 11/236,869

15
subcategory hit count to a threshold that is defined by less popular
(undepicted) car rental terms.
Therefore, in addition to the canonicalized time frames and baseline
thresholds involved in those determinations that the Examiner relies upon
(see Ans. 6), as the Examiner also generally indicates, comparing buzz
scores for top categories each day, or values to a previous day’s buzz values,
as a percentage change within a category, to see “spikes,” also constitutes
“identifying . . . search terms that were registered in a predetermined time
frame” and “more than a threshold number of times,” and “identifying
topical subjects based on . . . search terms that were registered more than a
threshold number of times.” See FF; Fig. 9, 12A.
Based on the foregoing discussion, Appellants’ arguments fail to show
error in the anticipation rejection of claims 1, 7, and 9-12.
Claim 13:
Appellants’ arguments with respect to claim 13 are similar to those
addressed supra in connection with claim 1. Appellants contend that the
“local weather” example at column 7 of Yoo “has nothing to do with
analyzing alerts that have been registered more than a threshold number of
times in a period.” App. Br. 19. According to Appellants,
even if the search of YOO et al. could reasonably be construed
as corresponding to registering an alert (a point that Appellants
do not concede), YOO et al. does not disclose or suggest
analyzing aggregated searches to locate topics that have been
registered more than a threshold number of times in a time
period.
Id. at 19-20.
Appellants also maintain that “entering a phrase . . . does not disclose or
suggest that the searches or phrases are registered.” Id. at 19.
Appeal 2011-007140
Application 11/236,869

16
Appellants’ arguments fail to distinguish claim 13 from Yoo primarily
for the reasons explained supra in connection with claim 1. For example,
Appellants fail to explain how “aggregating . . . alerts associated with user
devices, each of the alerts including search terms,” as called for in claim 13,
is distinct from analyzing Yoo’s search terms, which have been registered to
create alerts in the form of buzz reports, as explained supra.
Claim 13 recites “aggregating . . . alerts . . . , each of the alerts
including search terms, registered by the users, . . . the users registering the
search terms to receive alerts.” Thus, as expressly specified in claim 13,
alerts include registered search terms. As explained in connection with
claim 1, Yoo’s system analyzes the package of logged data, which includes
user ID data, time stamps, and the search terms, to form the buzz report
alerts. Logging the package of data to create and transmit a buzz report web
page reasonably corresponds to “registering the search terms to receive
alerts.” Appellants’ arguments do not adequately explain why Yoo’s system
does not disclose aggregating alerts that each includes a registered search
term. See In re Morris, 127 F.3d at 1056 (“It is the applicant’s burden to
precisely define their invention, not the PTO’s”).
As discussed supra, the Examiner relies on the buzz report, which
includes alerts, at Figure 11. Ans. 7, 8. Yoo’s system analyzes aggregated
logged search terms that are registered to receive alerts. The system also
canonicalizes or merges the (alert) search terms above certain thresholds
over a given time period, and then, compares the aggregated search term
alerts to further create ranked categories. See FF.
Appeal 2011-007140
Application 11/236,869

17
Appellants’ arguments, which generally assert that Yoo fails to
register terms more than a threshold number of times in a time period,
follow:
In connection with Fig. 6, YOO et al. discloses that “it is
possible and desirable to merge similar-appearing terms that
both have rapid rises [in interest], since they most probably
relate to the same concept or topic” (see, for example, column
11, lines 55-58 of YOO et al.). Fig. 6 of YOO et al. deals with
“merg[ing] similar-appearing terms” and has nothing to do with
locating topics that have been registered more than a threshold
number of times in a time period. In fact, merging “similar-
appearing terms that both have rapid rises [in interest]” is
simply a different function with a different result from locating
topics that have been registered more than a threshold number
of times in a time period.
Reply Br. 7 (quoting Yoo).
These varied arguments are similar to the arguments addressed supra
and fail to show Examiner error. As found by the Examiner, Yoo’s system
logs and aggregates search terms tied to unique users “in various stages such
as in the data collection stage” to create ranked categories. Ans. 7. In one
stage, the canonicalizer aggregates related alert terms that show a rapid rise
in hit counts per unit time by comparison to a previous threshold baseline.
See Ans. 7, 20; Yoo, col. 11, l. 24 – col. 6, l. 7; Figs. 6, 8; FF. Based on
these aggregated alert search terms, the system generates the buzz alerts in
the form of ranked categories and “related links.” See Figure 11.
The Examiner explains further that Yoo’s traffic monitor 222
“‘aggregates counts into bins, where each bin is for a particular topic or
term’” and “‘aggregate[s] hits by subject.’” Ans. 7 (quoting Yoo at col. 7, ll.
Appeal 2011-007140
Application 11/236,869

18
59-67).
3
Analyzing these aggregated alert search terms, Yoo’s system
“locate[s] topics,” as claim 13 requires, by displaying top categories (and
subcategories) in a buzz report “in order of number of counts, along with a
relative change in buzz values.” Yoo, col. 15, ll. 11-13; Fig, 9.
As explained in connection with claim 1, by comparing counts per
unit time in the canonicalization process to create categories, by showing
only the top (canonicalized) categories ranked as such for a certain time
period (i.e., a day, see Figures 9, 11), or by comparing the percentage or
relative changes in buzz values relative to a previous day, Yoo’s system
“analyz[es] . . . the aggregated alerts to locate topics that have been
registered more than a threshold number of times in a time period,” as claim
13 requires. Simply creating the display of the top categories over a certain
day in a buzz report, as Yoo’s system does, satisfies this claim step. See
Yoo, Figs. 9, 11; note 3. Claim 13 also requires “populating a web page
with the located topics.” This further implies that the web page information,
displayed on Yoo’s user’s computer, constitutes an alert “to receive” as
claim 13 also requires. Accordingly, Appellants fail to show error in the
rejection of claims 13, 17-19, and 34.
Claim 14:
With respect to claim 14, Appellants argue that Yoo does not disclose
the claimed feature of aggregating alerts received within a predetermined
time. App. Br. 21-23. Claim 14 recites “[t]he method of claim 13, where

3
The traffic monitor monitors “traffic,” which by definition, constitutes
monitoring over certain time frames: “As used herein ‘traffic’ refers to use
of a Website or any of its pages over a given time.” Yoo, col. 1, ll. 66-67.
Appeal 2011-007140
Application 11/236,869

19
aggregating alerts registered by the user devices includes aggregating alerts
received within a predetermined time frame.”
Claim 13, from which claim 14 depends, recites, inter alia, the
following: “aggregating alerts . . . , each of the alerts including search terms,
registered by the users, that define topics, the users registering the search
terms to receive alerts relating to topics.” Similar to the discussion supra of
claim 13, in the context of claim 14 and in Yoo, users register search terms
to receive alerts relating to topics. See Ans. 7-9. Yoo’s system aggregates
the alert search terms and topics within predetermined time frames. FF.
Appellants’ arguments fail to identify a claim distinction, and track similar
arguments discussed supra. Appellants’ arguments, therefore, fail to show
error in the anticipation rejection of claims 14 and 15.
Claim 16:
Claim 16 recites “determining a number of similar search terms
entered by the users and locating the topics when the number is greater than
a threshold.” As discussed above in connection with claim 1, Yoo’s system
tracks a number of top categories, or topics, creates buzz change values for
each topic, and displays a list of top categories each of which necessarily are
displayed relative to a number greater than a threshold associated with less
popular (i.e., non-displayed) categories. See Figure 11. Accordingly,
Appellants fail to show error in the rejection of claim 16.
Claim 20:
Appellants’ arguments directed towards claim 20 are similar to
arguments addressed supra. The arguments do not show error. For
example, Appellants argue that Yoo does not analyze alerts. See App.
Appeal 2011-007140
Application 11/236,869

20
Br. 26. However, Appellants fail to explain why Yoo does not analyze
alerts. As explained supra, alerts may include displayed search results,
which may include documents or links to documents that relate to search
terms selected by the user when registering for the alert. Spec. ¶ 23.
Therefore, analyzing alerts reasonably encompasses analyzing alerts that
include registered search terms. See Morris, 127 F.3d at 1056 (“It is the
applicant’s burden to precisely define their invention, not the PTO’s.”).
In Yoo, the buzz report alerts include or aggregate search term and
other data from registered users that are registered as alert search terms
according to unique users. Claim 20 refers to analyzing and generating
alerts, and requires the system to generate “topical news subjects that
correspond to the popular alerts.” Yoo’s buzz reports do that, for the reasons
noted supra. See Yoo, Fig. 9-11, FF. Appellants’ arguments, therefore, fail
to show error in the rejection of claims 20 and 23.
Claim 21:
Appellants’ arguments directed towards claim 21 are similar to
arguments addressed supra. The arguments do not show error. Again,
Appellants argue that “Yoo does not disclose or suggest that the terms are
registered.” App. Br. 27. Yoo discloses that users and search terms are
logged together in server logs, i.e., registered, as explained supra.
Appellants also argue, as they do in connection with claim 1, a
distinction between tracking “a rapid rise in interest” and “being registered
more than a threshold number of times.” Id. at 28. This argument also is not
persuasive as explained supra. Generally, by merging terms using baseline
comparisons, or showing only the top categories, Yoo’s system “identifies
popular alert registrations based on a comparison . . . to a threshold value,”
Appeal 2011-007140
Application 11/236,869

21
as claim 21 requires. Appellants’ arguments, therefore, fail to show error in
the rejection of claims 21 and 22.
Claim 28:
With respect to claim 28, Appellants argue that Yoo does not disclose
“means for analyzing aggregated alerts (registered by users) to locate
subjects that are topical to users based on alerts that occur frequently within
the aggregated alerts.” Id. at 29. Appellants’ arguments focus on the
recited function, and assert that “[e]ntering a term into a search is different
than registering an alert.”
4
Appellants contend that “[e]ntering a search term
into a search engine yields a set of search results and does not yield an alert
about a topic for which a user is interested in receiving information.” Id. at
30. This argument is similar to the arguments addressed supra and fails to

4 Appellants do not contend that the Examiner’s showing is deficient with
respect to corresponding structure for any of the means-plus-function claims
on appeal. Appellants generally rely on “e.g., 135 Fig. 1; 220, 230-250; Fig.
2; paragraph 0037” as supporting claim 28. See App. Br. 9. Elements 135,
220, and 230-250 are essentially black boxes for a “topical subject
generator,” “processor,” etc. Paragraph 37 describes a table (Fig. 7A) that
generically shows search term hit counts, and implies, if anything,
algorithmic structure that reads on that disclosed in Yoo. See, e.g., Yoo,
Fig. 1 (search logs records, page hit records, categorizer 104, canonicalizer
102, and count generator 106). With further respect to the identified “topical
subject generator 135,” the Specification states that the structure “is not
limited to any specific combination of hardware circuitry and software.”
Spec. ¶ 0028. In general, the Specification discloses a broad array of
structure, including “software, or a combination of hardware and software,”
id. at ¶ 0052, and notes that “it will also be apparent to one of ordinary skill
in the art that aspects of the invention, as described above, may be
implemented in many different forms of software, firmware, and hardware
in the implementations illustrated in the figures,” id. at ¶ 0051.

Appeal 2011-007140
Application 11/236,869

22
show a claim distinction. Accordingly, Appellants fail to show error in the
rejection of claim 28.
Claim 30:
With respect to claim 30, Appellants assert that Yoo does not disclose
“means for aggregating alerts received within a predetermined time frame.”
App. Br. 31. These arguments are similar to arguments addressed supra and
fail to show a claim distinction. Again, Appellants focus on the function and
do not assert that Yoo fails to disclose the corresponding structure for the
means-plus-function clause. See note 4. As generally explained supra,
Yoo’s system outputs a buzz alert report that involves aggregating alerts as
claimed. Accordingly, Appellants fail to show error in the rejection of
claim 30.
Claim 31:
With respect to claim 31, Appellants assert that Yoo does not disclose
“means for locating the topical subjects when the number [of similar search
terms entered by the users] is greater than a threshold number.” Again,
Appellants do not assert that Yoo fails to disclose the corresponding
structure for the means-plus-function clause. See note 4. Rather, Appellants
rely on similar arguments related to the function that are discussed supra.
See App. Br. 33 (discussing an alleged distinction between tracking
increased frequency and comparison to a threshold).
For example, Appellants assert that Yoo’s system discloses rising
interest in terms or topics, but not on a number greater than a threshold
value. App. Br. 33. According to one example in the Specification, like
search terms for “Rafki Hariri” and “Hariri” are binned together into one
category. See Spec., Figs. 7A and 7B. This disclosure is similar to Yoo’s
Appeal 2011-007140
Application 11/236,869

23
buzz report canonicalization process that aggregates terms and locates
topical subjects using time-based baseline threshold numbers as described by
the Examiner, and as discussed above. Accordingly, Appellants fail to show
error in the rejection of claim 31.
Based on the foregoing discussion, Appellants fail to show that the
Examiner erred in determining that Yoo anticipates claims 1, 7, 9-23, 28, 30,
31, and 34.
B. Claim 6, obviousness over Yoo, and claims 2-5, 24-27, 29, 32, and 33,
obviousness over the combination of Yoo and Faudman
Appellants primarily rely on alleged deficiencies in Yoo, discussed
supra, to show that the Examiner failed to establish obviousness. See App.
Br. 34-49. Based on the foregoing discussion, and the Examiner’s findings
and rationale, Appellants fail to show error in the Examiner’s determination
of obviousness. See Fin. Rej. 10-15; Ans. 12-18, 24-26.
With further respect to claim 6, “Appellants submit that the
Examiner’s statement of Official Notice does not remedy the deficiencies in
the disclosure of YOO et al. set forth above with respect to claim 1.” App.
Br. 46. This statement fails to challenge the Official Notice by the
Examiner, which asserts that a particular programming search language,
SQL, was well-known. See Fin. Rej. 14. It also fails to challenge or show
error in the Examiner’s rationale: “It [would have been] obvious . . . to apply
the known practice to the system disclosed by Yoo, in order to adopt a
common database search method.” Id.
Appellants also assert that claims 4 and 33 recite a feature not
disclosed or suggested by Yoo and Faudman—receipt of an indication of the
frequency that email alerts are to be transmitted to the user device. See App.
Br. 46-49. Setting aside the characterization of “official notice” by the
Appeal 2011-007140
Application 11/236,869

24
Examiner, the Examiner essentially finds that allowing users to define an
“event/alert/notification” frequency amounts to a design choice. See Fin.
Rej. 14.
Claim 4 ultimately depends from claim 2, which requires an email
alert. Claim 33 depends from claim 29, which also requires an email alert.
The Examiner relies on Faudman to teach or suggest email alerts to provide
notice of events. See Fin. Rej. 11 (citing ¶¶ 0098, 0104). At the cited
passages, Faudman discloses generating status email alerts regarding
favorite types of property of interest. The email updates may include
changes in the status of such properties. Given the combined teachings, as
the Examiner generally reasons, it would have been obvious to allow a user
to decide how often such status alerts, or similar search term email alerts,
should be sent to create notice of an event.
Allowing users to specify the frequency of email alerts amounts to a
design choice, as the Examiner reasons, to improve user friendliness. See
Fin. Rej. 14. Appellants do not challenge the Examiner’s finding; rather,
they complain that the Examiner has merely dismissed the limitation with a
conclusory statement. App. Br. 46-47. Contrary to the argument, the
Examiner did not dismiss the limitation; rather, the Examiner found that it
was a non-inventive design choice. Appellants fail to identify error in that
finding.
Appellants do not challenge the Examiner’s underlying determination
that it would have been obvious to request a single email alert. Appellants
fail to explain how requesting a specific number of alerts, as opposed to
requesting a single alert, would alter the function or purpose of the email
notification system suggested by the combination of Yoo and Faudman.
Appeal 2011-007140
Application 11/236,869

25
Moreover, claims 4 and 33 do not preclude requesting to receive one email
alert per topical subject, i.e., a frequency of one alert per subject, as the
combination fairly suggests.
Based on the foregoing discussion, Appellants’ arguments fail to show
that the Examiner erred in determining that claims 2-6, 24-27, 29, 32, and 33
would have been obvious.
DECISION
The Examiner’s decision to reject claims 1-7 and 9-34 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)(1)(iv).

AFFIRMED