Prosecution Insights
Last updated: May 29, 2026
Application No. 19/048,322

DYNAMIC FILTER RECOMMENDATIONS

Final Rejection §101§102
Filed
Feb 07, 2025
Priority
Dec 12, 2019 — continuation of 11/727,014 +1 more
Examiner
ORTIZ DITREN, BELIX M
Art Unit
2164
Tech Center
2100 — Computer Architecture & Software
Assignee
Pinterest Inc.
OA Round
2 (Final)
84%
Grant Probability
Favorable
3-4
OA Rounds
1y 6m
Est. Remaining
86%
With Interview

Examiner Intelligence

Grants 84% — above average
84%
Career Allowance Rate
579 granted / 689 resolved
+29.0% vs TC avg
Minimal +2% lift
Without
With
+2.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
16 currently pending
Career history
707
Total Applications
across all art units

Statute-Specific Performance

§101
4.4%
-35.6% vs TC avg
§103
63.3%
+23.3% vs TC avg
§102
23.8%
-16.2% vs TC avg
§112
2.4%
-37.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 689 resolved cases

Office Action

§101 §102
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Remarks In response to communication files on February 2, 2026, claims 1-2, 4-7, 9-10, 12-15, 17, and 19-20 are amended by applicant's request. Therefore, claims 1-20 are presently pending in the application. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-6, 9-14, and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Regarding claims 1, 9, and 17, Step 1 Analysis: Claim 1, 9, and 17 are directed to a process, which falls within one of the four statutory categories. Step 2A Prong 1 Analysis: Claim 1 recites, The limitations of: “determining a category associated with the user activity data” is a mental process which can be performed by the human mind. A human can make a determination. “identifying a first session record from a plurality of session records by comparing the category with a plurality of session definitions associated with a plurality of session records, the first session record including a first session preference hierarchy indicating user preferences with respect to a plurality of levels, the first session preference hierarchy compiled from first hierarchies for one or more of a plurality of first items of the first session record” is a mental process which can be performed by the human mind. A human can identify and compare categories. “determining, based at least in part on the first session record, a plurality of second items that are responsive to the user activity data” is a mental process which can be performed by the human mind. A human can determine or identify items. “scoring one or more of the plurality of second items including comparing levels for one or more second hierarchies associated with the plurality of second items with the levels of the first session preference hierarchy to calculate a respective similarity score for the one or more second items” is a mental process which can be performed by the human mind. A human can score, organize, and compare items. “providing at least a portion of the plurality of second items to the client device for presentation based on the score determined for one or more of the plurality of second items” is a mental process which can be performed by the human mind. A human can provide a list of results. These limitations, as drafted, are processes that, under broadest reasonable interpretation, covers the performance of the limitation in the mind which falls within the “Mental Processes” or certain methods of organizing human activities grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Step 2A Prong 2 Analysis: Claims 1, 9, and 17 recites the additional elements: “receiving, from a client device, user activity data of a user” is an additional element and is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application. A computer program product comprising client device, one or more processors, a memory, one or more computer storage media, and computer, note that these recited additional elements are a high-level recitation of generic computer components to perform the mental process and applied on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application. Step 2B Analysis: the conclusions for the additional elements representing mere implementation using a computer are carried over and do not provide significantly more. With respect to the "receiving” limitation is identified as insignificant extra-solution activity above when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more. Lastly the recitation of client device, one or more processors, a memory, one or more computer storage media, and computer are recitation of generic computer components to perform the mental process and applied on a computer as in MPEP 2106.05(f). Regarding claims 2 and 10, recites the additional elements: “receiving a user selection of one or more second item of the at least the portion of the plurality of second items provided for presentation to the client device”. The limitation of “receiving” are an additional element and is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application. Regarding claims 3-6, 11-14, and 18-20, the rejection of claims 1, 9, and 17 are further incorporated, and further, the claim recites: receiving a user selection…, updating preference…compare and scoring items…, recites limitations abstract ideas previously identified in the independent claims, that are mental process which can be performed by the human mind. This claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Therefore, the claims as a whole does not change this conclusion and the claims are ineligible. Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claim(s) 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Smith et al. (U.S. Pub 2002/0010625) (Eff filing date of app: 3/29/20010) (Hereinafter Smith). As to claims 1, 9, and 17, Smith teaches a method comprising: receiving, from a client device, user activity data of a user (see abstract, “Various methods are disclosed for monitoring user browsing activities”); determining a category associated with the user activity data (see p. 23, “The list may optionally be filtered based on the category of products currently being viewed by the user. For example, when a user views a product detail page of an item, the detail page may be supplemented with a list of other recently viewed items falling within the same product category as the viewed product.”); identifying a first session record from a plurality of session records by comparing the category with a plurality of session definitions associated with a plurality of session records, the first session record including a first session preference hierarchy (see abstract, “monitoring user browsing activities, and for using such information to provide session-specific item recommendations to users.”, fig. 11 and p. 17, “…by maintaining user-specific (and preferably session-specific) histories of item detail pages viewed by the users…”) indicating user preferences with respect to a plurality of levels (see fig. 2, character 80 and p. 52, “the user has implicitly or explicitly indicated some level of interest from items predicted by the Recommendation Service to be of interest.)”), the first session preference hierarchy compiled from first hierarchies for one or more of a plurality of first items of the first session record (see p. 94, ranked); determining, based at least in part on the first session record, a plurality of second items that are responsive to the user activity data (see fig. 1, character 62 and 64 and fig. 11 and p. 12-13, “The resulting item relatedness data may be used to provide personalized item recommendations to users (e.g., product recommendations to customers of an online store), and/or to provide users with non-personalized lists of related items (e.g., lists of related products on product detail pages).”); scoring one or more of the plurality of second items including comparing levels for one or more second hierarchies associated with the plurality of second items with the levels of the first session preference hierarchy to calculate a respectibe similarity score for the one or more second items (see fig. 2, character 84 and p. 94, “If multiple similar items lists 64 are retrieved in step 82, the lists are appropriately combined (step 86), preferably by merging the lists while summing or otherwise combining the scores of like items. The resulting list is then sorted (step 88) in order of highest-to-lowest score”); and providing at least a portion of the plurality of second items to the client device for presentation based on the score determined for one or more of the plurality of second items (see p. 25, “In one embodiment, the method comprises selecting products to recommend to the user based on whether each product is a member of one or more of the results sets of the recently conducted searches. A product that is a member of more than one such search results set may be selected over products that are members of only a single search results set.”). As to claims 2 and 10, Smith teaches The method further comprising: receiving a user selection of one or more second items of the at least the portion of the plurality of second items provided for presentation to the client device (see p. 60, “The recommendations are preferably displayed on a special Web page that can selectively be viewed by the user.”). As to claims 3, 11, and 18, Smith teaches The method further comprising: in response to the identifying the first session record, updating the first session record according to the user activity data (see p. 194, “modified session record.”), wherein updating the first session record comprises: updating the first session preference hierarchy according to one or more image data hierarchies of items associated with the user activity data (see p. 194, “When the user selects this button, the HTTP/XML application 37 deletes the de-selected item(s) from the corresponding session record in the click stream table 39, or marks such items as being deselected. The Session Recommendations process 52 then regenerates the Session Recommendations using the modified session record.”). As to claims 4, 12, and 19, Smith teaches wherein scoring one or more of the items comprises: comparing one or more of the plurality of second items to the first session preference hierarchy including: comparing, for one or more of the plurality of second items, the first session preference hierarchy with a respective image data hierarchy of the second item (see p. 215, “Each user's history of recent searches, as reflected within the session record, may be used to generate recommendations in an analogous manner to that described in section VIII. The results of each search (i.e., the list of matching items”); and determining the score for one or more item based on a matching between the first session preference hierarchy and the image data hierarchy for the second item at one or more level of the respective hierarchies (see p. 164-165). As to claims 5 and 13, Smith teaches The method further comprising: scoring one or more of the plurality of second items based on a comparison of the respective image data hierarchy for one or more of the plurality of second items and a global user preference hierarchy (see p. 79, “The similar items table 60 could also reflect non-collaborative type item similarities, including content-based similarities derived by comparing item contents or descriptions.” And p. 148, “For example, the table generation process could compare item contents and/or use previously-assigned product categorizations as additional or alternative indicators of item relatedness”); and combining a first score based on the first session preference hierarchy and a second score based on the global user preference hierarchy to determine a score for one or more second item (see p. 94, “preferably by merging the lists while summing or otherwise combining the scores of like items. The resulting list is then sorted (step 88) in order of highest-to-lowest score. By combining scores of like items, the process takes into consideration whether an item is similar to more than one of the items of known interest.”). As to claims 6, 14, and 20, Smith teaches The method, further comprising: in addition to determining the category associated with the user activity data, determining features of the plurality of second items associated with the user activity data (see abstract “Various methods are disclosed for monitoring user browsing activities, and for using such information to provide session-specific item recommendations to users.” And p. 2, “The present invention relates to methods for monitoring activities of online users, and for recommending items to users based on such activities. More specifically, the invention relates to methods for providing personalized recommendations that are relevant to a current browsing session of a user.”); and using the features of the plurality of second items in identifying the first session record (see p. 184, “during the current session, the user is presented with a link to a custom page of the type shown in FIG. 11. The link includes an appropriate message such as "view the page you made," and is preferably displayed persistently as the user navigates from page to page. When the user selects this link, a Session Recommendations component 52 accesses the user's cached session record to identify the products the user has viewed, and then uses some or all of these products as the "items of known interest" for generating the personal recommendations. T”). As to claims 7 and 15, Smith teaches wherein the user activity data comprises a user query, and wherein the plurality of second items is responsive to the user query (see p, 182, “For example, when the user runs a search for a product, the HTTP/XML application may record the search query”). As to claims 8 and 16, Smith teaches wherein the first session preference hierarchy comprise preferred content characteristics based on session activity associated with the first session record, and wherein scoring further comprises weighting the first session preference hierarchy based on an activity stage of the user (see p. 173, “An important characteristic of this process is that the recommended products tend to be products that are similar to more than one of the products in the shopping cart (since the CI values of like items are combined). Thus, if the items in the shopping cart share some common theme or characteristic, the items recommended to the user will tend to have this same theme or characteristic.”). Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to BELIX M ORTIZ DITREN whose telephone number is (571)272-4081. The examiner can normally be reached M-F 9am -5pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Amy Ng can be reached at 571-270-1698. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. BELIX M. ORTIZ DITREN Primary Examiner Art Unit 2164 /Belix M Ortiz Ditren/Primary Examiner, Art Unit 2164
Read full office action

Prosecution Timeline

Feb 07, 2025
Application Filed
Oct 01, 2025
Non-Final Rejection mailed — §101, §102
Feb 02, 2026
Response Filed
May 20, 2026
Final Rejection mailed — §101, §102 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
84%
Grant Probability
86%
With Interview (+2.0%)
2y 10m (~1y 6m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 689 resolved cases by this examiner. Grant probability derived from career allowance rate.

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