Prosecution Insights
Last updated: April 19, 2026
Application No. 18/737,559

System and Method for Sampling Content Recommendations Using a Multi-Entity Surrogate Connectivity Graph and Telemetry Data

Non-Final OA §102
Filed
Jun 07, 2024
Examiner
PARRA, OMAR S
Art Unit
2421
Tech Center
2400 — Computer Networks
Assignee
Microsoft Technology Licensing, LLC
OA Round
1 (Non-Final)
74%
Grant Probability
Favorable
1-2
OA Rounds
2y 9m
To Grant
84%
With Interview

Examiner Intelligence

Grants 74% — above average
74%
Career Allow Rate
496 granted / 673 resolved
+15.7% vs TC avg
Moderate +10% lift
Without
With
+9.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
34 currently pending
Career history
707
Total Applications
across all art units

Statute-Specific Performance

§101
6.2%
-33.8% vs TC avg
§103
48.3%
+8.3% vs TC avg
§102
25.8%
-14.2% vs TC avg
§112
4.8%
-35.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 673 resolved cases

Office Action

§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 . Claim Rejections - 35 USC § 102 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claim(s) 1-6, 9-12 and 15-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kelley (Pub. No. 2015/0149484). Regarding claims 1, 9 and 17, Kelley teaches a computing system (100, Fig. 1) (with corresponding computer-implemented method and a computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon ([0001] -software providing a graph-based recommendations service; fig. 1 - server, client devices) comprising: a memory; and a processor (these elements are inherent on computing devices) configured to: processing a plurality of content portions and a plurality of opportunities associated with a recommender system; ([0039]; [0040] - item provider 110 may provide recommendable items; while Recommendations server 1200 provides recommendations of those items. [0050], - request-context metadata associated with the recommendation request include data such as a user identifier identifying a user to whom a recommendation will be provided, an item identifier identifying a recommendable item that the user is currently viewing and/or currently indicating an interest in, a current date and/or time, current physical location, current state of the application or the like (=personal communication for a product, i.e. "opportunity" according to the description)); generating a dynamic surrogate connectivity graph using the plurality of content portions and the plurality of opportunities; (Fig.3; [0032] - a heterogeneous recommendations graph includes nodes representing recommendable items; intermediate nodes representing non-recommendable joining elements; and weighted edges joining the nodes. [0076] - node '/' may correspond to a particular ringtone by a particular artist, which can be purchased by the user for a particular price(= opportunity)); processing telemetry data associated with the recommender model; ([0050]); modeling a plurality of weighted path scores using the dynamic surrogate connectivity graph and the telemetry data; and ([0050], where count of highly-weighted paths to recommendable nodes from only a portion of the recommendations directed-graph that is reachable from the entry node {as selected in block 405) via only highly-weighted paths of configurable lengths; [0072], [0073] - average the weight values of each weighted edge in the path); providing the plurality of weighted path scores to the recommender model for generating subsequent recommendations ([0074] - In ending loop block 435, recommendations-request subroutine 400 iterates back to opening loop block 420 to process the next potential recommendation node, if any). Regarding claims 2 and 15, Kelly teaches further comprising: sampling a plurality of subsequent recommendations generated by the recommender system using the plurality of weighted path scores by determining a number of content portions to provide for each path type by multiplying a total number of subsequent recommendations with the plurality of weighted path scores (fig.2; [0048] - Recommendations-service routine 200 iterates from opening loop block 215 to ending loop block 235 while handling recommendation requests. [0067] - recommendations-request subroutine 400 may select multiple entry nodes and process them in series or parallel(= sampling). Fig.4 - 420 - for each potential recommendation; [0070] - processes each potential recommendation node accordingly. [0068], [0072], [0073] – using highly-weighted paths, compute a path weight for each path using mathematical methods, then combine the individual path weights by simple addition or otherwise). Regarding claims 3 and 16, Kelly teaches further comprising: providing subsequent recommendations with content portions of each path type from the plurality of subsequent recommendations to a requesting user based upon, at least in part, the number of content portions for each path type; processing a selection of one of the subsequent recommendations from the requesting user; and transmitting an electronic product associated with the selection to the requesting user (iterative recommendation service, using graph traversal subroutine traversing graph based on e.g. path length, path-weight batches, collecting paths to recommendable nodes until desired count is reached, highly-weighted paths; whereby end of the highest weighted path is returned first, par. 77 - the particular item). Regarding claims 4, 10 and 18, Kelly teaches wherein generating the dynamic surrogate connectivity graph includes using an opportunity-to-content portion semantic matching model to define a plurality of paths of a first path type ([0045]-[0048]). Regarding claims 5, 11 and 19, Kelly teaches wherein generating the dynamic surrogate connectivity graph includes using an opportunity-to-opportunity similarity model to define a plurality of paths of a second path type ([0065]). Regarding claims 6, 12 and 20, Kelly teaches wherein generating the dynamic surrogate connectivity graph includes a third path type using a content provider-to-content provider similarity model to define a plurality of paths of a third path type ([0045]; [0054]; [0065]; [0135]-[0137]). Allowable Subject Matter Claims 7, 8, 13 and 14 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to OMAR S PARRA whose telephone number is (571)270-1449. The examiner can normally be reached M-F: Mostly 10-6PM. 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, Nathan Flynn can be reached at 571-2721915. 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. /OMAR S PARRA/Primary Examiner, Art Unit 2421
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Prosecution Timeline

Jun 07, 2024
Application Filed
Jan 24, 2026
Non-Final Rejection — §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

1-2
Expected OA Rounds
74%
Grant Probability
84%
With Interview (+9.9%)
2y 9m
Median Time to Grant
Low
PTA Risk
Based on 673 resolved cases by this examiner. Grant probability derived from career allow rate.

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