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 § 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.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claims do not recite any computer or processor implementation. As such the claim can be practically performed mentally and therefore fall within the mental process exception.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a join inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The terms included in the claim limitations including: “relative likeness” and “a correlation between user engagement”. These terms are not defined by the claim, the specification does not provide a particularly defined definition or process to describe the function of “relative likeness” and “a correlation between user engagement”, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Remarks
In the applicant’s remarks received on October 16, 2025, the applicant argues: “Applicant’s representative submits that none of the cited refences teach or suggest, alone or in combination, “influence relationship indicative of a correlation between user engagement between pairs of content items in the content items in the plurality of result content items” as recited in claims 1.”
The Examiner reply: In the applicant’s claim amendment filed on October 16, 2025 the claims have been currently amended. The new claim amendment was not presented for review during the issuance of the Office Action mailed on July 16, 2025. Therefore, the current Office Action will address the current claim amendments below.
Claim Rejections - 35 USC § 103
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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 6, 8-11, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Dassa et al. (Patent No. 8,756,224 filed June 16, 2011, hereinafter Dassa) and Wang et al. (Publication No. 2015/0120753 filed October 24, 2013, hereinafter Wang).
Regarding Claims 1, 11, and 16, Dassa teaches a method for ranking content items (Abstract, content ranking) comprising: identifying a plurality of result content items matching at least one criterion, the plurality of result content items identified from one content items in a collection of content items (Abstract, specifically, detecting similarities between each of plurality of content snippets; column 8, lines 61-65, real-time ranking module (element 240) or any other component of the application can extract entities, keywords, and/or other elements from the received set of content snippets for comparison with entities, keywords, and/or other elements in the trend index. Column 9, lines 1-6, real-time ranking module (element 240) detects similarities between each of the content snippets and indexed trend data and user influence data (in index element 230), For example, real-time ranking module (element 240) can match trend data and user influence data to information obtained from the content snippets and generate a score for each of the snippets.);
ranking the content items in the plurality of result content items based on a similarity relationship that defines a relative likeness between the content items in the plurality of result content items (Abstract, lines 13-14, ranking the plurality of content snippets based on the detected similarities; column 9, lines 10-13, based on the determined similarities, a similarity score can be generated for each of the content snippets and real-time ranking module (element 240) can aggregate the similarity scores from matching trends.), and an influence relationship between the content items in the plurality of result content items (Abstract, lines 7-8, user influence information, column 7, lines 26-29, User influence data can be used to provide an indication that allows rea-time content to be differentiated based on the influence score of the user).
However, Dassa does not expressly teach a correlation between user engagement between pairs of content items.
Wang teaches a correlation between user engagement between pairs of content items (see Abstract, indexing content based upon index features (e.g., temporal features, user engagement features, and/or outlier features), and/or for providing content within a search result interface based upon such index features and/or rankings. For example, user reaction data associated with content (e.g., a microblog message, a social network post, etc.) may be evaluated to generate a user engagement feature that may be constrained to a time window feature (e.g., the number of shares of a message within the first 10 minutes from publication of the message) to create an index feature for indexing the content within a content index.).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the concept of Wang’s method with Dassa’s method because Wang’s method provides a user engagement feature constrained to a time window by indexed featured query content.
Regarding Claim 6, Dassa teaches wherein the content items are items of invitational content (see figure 10 beginning at element 1010, an invitation for the user to create a widget, column 12, lines 48-52), the method further comprising:
receiving a request for an item of invitational content by a content delivery system, wherein the request includes the at least one criterion (see figure 10 beginning at element 1010, an invitation for the user to create a widget, column 12, lines 48-52);
sending a highly ranked result content item in response to the request (column 12, lines 34-44, the user created widget, e.g. invitation, with content ranking lists.).
Regarding Claim 8, Dassa teaches determining the influence relationship based on aggregated sequence data of content item transitions, wherein a first content item has a stronger influence relationship on a second content item when users transition to the second content item recently after interacting with the first content item more frequently than other content items in the aggregated sequence data (column 7, lines 26-39, user influence data can be used to provide an indication that allows real-time content to be differentiated based on the influence score of the user; each user can be assigned an influence sore, where trend data, historical data can influence, among other things, approaches for ranking content).
Regarding Claim 9, Dassa teaches determining the influence relationship based on aggregated targeted campaign data, wherein a first content item has a stronger influence relationship of a second content item when targeted campaign data associated with the second content item targets users of the first content item more frequently than other content items in the aggregated targeted campaign data (column 7, lines 26-39, user influence data can be used to provide an indication that allows real-time content to be differentiated based on the influence score of the user; each user can be assigned an influence score, where trend data, historical data can influence, among other things, approaches for ranking content).
Regarding Claims 10, Dassa teaches determining the influence relationship based on aggregated review data, wherein a first content item has a stronger influence relationship on a second content item when first review data associated with the first content item references the second content item more frequently than other content items in the aggregated review data (column 7, lines 26-39, user influence data can be used to provide an indication that allows real-time content to be differentiated based on the influence score of the user; each user can be assigned an influence score, where trend data, historical data can influence, among other things, approaches for ranking content).
Claims 2, 7, 12, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Dassa et al. (Patent No. 8,756,224 filed June 16, 2011, hereinafter Dassa) and Wang et al. (Publication No. 2015/0120753 filed October 24, 2013, hereinafter Wang) as applied to claim 1 above, and further in view of Duan et al. (Publication No. 2020/0401634 filed June 20, 2019, hereinafter Duan).
Regarding Claims 2, 12, and 17, Dassa teaches determining the influence relationship between the pairs of content items in the collection of content items based on content item transitions (column 7, lines 66-67, column 8, lines 1-2, user influence data can be indexed into trend index 230. For example, a real-time ranking module 240 of the application can determine real-time online trends (e.g., the latest trends and topics)), and review data (column 12, lines 44-45, the user also reviews recent news and postings).
However, Dassa and Wand do not expressly teach targeted campaign data.
Duan (2020/0401634) teaches targeted campaign data ([0044)] targeted by the campaign).
It would have been obvious to one of ordinary skill in the art before the effective filling data of the claimed invention to incorporate the concept of Duan’s method with Dassa’s and Wang’s method because Duan’s method provides generating scores for the ranking of content items and a subset of content items being selected for delivery based on the ranking.
Regarding Claims 7, Duan teaches providing a user interface to configure a targeted campaign ([0044)] targeted by the campaign).
Dassa teaches a first item of invitational content that is configured to invite engagement with a first content item is to be targeted to be presented in association with at least one second content item (column 12, lines 34-44, the user created widget, e.g. invitation, with content ranking lists); recommending one or more highly ranked content items to be selected as the at least one second content item, wherein the at least one criterion is relevance to the first content item (Abstract); receiving a selection of the one or more highly ranked content items in the user interface; and configuring to serve the first item of invitational content in association with the selected one or more highly ranked content items (Abstract).
Regarding Claims 3, 4, 13, 14, 18, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Dassa et al. (Patent No. 8,756,224 filed June 16, 2011, hereinafter Dassa) and Wang et al. (Publication No. 2015/0120753 filed October 24, 2013, hereinafter Wang) as applied to claims 1, 11, and 16 above, and further in view of Yee et al. (Patent No. 9,129,227 filed September 8, 2015, hereinafter Yee).
Regarding Claims 3, 13, and 18, Dassa teaches determining the similarity relationship between a first content item and a second content item from a comparison of an embedding of the first content item an embedding of the second content item (column 2, lines 66-67, column 3, lines 1, detecting similarities between each of the plurality of content snippets and the determined real-time trend information) are derived from a title, a description, a user review, and a user rating of the content items (column 10, lines 24-30, content snippet is identified by a title; a description or a portion of the content; and user with the ranked list).
However, Dassa and Wang do not expressly teach an embedding space.
Yee teaches an embedding space (column 11, line 34, embedding space).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to incorporate the concept of Yee’s method with Dass’s and Wang’s method because Yee’s method provides generating the ranking of content items based on determined probabilities and a selection of a subset of content items being recommended to a user based on the ranked content items.
Regarding Claims 4, 14, and 19, Yee teaches construct a graph of relationships between the content items in the collection of content items (column 8, lines 38 & 41, topic graph includes a set of related topic nodes also including topic clusters e.g., edges), wherein edges connecting the content items to other content items are defined by a relevance value that represents a relevance of the content items (Abstract, ranking the plurality of content items) connected by the edges.
Dassa teaches the relevance value (column 7, lines 67, real-time ranking) being made up of the similarity relationship and the influence relationship (Abstract, lines 7-8, user influence information, column 7, lines 26-29, User influence data can be used to provide an indication that allows real-time content to be differentiated based on the influence score of the user.).
Allowable Subject Matter
Claims 5, 15, 20, and 21 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.
The prior art of record, Dassa, (Patent No. 8,756,224) teaches detecting similarities between each of a plurality of content snippets.
Next, the prior art of record, Rodrigues (Publication No. 2022/0114205) teaches ranking signals for content items given a weighted average.
However, the prior art of record does not teach or suggest in combination with the similarity relationship is weighted by the context-driven factor and the influence relationship is weighted by the inverse of the context-driven factor and aggregated behavioral and contextual signals indicative that engagement with the first content item increases a propensity for engagement with the second content item
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 CHERYL R LEWIS whose telephone number is (571)272-4113. The examiner can normally be reached Monday-Thursday, 8am-5pm, EST.
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/CHERYL LEWIS/Primary Examiner, Art Unit 2166 January 28, 2026