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 .
This office action is in response to application filed on March 2, 2026, in which claims 1-10, 12-18 and 20-22 are presented for further examination.
Response to Arguments
Applicant's arguments filed on March 2, 2026 have been fully considered but they are not persuasive. (See Remarks)
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 1-10, 12-18 and 20-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claim recites “A method comprising: determining, by a computing device, a plurality of search queries for a time period; determining a plurality of content items associated with at least one of the plurality of search queries; determining a time of availability for each of the plurality of content items; determining, based on the time of availability, a ranking order of the plurality of content items; and causing, by the computing device and at a user device, output of an indicator of at least a portion of the plurality of content items in the ranking order.” This judicial exception is not integrated into a practical application because the steps can be performed manually in human mind. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claim here merely uses the computer processor as a tool to perform the otherwise mental processes. See October Update at Section I(C)(ii). Thus, the limitations recite concepts that fall into the “mental process” grouping of abstract ideas.
ANALYSIS under Revised Guidance:
Statutory Category:
The claims 1-10, 12-18 and 20-22 are directed to one of the four statutory category (claims 1-10, 12-18 and 20-22 a method.
Step 2A — Prong 1: Judicial Exception Recited?
The claim 1 recites the limitations of “determining, by a computing device, a plurality of search queries for a time period; determining a plurality of content items associated with at least one of the plurality of search queries; determining a time of availability for each of the plurality of content items; determining, based on the time of availability, a ranking order of the plurality of content items; and causing, by the computing device and at a user device, output of an indicator of at least a portion of the plurality of content items in the ranking order” The limitations, as drafted, are steps or processes that, under their broadest reasonable interpretation, cover performance of the limitations in mind. That is, nothing in the claim 1 precludes the processes (the steps ...) from practically being performed in the human mind. The claim 1 encompasses the limitations of the processes or steps of receiving, determining, ranking, and causing output in a ranking order. The user manually the data and does not take the claimed limitations out of the mental processes, which is one of the groupings of abstract ideas. Thus, the claim 1 recites an abstract idea under one of groupings of abstract idea, mental processes (concepts performed in the human mind including an evaluation, judgment, opinion, observation). (MPEP 2106.05(a)).
Step 2A — Prong 2: integrated into a practical application?
The claim 1 recites limitations or elements (a computing device and a user device) do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea as identified in MPEP 2106.05(g).
Step 2B: The claim does not provide an incentive concept.
The claim 1 includes limitations or elements that are sufficient to amounts to no more than mere instructions to apply the judicial exception which cannot integrate a judicial exception into a practical application or provide an inventive concept. The same analysis applies here in 2B, that is, Mere instructions to apply a judicial exception, it cannot integrate a judicial exception into a practical application at step 2A or provide an inventive concept in step 2B. Thus, the claim 1 is ineligible.
At step 2A(i):
Independent claim 1 recites the following limitations directed to an abstract idea:
“determining, by a computing device, a plurality of search queries for a time period” recites a mental process as determining search query. The “determining” identified as insignificant extra solution activities above see MPEP 2106.04(d)(D(..e. retrieve/receive/transmit over network, store/retrieve from memory) for Berkheimer support of well-understood, routine, and conventional as evidence under MPEP 2106.07(a)(IID(A).
“determining a plurality of content items associated with at least one of the plurality of search queries” recites a mental process as determination, observation or evaluation of plurality of content. There is nothing specific recited as to how the queries are executed to “providing/returning” a result. Instead this merely recites that the abstract idea of determining the query is implemented on a computer per MPEP 2106.05(f).
“determining a time of availability for each of the plurality of content items”, recites a mental process as stratifying query records, the abstract idea of stratifying data query records. MPEP 2106.05(f).
“determining, based on the time of availability, a ranking order of the plurality of content items”, recites a mental process as stratifying query records, the abstract idea of stratifying data query records. MPEP 2106.05(f).
“causing, by the computing device and at a user device, output of an indicator of at least a portion of the plurality of content items in the ranking order.”, recites a mental process as output, the abstract idea of presenting content items. There is nothing specific recited as to how the query is executed to output set of historical query records. MPEP 2106.05(f).
At step 2A (ii):
The claim recites the following additional elements: That the method is “a computing device and a user device” insignificant extra solution activities per MPEP 2106.05(g).
At step 2B:
The conclusions for the mere implementation using a computer are carried over and does not provide significantly more. With respect to the “determining a plurality of search queries for a time period”. The “determining” identified as insignificant extra-solution activities above see MPEP 2106.04(d)(II)(i.e. receive/transmit over network, store/retrieve from memory) for Berkheimer support of well-understood, routine, and conventional as evidence under MPEP 2106.07(a)CID(A).
Independent claims 10 and 18 are rejected based on the same rationale as claim 1.
Dependent claim 2 recites “wherein determining the plurality of the search queries for the time period comprises: receiving at least one of: a listing of most received search queries for the time period or a listing of most used hashtag topics for the time period, wherein determining the plurality of search queries comprises determining, based on at least one of: the listing of the most received search queries for the time period or the listing of the most used hashtag topics for the time period, the plurality of search queries” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 3, recites “wherein determining the plurality of content items associated with at least one of the plurality of search queries comprises: determining, a plurality of content segments for a first content item of the plurality of content items; and determining, at least a portion of detected text of a first content segment of the plurality of content segments is associated with at least one of the plurality of search queries” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 4, recites “wherein causing output of at least the portion the plurality of content items in the ranking order comprises causing output of an indicator of a portion of the first content item comprising the first content segment.” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 5, recites “wherein the ranking order comprises ranking the plurality of content items in order from a most recent time of availability to a least recent time of availability.” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 6, recites “wherein the indicator for the at least the portion of the plurality of content items comprises at least one of: a title of a content item of the plurality of content items; an image associated with the content item of the plurality of content items, or a content channel name for a content channel associated with the content item of the plurality of content items.” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 7, recites “receiving, by the computing device, the plurality of content items from at least one content source” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 8, recites “wherein determining the ranking order of the plurality of content items comprises: determining a first portion of the plurality of content items associated with a first query of the plurality of search queries; and determining, based on the time of availability, a ranking order of the first portion of the plurality of content items.” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 9, recites “wherein determining the ranking order of the first portion of the plurality of content items further comprises: determining a portion of the first portion of the plurality of content items associated with a content source; and determining, based on the time of availability, a ranking order of the portion of the first portion of the plurality of content items associated with the content source.” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 10, recites “receiving, by a computing device, a search query for a time period; determining a plurality of content items comprising detected text associated with the search query ;determining a time of availability for each of the plurality of content items; ranking, based on the time of availability, the plurality of content items; and causing, by the computing device and at a user device, based on the ranking, output of an indicator of at least a portion of the plurality of content items.” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 12, recites “wherein the detected text comprises at least one of: closed-captioning text or metadata” which is further elaborating on the abstract idea, and therefore it does not amount to significantly more.
Dependent claim 13, recites “wherein the search query comprises at least one of amost-searched search query or a hashtag topic for the time period” which is further elaborating on the abstract idea, and therefore it does not amount to significantly more.
Dependent claim 14, recites “wherein determining the plurality of content items comprising the detected text associated with the search query comprises: determining, a plurality of content segments for a first content item of the plurality of content items; and determining, at least a portion of the detected text of a first content segment of the plurality of content segments is associated with the search query” which is further elaborating on the abstract idea, and therefore it does not amount to significantly more.
Dependent claim 15, recites “wherein ranking the plurality of content items comprises ranking the plurality of content items in order from a most recent time of availability to a least recent time of availability.” which is further elaborating on the abstract idea, and therefore it does not amount to significantly more.
Dependent claim 16, recites “receiving, by the computing device, a second search query for the time period; wherein the detected text comprises at least one of: closed-captioning text or metadata” which is further elaborating on the abstract idea, and therefore it does not amount to significantly more.
Dependent claim 17, recites “wherein ranking the plurality of content items comprises :determining a first portion of the plurality of content items associated with a content source; and determining, based on the time of availability, a ranking order of the first portion of the plurality of content items associated with the content source.” which is further elaborating on the abstract idea, and therefore it does not amount to significantly more.
Dependent claim 21, recites “wherein the indicator for the at least the portion of the plurality of content items comprises at least one of: a title of a content item of the at least the portion of the plurality of content items; an image associated with the content item of the at least the portion of the plurality of content items, or a content channel name for a content channel associated with the content item of the at least the portion of the plurality of content items.” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 20, recites “wherein the weighted value is greater for a more recent time of availability of a particular content item and less for a less recent time of availability of another particular content item” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 22, recites “wherein receiving the plurality of the search queries popular topics for the time period comprises receiving at least one of: a listing of most received search queries for the time period or a listing of most used hashtag topics for the time period.” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Claim Rejections - 35 USC § 103
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.
Claims 1-7, 10, 13-18 and 20-22 are rejected under 35 USC 103(a) as being unpatentable over HUANG et al. (US 20220237251 A1) (hereinafter Huang) In view of Zhang et al. (US 20170031654 A1) (hereinafter Zhang).
As per claims 1 and 10, Huang discloses determining, by a computing device, a plurality of popular search queries for a time period [obtaining a current query of a user, search history information of the user in a first time period, paragraph 7]; determining a plurality of content items associated with at least one of the plurality of popular search queries [an obtaining unit configured to obtain a current query of a user, search history information of a user in a first time period, search history information of the user in a second time period and candidate search results for the current query, paragraph 46]; and causing, by the computing device and at a user device, output of an indicator of at least a portion of the plurality of content items in the ranking order [an output of the ranking model includes scores of search results, paragraph 51]. However Huang does not disclose determining, based on the time of availability, a ranking order of the plurality of content items; determining, based on metadata associated with the plurality of content items, a time of availability for each of the plurality of content items. On the other hand, Zhang discloses determining, based on the time of availability, a ranking order of the plurality of content items [Each of the rankings 600 ranks a set of users that will have access to a media item at a known time. For example, “The New Show” may be scheduled to become accessible to users of the media system server 110 (or subsets of global users in the United States, Canada, and Mexico) on Dec. 15, 2016. The intermediate period ranking 600B may be a promotional period during which pre-availability elements are displayed to users in order to increase awareness of and promote viewing of “The New Show.” The length of the intermediate period ranking 600B may vary from a week to a month or more, and may vary for each media item being promoted, paragraph 45]; determining based on metadata associated with the plurality of content items, a time of availability for each of the plurality of content items [FIG. 4A is an illustration showing an exemplary cover page for a content digest 300. In this example, section 402 indicates that the cover page 400 belongs to a Wednesday morning digest. In addition to the text 404, an icon 406 indicative of the time of publication is also included., paragraph 68 (FIG. 4A is an illustration showing an exemplary cover page for a content digest 300. In this example, section 402 indicates that the cover page 400 belongs to a Wednesday morning digest. In addition to the text 404, an icon 406 indicative of the time of publication is also included.)]. It would have been obvious to one of ordinary skill in the art to modify Huang with Zhang’s availability-based ranking techniques in order to improve the relevance and timeliness of presented content items. Zhang teaches ranking content items based on availability timing, and applying this known technique to Huang’s search-result ranking system would have yielded predictable results.
As per claim 2, Zhang discloses wherein determining the plurality of the popular topics for the time period comprises: receiving at least one of: a listing of most received search queries for the time period or a listing of most used hashtag topics for the time period, wherein determining the plurality of popular topics comprises determining, based on at least one of: the listing of most received search queries for the time period or the listing of the most used hashtag topics for the time period, the plurality of popular topics [FIG. 4A is an illustration showing an exemplary cover page for a content digest 300. In this example, section 402 indicates that the cover page 400 belongs to a Wednesday morning digest. In addition to the text 404, an icon 406 indicative of the time of publication is also included. Image 408 displays a pattern in FIG. 4A, and may contain other information and graphics as well, paragraph 68].
As per claim 3, Huang discloses wherein determining the plurality of content items associated with at least one of the plurality of popular search query comprises: determining, a plurality of content segments for a first content item of the plurality of content items; and determining, at least a portion of detected text of a first content segment of the plurality of content segments is associated with at least one of the plurality of popular search query [Word segmentation processing is performed respectively for the query set Q of the user, a set D of clicked webpages and a set E of the clicked relevant entities in the second time period to respectively obtain word sets, paragraph 94].
As per claim 4, Huang discloses wherein causing output of at least a portion the plurality of content items in the ranking order comprises causing output of an indicator of a portion of the first content item comprising the first content segment [obtaining a set of queries and a set of clicked search results of the user in the second time period; performing a word segmentation process for the set of queries and the set of search results, and solving a union to obtain a word set; performing an encoding process for the word set by using PV-DBOW, to obtain the vector representation of the search history information of the user in the second time period, paragraph 161].
As per claim 5, Huang discloses wherein the ranking order comprises ranking the plurality of content items in order from a most recent output time to a least recent output time [determining scores presented by the ranking model to the search results according to a first similarity and a second similarity, the first similarity is a similarity between an integration of a vector representation of the sample query and a vector representation of the search history information in the first time period, paragraph 23].
As per claim 6, Huang discloses wherein the indicator for the at least the portion of the plurality of content items comprises at least one of: a title of a content item of the plurality of content items; an image associated with the content item of the plurality of content items, or a content channel name for a content channel associated with the content item of the plurality of content items [When the vector representations of the clicked webpages are determined, the neural network may be employed to encode the titles of the clicked webpages, paragraph 89].
As per claim 7, Zhang discloses receiving, by the computing device, the plurality of content items from at least one content source [FIGS. 7A-7C illustrate aspects of an exemplary article containing multiple content items, paragraph 33].
As per claim 13, Huang discloses wherein the popular search query comprises at least one of a most searched query or a hashtag topic for the time period [entity ranking of the entity ranking model tends to perform entity recommendation according to the most frequently-mentioned meaning of the query. As for an ambiguous query, in addition to the most frequently-mentioned meaning, the entity click data corresponding to less-mentioned and seldom-mentioned meanings are all very sparse, paragraph 130].
As per claim 14, Huang discloses wherein determining the plurality of content items comprising the detected text associated with the popular search query comprises: determining, a plurality of content segments for a first content item of the plurality of content items; and determining, at least a portion of the detected text of a first content segment of the plurality of content segments is associated with the popular search query [Word segmentation processing is performed respectively for the query set Q of the user, a set D of clicked webpages and a set E of the clicked relevant entities in the second time period to respectively obtain word sets, paragraph 94].
As per claim 15, Zhang discloses wherein ranking the plurality of content items comprises ranking the plurality of content items in order from a most recent time of availability to a least recent time of availability [The media item catalog 400 may further include availability information 412, paragraph 33].
As per claim 16, Huang discloses receiving, by the computing device, a second popular search query for the time period; determining a second plurality of content items comprising second detected text associated with the second popular search query; and ranking, based on an output time for each of the second plurality of content items, the second plurality of content items [The short-term search history may be regarded as context information of the current query, and reflect the user's short-term instant interest, paragraph 76].
As per claim 17, Zhang discloses wherein ranking the plurality of content items comprises: determining a first portion of the plurality of content items associated with a content source [[FIGS. 7A-7C illustrate aspects of an exemplary article containing multiple content items, paragraph 33]; and determining, based on the output time, a ranking order of the first portion of the plurality of content items associated with the content source [analyzing the content items (204), ranking the content items (206), Fig. 2A].
As per claim 18, Huang discloses receiving, by a computing device, a plurality of popular search queries for a time period [obtaining a current query of a user, search history information of the user in a first time period, paragraph 7]; determining, based on metadata associated with the plurality of content items, detected text for each of the plurality of content items [The short-term search history may be regarded as context information of the current query, and reflect the user's short-term instant interest, paragraph 76]; determining at least a portion of the detected text is associated with at least one of the plurality of popular search queries [an output of the ranking model includes scores of search results, paragraph 51]; and generating, based on the weighted value, a ranking of the plurality of content items [performing weighting process for the vector representations of the queries in the query sequence and vector representations of clicked search results corresponding to the queries by using an attention mechanism, to obtain the vector representation of the search history information of the user in the first time period, paragraph 28].However Huang does not disclose determining, based on a recency of a time of availability for each of the plurality of content items, a weighted value for each of the plurality of content items; causing, by the computing device and at a user device, based on the ranking, output of an indicator of at least a portion of the plurality of content items. On the other hand, Zhang discloses determining, based on a recency of a time of availability for each of the plurality of content items, a weighted value for each of the plurality of content items [FIG. 4A is an illustration showing an exemplary cover page for a content digest 300. In this example, section 402 indicates that the cover page 400 belongs to a Wednesday morning digest. In addition to the text 404, an icon 406 indicative of the time of publication is also included., paragraph 68 (FIG. 4A is an illustration showing an exemplary cover page for a content digest 300. In this example, section 402 indicates that the cover page 400 belongs to a Wednesday morning digest. In addition to the text 404, an icon 406 indicative of the time of publication is also included.)]; causing, by the computing device and at a user device, based on the ranking, output of an indicator of at least a portion of the plurality of content items [The media item catalog 400 may further include availability information 412, paragraph 33]. It would have been obvious to one of ordinary skill in the art to modify Huang with Zhang’s availability-based ranking techniques in order to improve the relevance and timeliness of presented content items. Zhang teaches ranking content items based on availability timing, and applying this known technique to Huang’s search-result ranking system would have yielded predictable results.
As per claim 20, Zhang discloses wherein the weighted value is greater for a more recent time of availability of a particular content item and less for a less recent time of availability of another particular content item [The media item catalog 400 may further include availability information 412, paragraph 33].
As per claim 21, Huang discloses, wherein the indicator for the at least the portion of the plurality of content items comprises at least one of: a title of a content item of the at least the portion of the plurality of content items [When the vector representations of the clicked webpages are determined, the neural network may be employed to encode the titles of the clicked webpages, paragraph 89]; an image associated with the content item of the at least the portion of the plurality of content items, or a content channel name for a content channel associated with the content item of the at least the portion of the plurality of content items.
As per claim 22, Huang discloses, wherein receiving the plurality of [[the]] popular search queries for the time period comprises receiving at least one of: a listing of most received search queries for the time period or a listing of most used hashtag topics for the time period [entity ranking of the entity ranking model tends to perform entity recommendation according to the most frequently-mentioned meaning of the query. As for an ambiguous query, in addition to the most frequently-mentioned meaning, the entity click data corresponding to less-mentioned and seldom-mentioned meanings are all very sparse, paragraph 130].
Claim 12 is rejected under 35 USC 103(a) as being unpatentable over HUANG et al. (US 20220237251 A1) (hereinafter Huang) In view of Zhang et al. (US 20170031654 A1) (hereinafter Zhang) further in view of Sloo (US 8006268 B1) (hereinafter Sloo).
As per claim 12, The rejection of claim 12 is incorporated by claim 10 above. However the combination of references cited do not teach or suggest wherein the detected text comprises at least one of: closed- captioning text or metadata. On the other hand, Sloo discloses wherein the detected text comprises at least one of: closed- captioning text or metadata [a broadcast news segment or a portion of a documentary can be recorded, as opposed to the entire program specified by EPG data. A viewer can use client device 106 to specify a time duration threshold around the occurrence of the words and phrases in the closed captioning text so that only that portion within the specified threshold would be recorded, col. 9, line 7]. All references Huang, Zhang and are in the same field of endeavor of searching a query. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the search result ranking model scores as taught by Huang with the gather, rank, categorize, and perform other processing of various types of content as disclosed in Zhang with the textual data that matches with search parameter as disclosed in Sloo to determine search results in an electronic device to improve the problem of inaccurate relevant entities for ambiguous queries.
Allowable Subject Matter
Claims 8-9 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 following is a statement of reasons for the indication of allowable subject matter:
The primary reason for objection to claim s8-9 is because the references cited do not teach or suggest “wherein determining the ranking order of the plurality of content items comprises: determining a first portion of the plurality of content items associated with a first topic of the plurality of popular topics; and determining, based on the output time, a ranking order of the first portion of the plurality of content items; wherein determining the ranking order of the first portion of the plurality of content items further comprises: determining a portion of the first portion of the plurality of content items associated with a content source; and determining, based on the output time, a ranking order of the portion of the first portion of the plurality of content items associated with the content source.”.
Remarks
Claims 1-10, 12-18 and 20-22 maintained rejected under the 35 USC 101 as explained above.
Applicant asserted, page 13, that the cited reference does not disclose “determining, by a computer device, a plurality of popular search queries for a time period”.
Examiner respectfully disagrees with this assertion. The Huang reference, paragraph [0051] discloses the training target comprising: maximizing a relevancy degree between the conditions of search results being clicked and the scores of the search results. This disclosure necessarily requires the system to monitor and evaluate user search queries and associated click frequencies over accumulated search sessions. A person of ordinary skill in the art would understand that search queries producing repeated user interactions and clicked results inherently correspond to queries that are more frequently submitted and therefore “popular” within a given time period. In order to maximize relevance based on user click behavior, the system must gather historical query data over time and identify those queries receiving significant user engagement. Such processing inherently involves determining a plurality of search queries that are popular during a monitored interval. Additionally, Huang’s relevance training process relies on aggregated user behavior data rather than isolated single-query events. The use of accumulated click-through information implies temporal collection and analysis of multiple search requests across users and/or sessions. Therefore, Huang reasonably teaches or at least suggests determining popular search queries for a time period, as claimed.
Applicant asserted, page 15, that the cited reference does not disclose “determining, based on the time of availability, a ranking order of the plurality of content items," as claimed.
Examiner respectfully disagrees with this assertion. The Huang reference, paragraph [0023], discloses training a ranking model with the training samples to achieve a preset training target; an input of the ranking model comprising the sample query, the search history information of the user in the first time period before inputting the sample query, the search history information of the user in the second time period before inputting the sample query, and search results corresponding to the sample query, and an output of the ranking model including scores of the search results; determining scores presented by the ranking model to the search results according to a first similarity and a second similarity, the first similarity is a similarity between an integration of a vector representation of the sample query and a vector representation of the search history information in the first time period. Huang explicitly discloses a ranking model that determines scores for search results using user search history information associated with different time periods. Specifically, paragraph [0023] discloses that the ranking model receives as input: (1) a sample query, (2) search history information from a first time period before the query, (3) search history information from a second time period before the query, and (4) corresponding search results. Huang further discloses that the model outputs scores for the search results based on similarities derived from those temporally segmented histories.
A person of ordinary skill in the art would recognize that the “first time period” and “second time period” constitute temporal availability information associated with the underlying content and user interactions. Huang’s ranking model explicitly evaluates and weights search information according to these different time-based data sets. The resulting scores are then used to rank the search results, thereby determining a ranking order of the content items based on temporal information.
Further, Huang’s disclosure of determining scores according to similarities between the query representation and search history representations from different time periods demonstrates that time-dependent availability and recency information directly affect the ranking outcome. Because the model produces ranking scores using information segmented by time periods, the ranking order is necessarily determined based on the temporal availability of the relevant information/content reflected in those periods. Additionally, one of ordinary skill in the art would understand that ranking search results using data from distinct historical time windows inherently prioritizes content differently depending on when the information was available or interacted with. Thus, Huang teaches using time-based availability information as a factor in generating the ranking order of multiple content items.
Conclusion
THIS ACTION IS MADE FINAL. 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 extension fee 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 Noosha Arjomandi whose telephone number is (571) 272-9784. The examiner can normally be reached on Monday through Friday, 8:30am - 6:00pm. E.S.T..
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sanjiv Shah can be reached on (571)272-4098. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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May 11, 2026
/NOOSHA ARJOMANDI/Primary Examiner, Art Unit 2166
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