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 .
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 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.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/15/2025 has been entered.
Examiner Notes
(1) In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention. This will assist in expediting compact prosecution. MPEP 714.02 recites: “Applicant should also specifically point out the support for any amendments made to the disclosure. See MPEP § 2163.06. An amendment which does not comply with the provisions of 37 CFR 1.121 (b), (c), (d), and (h) may be held not fully responsive. See MPEP § 714.” Amendments not pointing to specific support in the disclosure may be deemed as not complying with provisions of 37 C.F.R. 1.131 (b), (c), (d), and (h) and therefore held not fully responsive. Generic statements such as "Applicants believe no new matter has been introduced" may be deemed insufficient.
(2) Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Response to Arguments
Applicant’s amendments to the claims have overcome 101 rejections previously set forth in the Non-Final Office Action mailed 12/15/2025.
Regarding 35 U.S.C. 103, applicant’s arguments with respect to claims 1, 13 and 14 have been considered but are moot in view of the new ground(s) of rejection (See new references of ROSSET and QUAMAR).
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 of this title, 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 1-2, 13-15, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Hasan et al. (U.S. Patent No. 9,858,608 B2) in view of ROSSET et al. (U.S. Pub. No. 2021/0326742 A1), further in view of QUAMAR et al. (U.S. Pub. No. 2022/0277031 A1).
Regarding claim 1, Hasan teaches a method of suggesting search queries, including:
for a search session obtained from a media-providing service: receiving one or more user-input search queries (Fig. 5B, col. 5, a shopper types ‘dora the explorer doll’…);
determining, based on interactions with each user-input search query of the one or more user-input search queries, whether the search session satisfies success criteria (Fig. 10, col. 9, line 4-6 and line 13-22, once such database is query log having a given number of sessions, each session comprising a sequence of queries followed by a purchase-related event; queries can be used in user sessions from historical logs as training data to build the query suggestion index…; each session stores date, time, page type ,guid and a set of user event sorted by time; some example events includes executing query, viewing/clicking on search result, …; query suggestion can be built using query suggestion module…; the ranking function is composed of both popularity and the purchase-efficiency score…; noted, purchase-efficiency score is an indication of search session satisfies success criteria);
generating a graph that includes, for a plurality of search sessions that satisfy the success criteria (col. 14, line 32-45, one could also build a graph from a user activities history which includes searches, bins, bid, ask seller a question, watches, views, offers; each query seen in the user activity is a node on this graph): a first set of nodes, each node in the first set of nodes corresponding to a respective search query one or more user-input search queries in a respective search session (col. 14, line 32-45, one could also build a graph from a user activities history which includes searches, bins, bid, ask seller a question, watches, views, offers; each query seen in the user activity is a node on this graph; queries can be used in user sessions from historical logs as training data to build the query suggestion index…; each session stores date, time, page type ,guid and a set of user event sorted by time; also see col. 4, the query identification module 222 may be used to identify queries during the time periods and/or an additional time period).
Hasan does not explicitly disclose:
a second set of nodes, each node in the second set of nodes corresponding to a respective content item selected from a respective search query of the one or more user-input search queries in a respective search session.
ROSSET teaches: a second set of nodes, each node in the second set of nodes corresponding to a respective content item selected from a respective search query of the one or more user-input search queries in a respective search session (paragraph [0108]-[0109], mines a historical click log provided in the data store; including a query actually submitted by the user during a search session, a suggestion, that was actually served to a user by the search engine in response to the query, and a label; for a positive example, the label indicates that the user selected the suggestion; the search engine may store these queries in a historical queries log; a training example for this case includes a query that was actually submitted by a user during a search session; for a given query and for a given suggestion under consideration, a rate (e.g., click through rate or CTR) at which a plurality of users clicked on the suggestion after submitted the query; in combination with the graph taught by Hasan, it reads on as claimed).
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include said above limitations into query recommendation of Hasan.
Motivation to do so would be to include said above limitations to reduce the number of queries needs to submit to accomplish his or her search object; this reduce the burden on the user, saves times, and reduces the expenditure of computing resources (ROSSET, paragraph [0062], line 5-9).
Hasan as modified by ROSSET do not explicitly disclose: converting, using a graph neural network (GNN), the first set of nodes to a first set of vectors in a vector space.
QUAMAR teaches: converting, using a graph neural network (GNN), the first set of nodes to a first set of vectors in a vector space […] (paragraph [0064], after encoding the graph query as a graph, a Graph Neural Network (GNNs) can be used to convert a graph into a vector representation).
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include said above limitations into query recommendation of Hasan.
Motivation to do so would be to include said above limitations to provide effective and continuous guidance support in the conversation service (QUAMAR, paragraph [0002], line 13-14).
Hasan as modified by ROSSET and QUAMAR further teach:
the first set of vectors representing at least a subset of the first set of nodes; and the second set of nodes to a second set of vector in the vector space, the second set of vector representing at least a subset of the second set of nodes (paragraph [0087], generate intent vectors associated with respective queries in a search session; also see paragraph [0108]-[0109], mines a historical click log provided in the data store; including a query actually submitted by the user during a search session, a suggestion, that was actually served to a user by the search engine in response to the query, and a label; for a positive example, the label indicates that the user selected the suggestion; also see paragraph [0125], generates the machine-trained model for use by the intent-generating component by iteratively decrease the distances in the intent vector space between intent vectors associated with positive examples; noted, “intent vectors associated with respective queries” is interpreted as “a first set of vector” and “intent vectors associated with positive examples” is interpreted as “second set of vector in the vector space”);
receiving a new user-input search query (ROSSET, Fig. 14, item 1404 illustrates receiving user input query);
converting the new user-input search query to a new vector in the vector space (ROSSET, Fig. 14, paragraph [0055], using machine-trained model to map a query into an intent vector);
selecting a recommended search query based on a comparison of distances between the new vector and respective ones of the first set of vectors and/or the second set of vectors (ROSSET, paragraph [0126], computing the distance between each pair of queries, and produces an edge between queries having intent vectors that are separated by no more than a prescribed distance);
displaying, in a user interface of a media application of the media-providing service, the recommended search query as a selectable element (ROSSET, paragraph [0132], generating output information to be sent to the user computing device that includes the at least one suggestion, and send the output information to the user device; receiving the user reply from the user to the at least one suggestion in response to interaction by the user with a user interface provided by the user computing device);
receiving a user input selecting the recommended search query displayed as the selectable element (ROSSET, paragraph [0132], receiving the user reply from the user to the at least one suggestion in response to interaction by the user with a user interface provided by the user computing device);
and in response to receiving the user input: updating the user interface with the recommended search query; and performing a search using the recommended search query (ROSSET, Fig. 2, paragraph [0132], receiving the user reply from the user to the at least one suggestion in response to interaction by the user with a user interface provided by the user computing device; also see paragraph [0053], presenting four suggestions; the suggestions take the form of questions; the browser application running on the computing device to submit the question to the query processing system as next query; also see paragraph [0051], formulates the output information into one or more search results pages).
Regarding claim 2, Hasan as modified by ROSSET and QUAMAR teach all claimed limitations as set forth in rejection of claim 1, further teach wherein the search session is determined based on a heuristic for identifying one or more search queries that belong to the search session (Hasan, Fig. 10, col. 9, line 4-6 and line 13-22, once such database is query log having a given number of sessions, each session comprising a sequence of queries followed by a purchase-related event; also see col. 4, the query identification module 222 may be used to identify queries during the time periods and/or an additional time period).
As per claims 13-14, these claims are rejected on grounds corresponding to the same rationales given above for rejected claim 1 and are similarly rejected.
As per claim 15, this claim is rejected on grounds corresponding to the same rationales given above for rejected claim 2 and is similarly rejected.
As per claim 21, this claim is rejected on grounds corresponding to the same rationales given above for rejected claim 2 and is similarly rejected.
Claims 3 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Hasan et al. (U.S. Patent No. 9,858,608 B2) in view of ROSSET et al. (U.S. Pub. No. 2021/0326742 A1), and QUAMAR et al. (U.S. Pub. No. 2022/0277031 A1), further in view of Ahmad et al. (“Context Attentative Document Ranking and Query Suggestions”; Jun 2019).
Regarding claim 3, Hasan as modified by ROSSET and QUAMAR teach all claimed limitations as set forth in rejection of claim 1, but do not explicitly disclose: wherein the graph further includes a first set of edges between two or more nodes, wherein each edge in the first set of edges connects, for a respective search query, a node from the first set of nodes corresponding to the respective search query with a node from the second set of nodes corresponding to the respective content item selected from the respective search query.
Ahmad teaches: wherein the graph further includes a first set of edges between two or more nodes, wherein each edge in the first set of edges connects, for a respective search query, a node from the first set of nodes corresponding to the respective search query with a node from the second set of nodes corresponding to the respective content item selected from the respective search query (Ahmad, page 3, Fig. 1 illustrates clicked document [node] respective to session query [node]).
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include wherein the graph further includes a first set of edges between two or more nodes, wherein each edge in the first set of edges connects, for a respective search query, a node from the first set of nodes corresponding to the respective search query with a node from the second set of nodes corresponding to the respective content item selected from the respective search query into query recommendation of Hasan.
Motivation to do so would be to include wherein the graph further includes a first set of edges between two or more nodes, wherein each edge in the first set of edges connects, for a respective search query, a node from the first set of nodes corresponding to the respective search query with a node from the second set of nodes corresponding to the respective content item selected from the respective search query to address issue with none of the multi-task retrieval solutions model the sequential dependency across different retrieval task; this inevitably limits their ability in exploiting information buried in a user’s search sequence (Ahmad, page 1, right column, 2nd paragraph).
As per claim 16, this claim is rejected on grounds corresponding to the same rationales given above for rejected claim 3 and is similarly rejected.
Claims 4 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Hasan et al. (U.S. Patent No. 9,858,608 B2) in view of ROSSET et al. (U.S. Pub. No. 2021/0326742 A1), QUAMAR et al. (U.S. Pub. No. 2022/0277031 A1), and Ahmad et al. (“Context Attentative Document Ranking and Query Suggestions”; Jun 2019), further in view of HAO et al. (“Mining Web Graphs for Recommendation”; IEEE Transactions on Knowledge and Data Engineering, Vol. 24, No. 6, June 2012).
Regarding claim 4, Hasan as modified by ROSSET, QUAMAR, and Ahmar teach all claimed limitations as set forth in rejection of claim 3, but do not explicitly disclose: wherein the first set of edges comprises a set of bidirectional edges (HAO, page 1057, Fig. 2b shown the graph includes edges comprises a set of bidirectional edges).
HAO teaches: wherein the first set of edges comprises a set of bidirectional edges (HAO, page 1057, Fig. 2b shown the graph includes edges comprises a set of bidirectional edges).
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include wherein the first set of edges comprises a set of bidirectional edges into query recommendation of Hasan.
Motivation to do so would be to include wherein the first set of edges comprises a set of bidirectional edges which can be utilized to many recommendation tasks on the web (HAO, page 1052, left column).
As per claim 17, this claim is rejected on grounds corresponding to the same rationales given above for rejected claim 4 and is similarly rejected.
Claims 7 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Hasan et al. (U.S. Patent No. 9,858,608 B2) in view of ROSSET et al. (U.S. Pub. No. 2021/0326742 A1), and QUAMAR et al. (U.S. Pub. No. 2022/0277031 A1), further in view of HAO et al. (“Mining Web Graphs for Recommendation”; IEEE Transactions on Knowledge and Data Engineering, Vol. 24, No. 6, June 2012).
Regarding claim 7, Hasan as modified by ROSSET, and QUAMAR teach all claimed limitations as set forth in rejection of claim 1, but do not explicitly disclose: wherein the recommended search query is selected by: receiving a user input corresponding to a node in the vector space.
HAO teaches: wherein providing the recommendation includes: receiving a user input corresponding to a node in the vector space (HAO, page 1057, given a query g in V+…; start the diffusion processing…)
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include wherein providing the recommendation includes: receiving a user input corresponding to a node in the vector space into query recommendation of Hasan.
Motivation to do so would be to include wherein providing the recommendation includes: receiving a user input corresponding to a node in the vector space which can be utilized to many recommendation tasks on the web (HAO, page 1052, left column).
Hasan as modified by Hasan as modified by ROSSET, QUAMAR and HAO further teach: determining a nearest neighbor node in the vector space relative to the node corresponding to the received user input (HAO, page 1054-1055, diffusion process…; the related heat curve is shown in Fig. 1b, we can see that the node 2, the closest node to the heat source, gain more heat than other nodes… ); and providing a suggested query corresponding to the determined nearest neighbor node (HAO, page 1057, given a query g in V+…; start the diffusion processing…; output the Top-K queries with the largest values in vector F(1) as the suggestions).
As per claim 20, this claim is rejected on grounds corresponding to the same rationales given above for rejected claim 7 and is similarly rejected.
Claims 5-6, 10 and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Hasan et al. (U.S. Patent No. 9,858,608 B2) in view of ROSSET et al. (U.S. Pub. No. 2021/0326742 A1), and QUAMAR et al. (U.S. Pub. No. 2022/0277031 A1), further in view of MAO et al. (“A social-knowledge-directed Query Suggestion Approach for Exploratory Search”; 2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery).
Regarding claim 5, Hasan as modified by ROSSET, and QUAMAR teach all claimed limitations as set forth in rejection of claim 1, but do not explicitly teach wherein the graph further includes a second set of edges between two or more nodes in the graph, each edge in the second set of edges determined, for a respective search session that satisfies the success criteria, between a node representing a respective query in the respective search session and a node corresponding to the last query in the respective search session.
MAO teaches: wherein the graph further includes a second set of edges between two or more nodes in the graph, each edge in the second set of edges determined, for a respective search session that satisfies the success criteria, between a node representing a respective query in the respective search session and a node corresponding to the last query in the respective search session (MAO, page 3, left column, Fig. 1 shown the graph includes edges between two or more nodes connecting the query and the respective URL; let Q = {q1, q2, ..., qN} be the set of N unique queries submitted to a search engine during a specific period of time. Let D = {d1, d2, ..., dM} be the set of M URLs clicked for those queries; construct a query-URL bipartite graph G=; construction of the query-URL bipartite graph G=(V,E) whose vertices V are the union of these, V=Q Ս D, and every edge in E connect two classes of vertices: one in the query set Q and the other in the URL set D; the pair (q,d) is an edge of E if and only if there is a user who clicked on URL d after submitting the query q; each edge E is assigned a weight given by click count Cik; noted, the click count in response to query is an indication that the user satisfying the success criteria).
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include wherein the graph further includes a second set of edges between two or more nodes in the graph, each edge in the second set of edges determined, for a respective search session that satisfies the success criteria, between a node representing a respective query in the respective search session and a node corresponding to the last query in the respective search session into query recommendation of Hasan.
Motivation to do so would be to include wherein the graph further includes a second set of edges between two or more nodes in the graph, each edge in the second set of edges determined, for a respective search session that satisfies the success criteria, between a node representing a respective query in the respective search session and a node corresponding to the last query in the respective search session that uses both semantic relevancy and social knowledge to suggest diversified queries in a long-tail distribution (MAO, page 2, left column, line 1-3).
Regarding claim 6, Hasan as modified by ROSSET, QUAMAR and MAO teach all claimed limitations as set forth in rejection of claim 5, further teach wherein the second set of edges comprises a set of unidirectional edges, wherein each unidirectional edge directs a node representing a respective query in the respective search session and to the last query in the respective search session without directing the last query in the respective search session to the node representing the respective query in the respective search session (MAO, page 3, left column, Fig. 1 shown the graph includes shown the graph includes edges comprises unidirectional edge; unidirectional edge edges between two or more nodes connecting the query and the respective URL; let Q = {q1, q2, ..., qN} be the set of N unique queries submitted to a search engine during a specific period of time. Let D = {d1, d2, ..., dM} be the set of M URLs clicked for those queries; construct a query-URL bipartite graph G=; construction of the query-URL bipartite graph G=(V,E) whose vertices V are the union of these, V=Q Ս D, and every edge in E connect two classes of vertices: one in the query set Q and the other in the URL set D).
Regarding claim 10, Hasan as modified by ROSSET, and QUAMAR teach all claimed limitations as set forth in rejection of claim 1, but do not explicitly disclose: wherein converting the first set of nodes and the second set of nodes of the graph to the vector space includes performing random walks.
MAO: wherein converting the first set of nodes and the second set of nodes of the graph to the vector space includes performing random walks (page 3, Fig. 1, left column, let Q = {q1, q2, ..., qN} be the set of N unique queries submitted to a search engine during a specific period of time. Let D = {d1, d2, ..., dM} be the set of M URLs clicked for those queries; construct a query-URL bipartite graph G=; construction of the query-URL bipartite graph G=(V,E) whose vertices V are the union of these, V=Q Ս D, and every edge in E connect two classes of vertices: one in the query set Q and the other in the URL set D; noted, “URL in the set D” are interpreted as a second set of nodes ; also see page 5, run random walk n-steps to get a new vector v’=vPn…; in combination with the teaching of first set of nodes and second set of nodes by Hasan and Ahmad, it reads on as claimed).
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include wherein converting the first set of nodes and the second set of nodes of the graph to the vector space includes performing random walks into query recommendation of Hasan.
Motivation to do so would be to include wherein converting the first set of nodes and the second set of nodes of the graph to the vector space includes performing random walks that uses both semantic relevancy and social knowledge to suggest diversified queries in a long-tail distribution (MAO, page 2, left column, line 1-3).
As per claims 18-19, these claims are rejected on grounds corresponding to the same rationales given above for rejected claim 5-6 respectively and are similarly rejected.
Claims 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Hasan et al. (U.S. Patent No. 9,858,608 B2) in view of ROSSET et al. (U.S. Pub. No. 2021/0326742 A1), and QUAMAR et al. (U.S. Pub. No. 2022/0277031 A1), further in view of Bellingham et al. (U.S. Patent No. 11,960,446 B2).
Regarding claim 8, Hasan as modified by ROSSET, and QUAMAR teach all claimed limitations as set forth in rejection of claim 1, but do not explicitly disclose: wherein the graph further includes a third set of nodes, each node in the third set of nodes corresponding to metadata associated with the respective content item.
Bellingham teaches: wherein the graph further includes a third set of nodes, each node in the third set of nodes corresponding to metadata associated with the respective content item (col. 5, line 46-60, for a graph nodes, including enhanced metadata nodes, to form a client graph…; such as the nodes that represent a Root (Home menu), a Genre Menu, a Series menu,… and so on…; a “Genre menu” with a corresponding genre node…; also see col. 8, line 23-45, eventually by traversing the graph, …., a menu node is reached that has a node containing the information for a playable content item…; for example the node 240 represents some movie ‘X’; also see col. 4, line 33-38, data service may link any metadata node to any other node representing content or enhanced content…).
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include wherein the graph further includes a third set of nodes, each node in the third set of nodes corresponding to metadata associated with the respective content item into query recommendation of Hasan.
Motivation to do so would be to include wherein the graph further includes a third set of nodes, each node in the third set of nodes corresponding to metadata associated with the respective content item to allow interested client to explore more information, as well as to lay the video and switch between viewing the video playback in regular playback mode and interacting with the metadata (Bellingham, col. 3, line 21-24).
Regarding claim 9, Hasan as modified by ROSSET, QUAMAR and Bellingham teach all claimed limitations as set forth in rejection of claim 8, further teach wherein the metadata includes a topic or a genre (Bellingham, col. 5, line 46-60, for a graph node, including enhanced metadata nodes, to form a client graph…; such as the nodes that represent a Root (Home menu), a Genre Menu, a Series menu,… and so on…; a “Genre menu” with a corresponding genre node…).
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Hasan et al. (U.S. Patent No. 9,858,608 B2) in view of ROSSET et al. (U.S. Pub. No. 2021/0326742 A1), and QUAMAR et al. (U.S. Pub. No. 2022/0277031 A1), further in view of Thomas et al., (U.S. Pub. No. 2007/0162502 A1).
Regarding claim 12, Hasan as modified by ROSSET, and QUAMAR teach all claimed limitations as set forth in rejection of claim 1, but do not explicitly disclose: wherein the success criteria are satisfied in accordance with a determination that a document is streamed, downloaded, and/or added to library.
Thomas teaches: wherein the success criteria are satisfied in accordance with a determination that a document is streamed, downloaded, and/or added to library (paragraph [0081], if the user finds an advertisement (or content associated with advertisement) from the search results desirable and place it in the media library; noted, by placing it in the media library when the user finds the search result desirable, that reads on wherein the success criteria are satisfied in accordance with a determination that a document is streamed, downloaded, and/or added to library as claimed; also see paragraph [0077], [0079])
It would have been obvious to one of ordinary skill in art before the effective filing date of the claim invention to include wherein the success criteria are satisfied in accordance with a determination that a document is streamed, downloaded, and/or added to library into query recommendation of Hasan.
Motivation to do so would be to include wherein the success criteria are satisfied in accordance with a determination that a document is streamed, downloaded, and/or added to library to be desirable to identify and select content and/or bookmarks for the media library using any suitable means, including searching for content, receiving recommendation for content, and directly entering content identification information (Thomas, paragraph [0005], line 4-9).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEN HOANG whose telephone number is (571)272-8401. The examiner can normally be reached M-F 7:30am-5:00pm.
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/KEN HOANG/ Examiner, Art Unit 2168