DETAILED ACTION
This action is responsive to application filed on May 11, 2026.
The amendments filed on May 11, 2026 have been acknowledged and considered.
Claims 21, 28 and 34 have been amended.
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 .
Response to Amendment
Applicant's Remarks, filed May 11, 2026, has been fully considered and entered.
Accordingly, Claims 21-40 are pending in this application. Claims 21, 28 and 34 have been amended. Claim 13 has been canceled. Claims 21, 28 and 34 are independent claims. In light of applicant amendments, the objection to the specification because of informalities has been withdrawn.
Response to Arguments
Applicant’s arguments, see pages 10-12, filed May 11, 2026, with respect to the rejection of claims 21-40 under 35 U.S.C 103 have been fully considered, but they are moot in view of new grounds of rejection necessitated by amendment. Applicant arguments with respect of the non-statutory double patenting rejections have been fully considered, but they are not persuasive.
Argument: “the current amendment to claim 21 distinguishes claim 21 from the claims of the '058 and '178 patents… claim 21 as currently amended includes subject matter that is not already recited in the claims of the '058 patent… claim 21 as currently amended is not obvious over the claims of the '178 patent. Nonetheless, in the interest of advancing prosecution, Applicant has filed a terminal disclaimer to U.S. Patent No. 11,847,178 and U.S. Patent No. 12,299,058. Applicant therefore respectfully requests the withdrawal of the rejections on the ground of nonstatutory double patenting.”
Response to Argument: Examiner respectfully disagrees. Claim 12 of each of the ‘058 and ‘178 patents recites detecting that the representation of the first concept has been repositioned to a new location in the multidimensional canvas by the user and, in response, repositioning the representation of the document clips such that representations of document clips more semantically similar to the first concept move closer to the new location of the representation of the first concept. The only difference made in the amended claim language is that it perform the updating of the document representation dynamically during the repositioning, rather than in response to detecting that the repositioning has occurred, which is at most an obvious variant of the patented claims, and as explicitly taught by Ramos in the updated double patenting rejections below. Regarding the terminal disclaimer, the Examiner notes that no terminal disclaimer has been filed for the instant application. The double patenting rejections are maintained.
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.
Claims 21-40 are 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 joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding independent claims 21, 28 and 24, each claim recite "receiving [receive] a user input that specifies a repositioning of the concept embedding.” The “concept embedding” is a semantic vector generated from a concept definition, it is the “concept representation” not the embedding that has a position on the recited canvas, as confirmed by following limitation “update a position of the concept representation as specified by the user input”. It is unclear whether “a repositioning of the concept embedding” refers to a repositioning of the concept representation on the canvas, or a modification of the embedding vector itself (e.g. in an embedding space). For the purpose of examination, and consistent with the specification (See [0024] “the re-finder system may allow the user to interactively reposition the representations of concepts in the graphical user interface and may dynamically update locations of the representations of document clips based on the changing locations of the representations of the concepts in graphical user interface.”), the limitation is interpreted as receiving a user input that specifies a repositioning of the concept representation on the canvas. Dependent claims 22-27, 29-33 and 35-40 are rejected due to their dependency from claims 21, 28 and 34, respectively.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 21-40 are rejected on the ground of nonstatutory double patenting as being unpatentable over the claims 1-3, 5-6 and 13-16 of prior U.S. Patent No. 12,299,058 in view of Ramos (US Patent Application Publication No. US 20190244113 A1). Although the claims at issue are not identical, they are not patentably distinct from each other because they are directed to substantially the same invention, and any differences would have been obvious in view of Ramos.
Instant application
U.S. Patent No. 12,299,058
Claim 21. A system, comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations, the set of operations comprising:
generating a concept embedding based on a concept definition from a user;
evaluating the concept embedding to determine a semantic relationship between the concept embedding and one or more document embeddings corresponding to a set of documents; and
providing, for display to the user, an indication of a graphical user interface (GUI) that indicates the determined semantic relationship corresponding to the concept embedding,
wherein the GUI includes a canvas that spatially represents the concept embedding with a concept representation and spatially represents the one or more document embeddings with one or more document representations, according to the determined semantic relationship between the concept embedding and the one or more document embeddings;
receive a user input that specifies a repositioning of the concept embedding; and
in response to receiving the user input: update a position of the concept representation as specified by the user input; and based at least in part on the determined semantic relationship and the updated position of the concept representation, dynamically update respective positions of the one or more document representations on the canvas during the repositioning.
Claim 13. A system for assisting users in re-finding documents, the system comprising: one or more computer readable storage media; and program instructions stored on the one or more computer readable storage media that, when executed by at least one processor, cause the at least one processor to:
generate, for each concept clip of a set of concept clips that correspond to a concept searched by a user using a machine learning model, an embedding;
generate a concept embedding based on the embeddings of the set of concept clips;
determine a semantic relationship between the concept embedding and one or more document embeddings that each correspond to a document clip of a set of documents; and
generate a graphical user interface based on the determined semantic relationship depicting the semantic relationship between the concept and one or more document clips of the one or more document embeddings.
Claim 22
Claim 14
Claim 23
Claim 15
Claim 24
Claim 15
Claim 25
Claim 15
Claim 26
Claim 16
Claim 27
Claim 13
Claim 28. A method for document re-finding, the method comprising:
generating a concept embedding based on a concept definition from a user;
evaluating the concept embedding to determine a semantic relationship between the concept embedding and one or more document embeddings corresponding to a set of documents;
generating a graphical representation depicting the concept embedding in relation to the one or more document embeddings according to the determined semantic relationship; and
relationship,
wherein the graphical representation includes a canvas that spatially represents the concept embedding with a concept representation and spatially represents the one or more document embeddings with one or more document representations;
providing, for display to the user, the generated graphical representation;
receiving a user input that specifies a repositioning of the concept embedding; and in response to receiving the user input: updating a position of the concept representation as specified by the user input; and based at least in part on the determined semantic relationship and the updated position of the concept representation, dynamically updating respective positions of the one or more document representations on the canvas during the repositioning.
Claim 1. A method for assisting users in re-finding documents, the method comprising:
generating, for each concept clip of a set of concept clips, an embedding, wherein the set of concept clips corresponds to a concept searched by a user;
generating a concept embedding based on the embeddings of the set of concept clips;
determining a semantic relationship between the concept embedding and one or more document embeddings that each correspond to a document clip of a set of documents; and
based on the determined semantic relationship, providing, for display at a client device, an indication of the semantic relationship between the concept and one or more document clips of the one or more document embeddings.
Claim 29
Claim 2
Claim 30
Claim 3
Claim 31
Claim 3
Claim 32
Claim 5
Claim 33
Claim 6
Claim 34. A method for document re-finding, the method comprising:
generating a concept embedding based on a concept definition from a user;
evaluating the concept embedding to determine a semantic relationship between the concept embedding and one or more document embeddings corresponding to a set of documents; and
providing, for display to the user, a graphical user interface (GUI) that indicates the determined semantic relationship corresponding to the concept embedding,
wherein the GUI includes a canvas that spatially represents the concept embedding with a concept representation and spatially represents the one or more document embeddings with one or more document representations, according to the determined semantic relationship between the concept embedding and the one or more document embeddings; receiving a user input that specifies a repositioning of the concept embedding; and in response to receiving the user input: updating a position of the concept representation as specified by the user input; and based at least in part on the determined semantic relationship and the updated position of the concept representation, dynamically updating respective positions of the one or more document representations on the canvas during the repositioning.
Claim 1. A method for assisting users in re-finding documents, the method comprising:
generating, for each concept clip of a set of concept clips, an embedding, wherein the set of concept clips corresponds to a concept searched by a user;
generating a concept embedding based on the embeddings of the set of concept clips;
determining a semantic relationship between the concept embedding and one or more document embeddings that each correspond to a document clip of a set of documents; and
based on the determined semantic relationship, providing, for display at a client device, an indication of the semantic relationship between the concept and one or more document clips of the one or more document embeddings.
Claim 35
Claim 2
Claim 36
Claim 3
Claim 37
Claim 3
Claim 38
Claim 3
Claim 39
Claim 5
Claim 40
Claim 6
Claims 21-40 recite substantially the same subject matter as claims 1-3, 5-6 and 13-16 of US Pat. 12,299,058; however, this patent also fail to particularly show the limitations not in bold above, as this being the only difference between the claims.
However, Ramos teaches a GUI that includes a canvas that spatially represents a user defined concept with a concept representation and spatially represents documents with document representations according to a determined semantic relationship. (See Ramos [0024, 0026] “The exploration pane 100 displays a star coordinate space 102 spanned by anchor concepts 104 (shown as rings) arranged on a circle 106… Interior to the circle 106, data items 108… visually represented by various symbols, are displayed… The positions of the data items 108 depend on the positions of the anchor concepts 104 and… the similarity of the data items 108 to the anchor concepts 104” See also Ramos [0026] teaching the data items are documents such as web pages, and the scores are a cosine similarity (i.e. semantic relationship).) Ramos further teaches receiving a user input that specifies a repositioning of the concept representation as specified and dynamically updating the positions of the document representations on the canvas during the repositioning, based on the semantic relationship and the updated concept position. (See Ramos [0032, 0040] “using anchor concepts 104 to dynamically spread out the data items 108… users may manipulate the locations of the anchor concepts 104 along the circle 106 (e.g., by dragging a selected anchor concept 104)… by changing the position of the anchor concept 104 (e.g., moving it to a new position along the circle 106)… all of these manipulations affect the computation of the positions of the data items in the star coordinate space 102. Accordingly, following any such manipulation… the positions of the visual representations of the data items 108 are updated” See also Ramos [0005] “the user interface allows the user to rearrange the anchor concepts along the circle and, based on his observation of the resulting movement of data items in the plane, optimally spread out the data items”)
It would have been obvious to modify the system and methods of claims 1 and 13 of the ‘058 patent to depict the determined semantic relationship using Ramos’s interactive canvas, in which the concept is spatially represented together with documents and the user may drag the concept representation with the document representations dynamically following (Ramos 0024, 0032, 0040). One would be motivated to do so because Ramos teaches that such canvas lets the user dynamically spread out and visually organize the documents according to their relationship to the concept (Ramos 0005, 0032), thus helping the user locate documents of interest. Because Ramos’s canvas is driven by the same type of concept to document similarity values already determined by the ‘058 patent claims, the combination would yield predictable results.
Claims 21-40 are rejected on the ground of nonstatutory double patenting as being unpatentable over the claims 1-3, 5-6 and 13-16 of prior U.S. Patent No. 11,847,178 in view of Ramos (US Patent Application Publication No. US 20190244113 A1). Although the claims at issue are not identical, they are not patentably distinct from each other because they are directed to substantially the same invention, and any differences would have been obvious in view of Ramos.
Instant application
U.S. Patent No. 11,847,178
Claim 21. A system, comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations, the set of operations comprising:
generating a concept embedding based on a concept definition from a user;
evaluating the concept embedding to determine a semantic relationship between the concept embedding and one or more document embeddings corresponding to a set of documents; and
providing, for display to the user, an indication of a graphical user interface (GUI) that indicates the determined semantic relationship corresponding to the concept embedding,
wherein the GUI includes a canvas that spatially represents the concept embedding with a concept representation and spatially represents the one or more document embeddings with one or more document representations, according to the determined semantic relationship between the concept embedding and the one or more document embeddings;
receive a user input that specifies a repositioning of the concept embedding; and
in response to receiving the user input: update a position of the concept representation as specified by the user input; and based at least in part on the determined semantic relationship and the updated position of the concept representation, dynamically update respective positions of the one or more document representations on the canvas during the repositioning.
Claim 13. A system for assisting users in re-finding documents, the system comprising: one or more computer readable storage media; and program instructions stored on the one or more computer readable storage media that, when executed by at least one processor, cause the at least one processor to:
generate, using a machine learning model, embeddings for document clips related to respective documents among a plurality of documents; receive a first set of concept clips defining a first concept for searching for content of interest to a user in the plurality of documents; generate, using the machine learning model, embeddings for respective concept clips in the first set of concept clips;
generate a first concept embedding based on a combination of the embeddings generated for the respective concept clips in the first set of concept clips;
determine semantic relationships between the first concept and the document clips based on i) the embeddings generated for the document clips and ii) the concept embedding;
generate a graphical user interface depicting the semantic relationships between the first concept and the document clips; and cause display of the graphical user interface to be rendered at a client device, wherein the graphical user interface is operable to enable re-finding a document, among the plurality of documents, having the content of interest to the user.
Claim 22
Claim 14
Claim 23
Claim 15
Claim 24
Claim 15
Claim 25
Claim 15
Claim 26
Claim 16
Claim 27
Claim 13
Claim 28. A method for document re-finding, the method comprising:
generating a concept embedding based on a concept definition from a user;
evaluating the concept embedding to determine a semantic relationship between the concept embedding and one or more document embeddings corresponding to a set of documents;
generating a graphical representation depicting the concept embedding in relation to the one or more document embeddings according to the determined semantic relationship; and
relationship,
wherein the graphical representation includes a canvas that spatially represents the concept embedding with a concept representation and spatially represents the one or more document embeddings with one or more document representations;
providing, for display to the user, the generated graphical representation;
receiving a user input that specifies a repositioning of the concept embedding; and in response to receiving the user input: updating a position of the concept representation as specified by the user input; and based at least in part on the determined semantic relationship and the updated position of the concept representation, dynamically updating respective positions of the one or more document representations on the canvas during the repositioning.
Claim 1. A method for assisting users in re-finding documents, the method comprising:
generating embeddings for document clips related to respective documents among a plurality of documents; receiving a first set of concept clips defining a first concept for searching for content of interest to a user in the plurality of documents; generating embeddings for respective concept clips in the first set of concept clips;
generating a first concept embedding based on a combination of the embeddings generated for the respective concept clips in the first set of concept clips;
determining semantic relationships between the first concept and the document clips based on i) the embeddings generated for the document clips and ii) the concept embedding;
generating a graphical user interface depicting the semantic relationships between the first concept and the document clips; and causing display of the graphical user interface to be rendered at a client device, wherein the graphical user interface is operable to enable re-finding a document, among the plurality of documents, having the content of interest to the user.
Claim 29
Claim 2
Claim 30
Claim 3
Claim 31
Claim 3
Claim 32
Claim 5
Claim 33
Claim 6
Claim 34. A method for document re-finding, the method comprising:
generating a concept embedding based on a concept definition from a user;
evaluating the concept embedding to determine a semantic relationship between the concept embedding and one or more document embeddings corresponding to a set of documents; and
providing, for display to the user, a graphical user interface (GUI) that indicates the determined semantic relationship corresponding to the concept embedding,
wherein the GUI includes a canvas that spatially represents the concept embedding with a concept representation and spatially represents the one or more document embeddings with one or more document representations, according to the determined semantic relationship between the concept embedding and the one or more document embeddings; receiving a user input that specifies a repositioning of the concept embedding; and in response to receiving the user input: updating a position of the concept representation as specified by the user input; and based at least in part on the determined semantic relationship and the updated position of the concept representation, dynamically updating respective positions of the one or more document representations on the canvas during the repositioning.
Claim 1. A method for assisting users in re-finding documents, the method comprising:
generating embeddings for document clips related to respective documents among a plurality of documents; receiving a first set of concept clips defining a first concept for searching for content of interest to a user in the plurality of documents; generating embeddings for respective concept clips in the first set of concept clips;
generating a first concept embedding based on a combination of the embeddings generated for the respective concept clips in the first set of concept clips;
determining semantic relationships between the first concept and the document clips based on i) the embeddings generated for the document clips and ii) the concept embedding;
generating a graphical user interface depicting the semantic relationships between the first concept and the document clips; and causing display of the graphical user interface to be rendered at a client device, wherein the graphical user interface is operable to enable re-finding a document, among the plurality of documents, having the content of interest to the user.
Claim 35
Claim 2
Claim 36
Claim 3
Claim 37
Claim 3
Claim 38
Claim 3
Claim 39
Claim 5
Claim 40
Claim 6
Claims 21-40 recite substantially the same subject matter as claims 1-3, 5-6 and 13-16 of US Pat. 12,299,058; however, this patent also fail to particularly show the limitations not in bold above, as this being the only difference between the claims.
However, Ramos teaches a GUI that includes a canvas that spatially represents a user defined concept with a concept representation and spatially represents documents with document representations according to a determined semantic relationship. (See Ramos [0024, 0026] “The exploration pane 100 displays a star coordinate space 102 spanned by anchor concepts 104 (shown as rings) arranged on a circle 106… Interior to the circle 106, data items 108… visually represented by various symbols, are displayed… The positions of the data items 108 depend on the positions of the anchor concepts 104 and… the similarity of the data items 108 to the anchor concepts 104” See also Ramos [0026] teaching the data items are documents such as web pages, and the scores are a cosine similarity (i.e. semantic relationship).) Ramos further teaches receiving a user input that specifies a repositioning of the concept representation as specified and dynamically updating the positions of the document representations on the canvas during the repositioning, based on the semantic relationship and the updated concept position. (See Ramos [0032, 0040] “using anchor concepts 104 to dynamically spread out the data items 108… users may manipulate the locations of the anchor concepts 104 along the circle 106 (e.g., by dragging a selected anchor concept 104)… by changing the position of the anchor concept 104 (e.g., moving it to a new position along the circle 106)… all of these manipulations affect the computation of the positions of the data items in the star coordinate space 102. Accordingly, following any such manipulation… the positions of the visual representations of the data items 108 are updated” See also Ramos [0005] “the user interface allows the user to rearrange the anchor concepts along the circle and, based on his observation of the resulting movement of data items in the plane, optimally spread out the data items”)
It would have been obvious to modify the system and methods of claims 1 and 13 of the ‘178 patent to depict the determined semantic relationship using Ramos’s interactive canvas with a user-draggable concept representation and dynamically updating the document representations. One would be motivated to do so because Ramos teaches that such canvas lets the user dynamically spread out and visually organize the documents according to their relationship to the concept (Ramos 0005, 0032), thereby furthering the ‘178 patent claims purpose of re-finding a document having the content of interest to the user, with predictable results.
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.
Claims 21-40 are rejected under 35 U.S.C. 103 as being unpatentable over Mahmoud (US Patent Application Publication No. US 20220156298 A1), in view of Huh (US Patent Application Publication No. US 20190138615 A1).
Regarding claim 21, Mahmoud teaches a system, comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations, the set of operations comprising: generating a concept embedding based on a concept definition from a user; (See Mahmoud [0034-0038, 0107] “The agent-assist system 118 may analyze the text of the communication sessions 108 and determine context of the conversation, such as a semantic or meaning of the conversation… the techniques described herein include identifying portions of the documents, or “subdocuments,” that are more relevant to the queries or context of the conversation between the agents 112 and user 104… The contact-center infrastructure 102 and the agent-assist system 118 may include one or more hardware processors (processors)… At 608, the agent-assist system 118 may identify first input received from the user device 106 where the first input represents a query of the user 104 [Thus, from a user] for the agent 112 to answer. At 610, the agent-assist system 118 may identify, from the subdocuments 302, a first subdocument 302 as including first text that is semantically related to the query. For example, the agent-assist system 118 may generate an embedding [e.g. concept embedding] representing the semantic meaning of the query [e.g. concept definition from a user], and identify subdocuments 302 having embeddings that are similar to (e.g., within a threshold distance in a vector space) the query embedding.”)
evaluating the concept embedding to determine a semantic relationship between the concept embedding and one or more document embeddings corresponding to a set of documents; and (See Mahmoud [0104-0107] “At 602, an agent-assist system 118 may obtain a plurality of documents 206 relating to different topics… At 604, the agent-assist system 118 may identify subdocuments 302 from each of the plurality of documents 206 [e.g. a set of documents]… At 606, the agent-assist system 118 may establish a communication session 108 between a user device 106 and an agent device 114… the agent-assist system 118 may identify first input received from the user device 106 where the first input represents a query of the user 104 for the agent 112 to answer… the agent-assist system 118 may generate an embedding representing the semantic meaning of the query, and identify subdocuments 302 having embeddings that are similar to (e.g., within a threshold distance in a vector space) [Thus, evaluating the concept embedding to determine a semantic relationship] the query embedding. [Thus, evaluating the concept embedding to determine a semantic relationship between the concept embedding and one or more document embeddings corresponding to a set of documents]”)
providing, for display to the user, a graphical user interface (GUI) that indicates the determined semantic relationship corresponding to the concept embedding, (See Mahmoud [0109] “At 612, the agent-assist system 118 may cause presentation of a visual indicator on the display that indicates the first subdocument 302 as being relevant to the query.” See also Mahmoud [0024-0026] “After presenting the subdocuments, the agent-assist system may collect feedback from the agent and/or user in the conversation to determine a relevancy of the recommended answers or information.”
Mahmoud does not clearly teach a GUI that indicates the determined semantic relationship in the form of relevance scores/rankings presented to the user for the concept.
However, Huh also disclose providing, for display to the user, a GUI that indicates the determined semantic relationship corresponding to the concept embedding in more details. (See Huh [0005] “In response to a user query, documents and concept markers relevant to the query are determined.” See also Huh [0044, 0084] “determining the relevance of a concept marker may include calculating a cosine similarity between a vector representation of the concept markers and the words in the query… an average embedding for each concept marker may be generated by averaging the embeddings for each word in the concept marker in the query. Similarly, an average embedding for each word in the query may be generated. [Thus, generating a concept embedding based on a concept definition from a user]… ranking the documents in the search results may include calculating a cosine similarity between a vector representation of query concept markers and concept markers assigned to the document to determine the semantic similarity between the query and the document… The cosine similarity between the average embedding vector of the query and the average embedding vector of the document may then be determined [Thus, determine a semantic relationship between the concept embedding and document embedding corresponding to a set of documents]. Re-ranker module 152 may rank documents based on the respective calculated cosine similarity.” See also Huh [0104], Fig. 4 “the re-ranked search results documents and concept markers [e.g. concept embedding] are provided to the user, via the GUI [Thus, a graphical representation]. For example, as shown in FIG. 4, in response to the selection of concept marker 410, concept marker set 420 is provided and displayed in GUI 300. Additionally, a portion of the re-ranked search result documents 430 [Thus, depicting the concept embedding in relation to the one or more document embeddings according to the determined semantic relationship]. may be displayed in GUI 300.”
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Thus, by providing a score and rank in in the search result documents 430, it is providing (Thus, generating), for display to the user, a GUI indicating the determined semantic relationship corresponding to the concept embedding.)
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Mahmoud; which identifies portions of the documents, or “subdocuments,” being relevant to the queries, to incorporate the teachings of Huh by providing a score and ranking in in the documents search result.
One would be motivated to do so to improve relevance and prioritization, allowing users to identify most relevant results.
Mahmud in view of Huh does not explicitly disclose wherein the GUI includes a canvas that spatially represents the concept embedding with a concept representation and spatially represents the one or more document embeddings with one or more document representations, according to the determined semantic relationship between the concept embedding and the one or more document embeddings.
However, Ramos teaches GUI includes a canvas that spatially represents the concept embedding with a concept representation and spatially represents the one or more document embeddings with one or more document representations, according to the determined semantic relationship between the concept embedding and the one or more document embeddings. (See Ramos [0024, 0026] “The exploration pane 100 [e.g. GUI] displays a star coordinate space 102 spanned by anchor concepts 104 (shown as rings) [e.g. concept representations] arranged on a circle 106… Interior to the circle 106, data items 108 (pointed to in the aggregate in FIG. 1A), visually represented by various symbols [e.g. one or more document representations], are displayed. The positions of the data items 108 depend on the positions of the anchor concepts 104 and some property of the data items 108 measured by the anchor concepts 104, such as, for one example type of anchor concept, the similarity of the data items 108 to the anchor concepts 104 [Thus, the concept representation and document representations are spatially arranged on the canvas according to the determined semantic relationship]… the position vector {right arrow over (r)}(i) of data item i may be calculated as the normalized vector sum over the anchor-concept vectors {right arrow over (V)}k each multiplied by the respective score sk(i) [Thus, each document representation’s spatial position is computed from the concept representation’s position weighted by the concept to document relationship score]… the scores measure a degree of similarity between the anchor concepts 104 and the data items 108. For example, in the context of developing a concept classifier for documents (such as, e.g., web pages)… a suitable metric of similarity between a data item 108 and an anchor concept 104 is the cosine similarity between their respective… vectors [Thus, the data items are documents, and the spatial arrangement follows a vector similarity semantic relationship]”)
It would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to modify Mahmoud in view of huh, which determines and displays the semantic relationship between the concept embedding and the document embeddings as scored and ranked results, to incorporate the teachings of Ramos by displaying that semantic relationship on a canvas that spatially represent the concept with a concept representation and the documents with document representations positioned according to their similarity to the concept.
One would be motivated to do so to let the user visually organize and explore the documents according to their relationship to the concept (Ramos 0005, 0032), making it easier to identify documents of interest. The results would be predictable, since Ramos’s canvas positions the documents using the same type of similarity values between concept and document vector that Mahmoud and Huh already compute (Mahmoud 0104-0107, Huh 0044, 0026).
Mahmoud in view of Hub and further in view of Ramos, [hereinafter Mahmoud-Huh-Ramos] additionally teaches receive a user input that specifies a repositioning of the concept embedding; and in response to receiving the user input: update a position of the concept representation as specified by the user input; and (See Ramos [0032] “Further, to tease apart sub-concepts of a target concept, or generally to contrast or associate anchor concepts 104 and the data items they attract, users may manipulate the locations of the anchor concepts 104 along the circle 106 (e.g., by dragging a selected anchor concept 104) [Thus, receiving a user input (a drag) that specifies a repositioning of the concept representation. (See the interpretation of this limitation in the 112(b) rejection above)]” See also Ramos claim 5 “user manipulation of the anchor concepts comprises changing a position of an anchor concept along the circle” See also Ramos [0040] “the user can manipulate an anchor concept… by changing the position of the anchor concept 104 (e.g., moving it to a new position along the circle 106) [Thus, the position of the concept representation is updated to the position specified by the user’s drag input]”)
based at least in part on the determined semantic relationship and the updated position of the concept representation, dynamically update respective positions of the one or more document representations on the canvas during the repositioning. (See Ramos [0040] “by changing the position of the anchor concept 104 (e.g., moving it to a new position along the circle 106)… —all of these manipulations affect the computation of the positions of the data items in the star coordinate space 102. Accordingly, following any such manipulation or the creation of a new anchor concept 104 (operation 306), the positions of the visual representations of the data items 108 are updated in the star coordinate space 102 (operation 308) [Thus, in response to the repositioning of the concept representation, the positions of the documents representations on the canvas are updated].” See also Ramos [0032] “The exploration pane 100 allows users to interactively explore the dataset, using anchor concepts 104 to dynamically spread out the data items 108 [Thus, the updating is dynamic].” See also Ramos [0005] “the user interface allows the user to rearrange the anchor concepts along the circle and, based on his observation of the resulting movement of data items in the plane, optimally spread out the data items [Thus, the user observes the resulting movement of the document representation as the concept representations are rearranged (i.e. dynamic updating during repositioning)]”)
Regarding claim 22, Mahmoud in view of Hub and further in view of Ramos, [hereinafter Mahmoud-Huh-Ramos] teaches all limitations and motivations of claim 21, wherein the set of documents comprises one or more of: a webpage; or an electronic file. (See Mahmud [0044] “As shown in FIG. 2, the agent-assist pipeline 202 may obtain, at “1,” documents 206 from the knowledge-base source(s) 204… The documents may be text documents, FAQ webpages, PDFs, and/or any type of electronic document with information.)
Regarding claim 23, Mahmoud-Huh-Ramos teaches all limitations and motivations of claim 21, wherein each document embedding of the one or more document embeddings corresponds to a content subpart of a document in the set of documents. (See Mahmoud [0107] “the agent-assist system 118 may generate an embedding representing the semantic meaning of the query, and identify subdocuments 302 having embeddings [e.g. document embedding] that are similar to (e.g., within a threshold distance in a vector space) the query embedding.” See also Mahmoud [0066] “each document is a collection of subdocuments. A subdocument can be a paragraph in a document [Thus, corresponds to a content subpart of a document in the set of documents], a unit smaller than a paragraph (e.g., a sentence or a collection of contiguous sentences), or a collection of contiguous paragraphs.”)
Regarding claim 24, Mahmoud-Huh-Ramos teaches all limitations and motivations of claim 21, wherein each document embedding of the one or more document embeddings corresponds to a plurality of content subparts of a document in the set of documents. (See Mahmoud [0107] “the agent-assist system 118 may generate an embedding representing the semantic meaning of the query, and identify subdocuments 302 having embeddings [e.g. document embedding] that are similar to (e.g., within a threshold distance in a vector space) the query embedding.” See also Mahmoud [0066] “each document is a collection of subdocuments. A subdocument can be a paragraph in a document, a unit smaller than a paragraph (e.g., a sentence or a collection of contiguous sentences), or a collection of contiguous paragraphs. [Thus, corresponds to a plurality of content subparts of a document in the set of documents]”)
Regarding claim 25, Mahmoud-Huh-Ramos teaches all limitations and motivations of claim 24, wherein each content subpart of the content subparts is a paragraph of the document. (See Mahmoud [0107] “the agent-assist system 118 may generate an embedding representing the semantic meaning of the query, and identify subdocuments 302 having embeddings [e.g. document embedding] that are similar to (e.g., within a threshold distance in a vector space) the query embedding.” See also Mahmoud [0066] “each document is a collection of subdocuments. A subdocument can be a paragraph in a document [Thus, corresponds to a content subpart of a document in the set of documents], a unit smaller than a paragraph (e.g., a sentence or a collection of contiguous sentences), or a collection of contiguous paragraphs.”)
Regarding claim 26, Mahmoud-Huh-Ramos teaches all limitations and motivations of claim 21, wherein the concept definition includes one or more of: a text paragraph provided by the user; (See Mahmoud [0034-0035] “The agent-assist system 118 may analyze the text of the communication sessions 108 and determine context of the conversation, such as a semantic or meaning of the conversation… the techniques described herein include identifying portions of the documents, or “subdocuments,” that are more relevant to the queries or context of the conversation between the agents 112 and user 104” See also Mahmud [0070], Fig. 4A “The agent-assist user interface (UI) 402 may present a conversation 120 [Thus, includes a text paragraph provided by the user] between a user 104 and an agent 112 as well as agent-assist recommendations 122 for the agent 112 to use to respond to the user 104. As shown, the conversation 120 includes user input 404 and agent input 406”
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Regarding claim 27, Mahmoud-Huh-Ramos teaches all limitations and motivations of claim 21,wherein: the one or more document embeddings were generated using a machine learning model based on content of the set of documents; and the concept embedding is generated using the machine learning model. (See Mahmoud [0057] “the retriever component 218 may embed the query using an embedding model [Thus, the concept embedding is generated using the machine learning model] (that preserves the semantic relationships detailed earlier) into a vector q, and searches the vector space index that corresponds to the agent's 112 knowledge base profile. An agent 112 handling a user conversation can be assigned to a single profile at a time, Each subdocument [e.g. content of the set of documents] in the knowledge base profile, with references to the document to which it belongs, is represented as a point in the high-dimensional vector space (e.g., 1024 dimensions). The agent-assist system 118 finds the k nearest points, embedded using the same embedding model [Thus, the one or more document embeddings were generated using a machine learning model based on content of the set of documents], to the input q.”)
Regarding claim 28, Mahmoud-Huh-Ramos teaches all of the elements of claim 21 in system form. Therefore, the supporting rationale of the rejection to claim 21 applies equally as well to those elements of claim 28.
Regarding claim 29, Mahmoud-Huh-Ramos teaches all of the elements of claim 22 in system form. Therefore, the supporting rationale of the rejection to claim 22 applies equally as well to those elements of claim 29.
Regarding claim 30, Mahmoud-Huh-Ramos teaches all of the elements of claim 24 in system form. Therefore, the supporting rationale of the rejection to claim 24 applies equally as well to those elements of claim 30.
Regarding claim 31, Mahmoud-Huh-Ramos teaches all of the elements of claim 25 in system form. Therefore, the supporting rationale of the rejection to claim 25 applies equally as well to those elements of claim 31.
Regarding claim 32, Mahmoud-Huh-Ramos teaches all of the elements of claim 26 in system form. Therefore, the supporting rationale of the rejection to claim 26 applies equally as well to those elements of claim 32.
Regarding claim 33, Mahmoud-Huh-Ramos teaches all of the elements of claim 27 in system form. Therefore, the supporting rationale of the rejection to claim 27 applies equally as well to those elements of claim 33.
Regarding claim 34, Mahmoud-Huh-Ramos teaches all of the elements of claim 21 in system form. Therefore, the supporting rationale of the rejection to claim 21 applies equally as well to those elements of claim 34.
Regarding claim 35, Mahmoud-Huh-Ramos teaches all of the elements of claim 22 in system form. Therefore, the supporting rationale of the rejection to claim 22 applies equally as well to those elements of claim 35.
Regarding claim 36, Mahmoud-Huh-Ramos teaches all of the elements of claim 23 in system form. Therefore, the supporting rationale of the rejection to claim 23 applies equally as well to those elements of claim 36.
Regarding claim 37, Mahmoud-Huh-Ramos teaches all of the elements of claim 24 in system form. Therefore, the supporting rationale of the rejection to claim 24 applies equally as well to those elements of claim 37.
Regarding claim 38, Mahmoud-Huh-Ramos teaches all of the elements of claim 25 in system form. Therefore, the supporting rationale of the rejection to claim 25 applies equally as well to those elements of claim 38.
Regarding claim 39, Mahmoud-Huh-Ramos teaches all of the elements of claim 26 in system form. Therefore, the supporting rationale of the rejection to claim 26 applies equally as well to those elements of claim 48.
Regarding claim 40, Mahmoud-Huh-Ramos teaches all of the elements of claim 27 in system form. Therefore, the supporting rationale of the rejection to claim 27 applies equally as well to those elements of claim 40.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chang et al. (US 8,364,673 B2) discloses a system and graphical user interface for dynamically and interactively searching a database of documents, in which user-selected search concepts are placed as search anchors on a navigation map, a concept relevance weight is computed for each cell of the map based on the distance between the cell and the positions of the search anchors, and the cells are populated with documents ranked by a total relevance score combining the concept relevance weight with document relevance scores, where a user may position and reposition the search anchors on the navigation map by drag and drop manipulation, where the system monitors changes to the navigation map, computes new concept relevance weights for each cell, and generates new result lists when anchors are added, removed or rearranged, such that the displayed results are dynamically adjusted based on the anchors updated positions.
Duffy et al. (US 2015/0331908 A1) discloses a visual interactive search system in which a catalog of documents is embedded into an embedding space, with the distance between each pair of documents in the embedding space corresponding to a predetermined measure of semantic dissimilarity between the documents, and in which the search is iteratively refined by interpreting the user’s relative feedback as geometric constraints on the embedding space that narrow the candidate space of documents, where candidate documents in a two dimensional layout in which documents are far from each other in the embedding space are displayed far from each other in the display, so that the on-screen placement of the document representations conveys the underlying embedding space distances to the user.
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.
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/OSCAR WEHOVZ/Examiner, Art Unit 2161
/APU M MOFIZ/Supervisory Patent Examiner, Art Unit 2161
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