DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 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 1-20 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.
Claim 1 recites “selecting the first summary… based upon the summary scores” in the second to last limitation. “Selecting the first summary” indicates that the invention already knows which summary (the first summary) to select. Why is the invention generating the second through fourth summaries if the invention is always going to “select the first summary?” Why is the invention scoring four summaries when the invention is always going to “select the first summary?” Why is the invention generating four different content items if the second through fourth content items will never be used? It is unclear to the Examiner what the invention is supposed to be doing. For the purposes of express examination, the Examiner interprets that the invention is “selecting one of the first summary, the second summary, the third summary, and the fourth summary, based upon the summary scores.” Claims 11 and 29 recite similar limitations.
Claims 2-10, 12-18, and 20 are dependent claims, and inherit the 35 U.S.C. §112(b) rejections from their independent claims.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan et al., Patent Application Publication number US 20250139105 A1, (hereinafter “Srinivasan”), in view of Soubbotin, Patent Number US 12038958 B1 (hereinafter “Soubbotin”), in view of Zhao, Patent Application Publication number US 20180181573 A1 (hereinafter “Zhao”).
Claim 1: Srinivasan teaches “A method, comprising:
receiving, from a client device, a query (i.e. responsive to a query [Srinivasan 0035]);
in response to the query, generating a plurality of search results (i.e. At step 402, the system identifies (e.g., receives identifiers for) resources determined to be responsive to a query. For at least some of the top-ranked resources [Srinivasan 0035, Fig. 4]) corresponding to a plurality of internet resources associated with the query (i.e. resources can refer to any content accessible to a search engine. Thus, resources include webpages, images, documents, media, etc [Srinivasan 0013]);
generating, using a first content extraction model (i.e. the system generates an extractive summary by concatenating the most relevant sentences… In some implementations, sentences which have a sentence relevance score that meets a threshold are included in the extractive summary [Srinivasan 0036] note: “sentence relevance score that meets a threshold” as a first model), a first content item (i.e. the most relevant sentences [Srinivasan 0036]) based upon a first search result of the plurality of search results (i.e. For at least some of the top-ranked resources, at step 404, the system may generate an extractive summary [Srinivasan 0035] note: at least 2 search results);
generating, using a second content extraction model (i.e. the system generates an extractive summary by concatenating the most relevant sentences… In some implementations, a maximum number (predetermined number) of sentences that have a relevance score that meets the threshold are used [in the extractive summary] [Srinivasan 0036] note: “a maximum number (predetermined number) of sentences that have a relevance score” as a second model), a second content item (i.e. the most relevant sentences [Srinivasan 0036]) based upon the first search result (i.e. For at least some of the top-ranked resources, at step 404, the system may generate an extractive summary [Srinivasan 0035] note: at least 2 search results);
generating, using the first content extraction model (i.e. the system generates an extractive summary by concatenating the most relevant sentences… In some implementations, sentences which have a sentence relevance score that meets a threshold are included in the extractive summary [Srinivasan 0036] note: “sentence relevance score that meets a threshold” as a first model), a third content item (i.e. the most relevant sentences [Srinivasan 0036]) based upon a second search result of the plurality of search results (i.e. For at least some of the top-ranked resources, at step 404, the system may generate an extractive summary [Srinivasan 0035] note: at least 2 search results);
generating, using the second content extraction model (i.e. the system generates an extractive summary by concatenating the most relevant sentences… In some implementations, a maximum number (predetermined number) of sentences that have a relevance score that meets the threshold are used [in the extractive summary] [Srinivasan 0036] note: “a maximum number (predetermined number) of sentences that have a relevance score” as a second model), a fourth content item (i.e. the most relevant sentences [Srinivasan 0036]) based upon the second search result (i.e. For at least some of the top-ranked resources, at step 404, the system may generate an extractive summary [Srinivasan 0035] note: at least 2 search results);
generating… a plurality of summaries (i.e. For at least some of the top-ranked resources, at step 404, the system may generate an extractive summary [Srinivasan 0035]) comprising:
a first summary of the first content item;
a second summary of the second content item;
a third summary of the third content item; and
a fourth summary of the fourth content item (Srinivasan teaches at least 2 different extraction models that create summaries in 0036. Srinivasan teaches that extraction summaries are generated for at least 2 search results in 0035. Srinivasan is capable of using each of the 2 extraction models upon each of the 2 search results to generate a first summary of the first content item, a second summary of the second content item, a third summary of the third content item; and a fourth summary of the fourth content item);
determining summary scores of the plurality of summaries (i.e. At step 412, the system may calculate a relevance score for the extractive summary. The relevance score is based on the relevance of the extractive summary to the query [Srinivasan 0037, Fig. 4] note: in Fig. 4 step 412, scoring is performed for each summary generated in step 410);…”
Srinivasan is silent regarding generating, “using a language model,” a plurality of summaries.
Soubbotin teaches “receiving, from a client device, a query (i.e. a user's query for “causes of ocean tides” in query field 101, as well as search results list 103 as links to documents that were found by the search engine while matching the query [Soubbotin Col 20 lines 47-49, Fig. 1-2]);
in response to the query, generating a plurality of search results (i.e. a user's query for “causes of ocean tides” in query field 101, as well as search results list 103 as links to documents that were found by the search engine while matching the query [Soubbotin Col 20 lines 47-49, Fig. 1-2]) corresponding to a plurality of internet resources associated with the query (i.e. search results list 103 may be displayed with relevant information such as, but not limited to… a URL to the location of the document [Soubbotin Col 20 lines 43-46]);…
generating, using a language model, a plurality of summaries (i.e. If the user clicks summary request button 100, a summary of the results that are displayed on this page may be generated by the system [Soubbotin Col 20 lines 65-67, Fig. 1-2]… FIG. 2 illustrates an exemplary summary 200… that may be generated… based on Statistical AI Language Models (e.g., LLMs). In the present embodiment, the Summary has a title “causes of ocean tides” [Soubbotin Col 23 lines 6-10, Fig. 1-2]) comprising:
a first summary of the first content item;
a second summary of the second content item;
a third summary of the third content item; and
a fourth summary of the fourth content item (i.e. If the user clicks summary request button 100, a summary of the results that are displayed on this page may be generated by the system [Soubbotin Col 20 lines 65-67, Fig. 1-2] note: Fig. 1-2 shows at least 6 summaries, element 200);…”
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention/combination of Srinivasan to include the feature of having the ability to use a language model as disclosed by Soubbotin.
One would have been motivated to do so, before the effective filing date of the invention because it provides the benefit of using generative AI, which reduces manual labor (manual code programming), and also the summary text can flow better, and not merely be a choppy selection of sentences.
Srinivasan and Soubbotin are silent regarding “selecting the first summary from the plurality of summaries based upon the summary scores; and in response to selecting the first summary, providing the first summary for display on the client device.”
Zhao teaches “in response to the query, generating a plurality of search results corresponding to a plurality of… resources associated with the query (i.e. search for multiple pieces of page information matching the query from a database [Zhao 0071]);
generating, using a first content extraction model, a first content item based upon a first search result of the plurality of search results (i.e. Page information recorded in the database includes entity data obtained by performing entity extraction on pages, and/or, paragraphing data obtained by extracting paragraphs containing an answer from the pages [Zhao 0072] note: page information includes extracted text);…
determining summary scores of the plurality of summaries (i.e. perform multi-characteristic analysis on each piece of page information according to characteristics, to obtain a characteristic score of each of the characteristics [Zhao 0073] note: from 0072 above, page information includes extracted text, which is a summary);
selecting the first summary from the plurality of summaries based upon the summary scores; and
in response to selecting the first summary, providing the first summary for display on the client device (i.e. rank the multiple pieces of page information according to the characteristic score [Zhao 0075]… As a possible implementation, pieces of page information top ranked can be selected and displayed as a summary on the search result page. FIG. 2 [Zhao 0051, Fig. 2]).”
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention/combination of Srinivasan and Soubbotin to include the feature of having the ability to display a certain summary as disclosed by Zhao.
One would have been motivated to do so, before the effective filing date of the invention because it provides the benefit to view the summary that the user desires, and summaries reduce the amount of reading a user is required, which saves the user time.
Claim 2: Srinivasan and Soubbotin and Zhao teach all the limitations of claim 1, above. Zhao teaches “displaying a search interface on the client device, wherein the query is received via the search interface (Zhao Fig. 2 shows a search interface with a query); and
in response to selecting the first summary, displaying the first summary via the search interface (i.e. rank the multiple pieces of page information according to the characteristic score [Zhao 0075]… As a possible implementation, pieces of page information top ranked can be selected and displayed as a summary on the search result page. FIG. 2 [Zhao 0051, Fig. 2]) concurrently with displaying one or more representations of one or more search results of the plurality of search results via the search interface (Zhao Fig. 2 shows “This answer is from mingju.3518.cn”).”
One would have been motivated to combine Srinivasan and Soubbotin and Zhao, before the effective filing date of the invention because it provides the benefit to view the summary that the user desires, and summaries reduce the amount of reading a user is required, which saves the user time.
Claim 3: Srinivasan and Soubbotin and Zhao teach all the limitations of claim 1, above. Soubbotin teaches generating summaries using a language model in claim 1 (see Soubbotin Col 23 lines 6-10, Fig. 1-2, above). Srinivasan teaches “generating… an initial summary comprising a plurality of summary items (i.e. the system generates an extractive summary by concatenating the most relevant sentences [Srinivasan 0036] note: set of relevant sentences as initial summary, each sentence as summary items);
determining, based upon the plurality of summary items and the query (i.e. each sentence in the most relevant portions… relevance represents relevance to the query [Srinivasan 0035]), a plurality of relevance statuses comprising:
a first relevance status of a first summary item of the plurality of summary items, wherein the first relevance status indicates that the first summary item is relevant to the query (i.e. relevance represents relevance to the query [Srinivasan 0035]… sentences which have a sentence relevance score that meets a threshold are included in the extractive summary [Srinivasan 0036] note: status of “included”); and
a second relevance status of a second summary item of the plurality of summary items, wherein the second relevance status indicates that the second summary item is not relevant to the query (i.e. relevance represents relevance to the query [Srinivasan 0035]… a sentence with a 0.25 relevance score may be excluded [Srinivasan 0036] note: status of “excluded”); and
generating the first summary based upon the initial summary and the plurality of relevance statuses (i.e. sentences which have a sentence relevance score that meets a threshold are included in the extractive summary [Srinivasan 0036]).”
Claim 4: Srinivasan and Soubbotin and Zhao teach all the limitations of claim 3, above. Srinivasan teaches “wherein generating the first summary comprises:
including the first summary item in the first summary based upon the first relevance status indicating that the first summary item is relevant to the query (i.e. relevance represents relevance to the query [Srinivasan 0035]… sentences which have a sentence relevance score that meets a threshold are included in the extractive summary [Srinivasan 0036] note: status of “included”); and
not including the second summary item in the first summary based upon the second relevance status indicating that the second summary item is not relevant to the query (i.e. relevance represents relevance to the query [Srinivasan 0035]… a sentence with a 0.25 relevance score may be excluded [Srinivasan 0036] note: status of “excluded”).”
Claim 5: Srinivasan and Soubbotin and Zhao teach all the limitations of claim 3, above. Srinivasan teaches “wherein determining the summary scores of the plurality of summaries comprises:
determining a first summary score of the first summary (i.e. system may calculate a relevance score for the extractive summary [0037]) based upon the plurality of relevance statuses (i.e. sentences which have a sentence relevance score that meets a threshold are included in the extractive summary [Srinivasan 0036] note: score is based on the summary, which is based on the relevant sentences, which have an “included” status (see claim 3); thus the score is based upon the status).”
Claim 6: Srinivasan and Soubbotin and Zhao teach all the limitations of claim 3, above. Srinivasan teaches “wherein determining the summary scores of the plurality of summaries comprises:
determining a first summary score of the first summary based upon a quantity of summary items of the plurality of summary items (i.e. In some implementations, a maximum number (predetermined number) of sentences that have a relevance score that meets the threshold are used [0036] note: score is based upon both a quantity and a quality attribute).”
Claim 7: Srinivasan and Soubbotin and Zhao teach all the limitations of claim 3, above. Srinivasan teaches “wherein determining the summary scores of the plurality of summaries comprises:
determining a first summary score of the first summary based upon item sizes of the plurality of summary items (i.e. In some implementations, a maximum number (predetermined number) of sentences that have a relevance score that meets the threshold are used [0036] note: score is based upon both a quantity (size) and a quality attribute).”
Claim 8: Srinivasan and Soubbotin and Zhao teach all the limitations of claim 1, above. Srinivasan teaches “comprising:
determining rankings, of the plurality of search results, comprising a first ranking of the first search result and a second ranking of the second search result (i.e. top ranked resources that are responsive to the query [Srinivasan 0021] note: top ranked resources indicates at least 2 ranked results),
wherein determining the summary scores of the plurality of summaries comprises determining a first summary score of the first summary based upon the first ranking (i.e. extractive summary system 126 is configured to generate an extractive summary relevance score… In some implementations, a search result generator 124 may use the extractive summary generated for a resource in a search result page [Srinivasan 0024] note: summary uses results rankings as a score, to display the summaries in the ranking order of the search results).”
Claim 9: Srinivasan and Soubbotin and Zhao teach all the limitations of claim 1, above. Srinivasan teaches “comprising:
determining a similarity score associated with a similarity between at least a portion of the first summary and content associated with an internet resource corresponding to the second search result, wherein determining the summary scores of the plurality of summaries comprises determining a first summary score of the first summary based upon the similarity score (i.e. Scoring the relevance of the extractive summary 235 to the query [results] enables the search system 120 to take into account context provided by other passages in the resource, enabling the search system 120 to better (more often and more accurately) identify resources that answer the full complex query 202. Thus, the extractive summary relevance score may be used as a resource relevance score 245 in determining a search result page for the query 202… the extractive summary system 126 can provide a resource relevance score 245 used to re-rank (re-order) resources [Srinivasan 0029] note: summaries are scored on relevance to each resource, or search result. Srinivasan’s “re-ranking” indicates that every search result is scored with an extractive summary relevance score, including a first and second search result. Extractive summary “relevance” score is a similarity score).”
Claim 10: Srinivasan and Soubbotin and Zhao teach all the limitations of claim 1, above. Srinivasan teaches “wherein:
determining a similarity score associated with a similarity between at least a portion of the first summary and content associated with an internet resource corresponding to the first search result, wherein determining the summary scores of the plurality of summaries comprises determining a first summary score of the first summary based upon the similarity score (i.e. Scoring the relevance of the extractive summary 235 to the query [results] enables the search system 120 to take into account context provided by other passages in the resource, enabling the search system 120 to better (more often and more accurately) identify resources that answer the full complex query 202. Thus, the extractive summary relevance score may be used as a resource relevance score 245 in determining a search result page for the query 202… the extractive summary system 126 can provide a resource relevance score 245 used to re-rank (re-order) resources [Srinivasan 0029] note: summaries are scored on relevance to each resource, or search result. Srinivasan’s “re-ranking” indicates that every search result is scored with an extractive summary relevance score, including a first and second search result. Extractive summary “relevance” score is a similarity score).”
Claim 11: Srinivasan and Soubbotin and Zhao teach a non-transitory machine-readable medium having stored thereon processor-executable instructions that when executed cause performance of operations (i.e. a non-transitory computer-readable medium storing instructions executable by one or more of the processors [Srinivasan 0043]), the operations corresponding to the method of claim 1; therefore, it is rejected under the same rationale.
Claim 12: Claim 12 is similar in content and in scope to claim 2, thus it is rejected under the same rationale.
Claim 13: Claim 13 is similar in content and in scope to claim 3, thus it is rejected under the same rationale.
Claim 14: Claim 14 is similar in content and in scope to claim 4, thus it is rejected under the same rationale.
Claim 15: Claim 15 is similar in content and in scope to claim 5, thus it is rejected under the same rationale.
Claim 16: Claim 16 is similar in content and in scope to claim 6, thus it is rejected under the same rationale.
Claim 17: Claim 17 is similar in content and in scope to claim 7, thus it is rejected under the same rationale.
Claim 18: Claim 18 is similar in content and in scope to claim 8, thus it is rejected under the same rationale.
Claim 19: Srinivasan and Soubbotin and Zhao teach a computing device comprising:
a processor; and
memory comprising processor-executable instructions that when executed by the processor cause performance of operations (i.e. a non-transitory computer-readable medium storing instructions executable by one or more of the processors [Srinivasan 0043]), the operations corresponding to the method of claim 1; therefore, it is rejected under the same rationale.
Claim 20: Claim 20 is similar in content and in scope to claim 2, thus it is rejected under the same rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chowdhury (US 7818314 B2) listed on 892 is related to assigning a score to each search result, based on the comparison of the terms included in the query.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SAMUEL SHEN whose telephone number is (469)295-9169 and email address is samuel.shen@uspto.gov. The examiner can normally be reached Monday-Thursday, 7:00 am - 5:00 pm CT.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fred Ehichioya can be reached on (571) 272-4034. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/S.S./Examiner, Art Unit 2179
/TUYETLIEN T TRAN/Primary Examiner, Art Unit 2179