DETAILED ACTION
This is Non-Final Office Action in response to amendment filed on February 12, 2026. Claims 2, 9 and 16 have been canceled. Claims 1, 3-8, 10-15 and 17-20 are pending.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 February 12, 2026 has been entered.
Examiner Remarks
It still appears to recite subject matter that, based on the amended claim language, could be characterized as an abstract idea, even though the examiner previously withdrew the rejection under 101. Withdrawing a rejection does not necessarily mean that the claims no longer raises eligibility concerns; rather, it may indicate that the examiner accepted the applicant’s arguments or amendments in that particular Office Action.
Response to Arguments
Applicant's arguments regarding the amended limitations “in response to a search strategy to be selected being a first-time selected search strategy, determining that there is no data selection rate stored in association with the search strategy” (response 1/12/2026, pages 2-4) have been fully considered but they are not persuasive.
The Applicant asserts that the claim requires “in response to a search strategy to be selected being a first-time selected search strategy, determining that therein no data selection rate stored in association with the search strategy.” However, Day clearly discloses that when none of the strategy conditions match the imported values, the system selects the first listed strategy (see ¶[005], Day), which corresponds to selecting a strategy when no prior associated parameter (e.g., a stored data selection rate) exists. Thus, Day teaches or suggests the claimed limitation.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3-8, 10-15 and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of mental process without significantly more. The claims recite “receiving a data query request; determining a plurality of search strategies that match target data as indicated by the data query request; for each search strategy, querying a data selection rate stored in association with the search strategy from a cache, wherein the cache is used to dynamically maintain the data selection rate corresponding to each search strategy, and the data selection rate stored in the cache is determined based on real selection rates obtained from multiple historical data queries; in response to an existence of the data selection rate stored in association with the search strategy, taking the data selection rate as a target selection rate corresponding to the search strategy; and determining a target search strategy based on the target selection rate corresponding to respective search strategy, wherein the target data is obtained from a database based on the target search strategy”. This judicial exception is not integrated into a practical application because the steps can be performed manually in human mind. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claim here merely uses the processor as a tool to perform the otherwise mental processes. See October Update at Section I(C)(ii). Thus, the limitations recite concepts that fall into the “mental process” grouping of abstract ideas.
ANALYSIS under Revised Guidance of 2019 PEG:
Statutory Category:
The claims 1, 3-8, 10-15 and 17-20 are directed to one of the four statutory category (claims 1-7 a method or a process, claims 8-14 an electronic device and claims 15-20 a non-transitory computer readable medium).
Step 2A – Prong 1: Judicial Exception Recited?
The claim 1 recites the limitations of “receiving a data query request; obtaining a plurality of search strategies that match target data as indicated by the data query request; for each search strategy, querying a data selection rate stored in association with the search strategy from a cache…; in response to an existence of the data selection rate stored in association with the search strategy, taking the data selection rate as a target selection rate corresponding to the search strategy; and determining a target search strategy based on the target selection rate corresponding to respective search strategy …” The limitations, as drafted, are steps or processes that, under their broadest reasonable interpretation, cover performance of the limitations in mind. That is, nothing in the claim 1 precludes the processes (the steps …) from practically being performed in the human mind. The claim essentially recites: calculating a “data selection rate” (a ratio), storing it in a cache, retrieving historical rates, sampling data if no historical rate exists, comparing selection rates, choosing the best search strategy and executing the chosen strategy at a high level of evaluating performance and selecting the most efficient strategy based on comparison. The fact that the claim is performed by a “processor” and involves a “database” and “cache” does not meaningfully limit the abstract idea. Those are generic computer components performing conventional functions. Thus, the claim 1 recites an abstract idea under one of groupings of abstract idea, mental processes (concepts performed in the human mind including an evaluation, judgment, opinion, observation). (MPEP 2106.05(a)).
Step 2A – Prong 2: integrated into a practical application?
The claim 1 recites limitations or elements (querying a data selection rate stored in association with the search strategy from cache) do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea as identified in MPEP 2106.05(g).
Step 2B: The claim does not provide an incentive concept.
The claim 1 recites the generic processor, generic database, the cache is used conventionally (store and retrieve values), sampling and ratio calculation are mathematical operations, no specific technical improvement to database architecture is recited, no unconventional data structure or hardware configuration and using generic computer components to perform routine data analysis does not supply an inventive concept. The claim 1 includes limitations or elements that are sufficient to amounts to no more than mere instructions to apply the judicial exception which cannot integrate a judicial exception into a practical application or provide an inventive concept. The same analysis applies here in 2B, that is, mere instructions to apply a judicial exception, it cannot integrate a judicial exception into a practical application at step 2A or provide an inventive concept in step 2B. Thus, the claim 1 is ineligible.
Dependent claim 3 recites “acquiring the sampling data from the database “ abstract idea under step 2A(i) and “determining sample data that has been queried in the sampling data by the search strategy, and taking a proportion of the sample data in the sampling data as the target selection rate associated with the search strategy” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 4 recites “performing queries in the database using each search strategy” abstract idea under step 2A(ii) and “determining a data selection rate corresponding to the search strategy” mental process of abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 5 recites “comparing a difference between a currently determined data selection rate and a data selection rate …” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Dependent claim 7 recites “determining, among search strategies stored in the cache, a search strategy to be deleted whose cache time exceeds a preset time threshold, and deleting the search strategy to be deleted and its associated stored data selection rate from the cache.” abstract idea under step 2A(i). Therefore, the claimed elements fail to integrate the judicial exception into a practical application.
Claims 8, 10-15 and 10-20 are similar to claims 1-5 and 7 and therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3-5, 8-12, 15 and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Day (US 2006/0074874 A1) in view of Zhao et al. (US 20210064665 A1) and further in view of Oztekin et al. (US 20100262615 A1).
Regarding claim 1, Day discloses a database-based data query method, comprising:
receiving a data query request (¶[0035]-[0038] and [0055]-[0056], Day, optimizing index search or table scan for a search strategy);
determining a plurality of search strategies that match target data as indicated by the data query request (¶[0051]-[0052] and [0058]-[0059], Day, evaluating all of the records “a table scan strategy” or to evaluate some subset of records which satisfy one of the conditions, the subset being produced by comparing the condition to the corresponding index “an index search strategy”); for each search strategy, querying a data selection rate stored in association with the search strategy from a cache (¶[0056]-[0058], Day, generating an optimized execution strategy for the query, this optimized strategy is saved in cache as a strategy block with the query object based on user’s selection), wherein the cache is used to dynamically maintain the data selection rate corresponding to each search strategy (¶[0055]-[0058], Day, i.e., dynamic strategy queries); and
in response to an existence of the data selection rate stored in association with the search strategy (¶[0057]-[0058] and [0070], Day, i.e., If a suitable strategy does exist (the `Y` branch from step 504), a strategy is selected (step 506)), taking the data selection rate as a target selection rate corresponding to the search strategy (¶[0057]-[0058] and [0070], Day); and
in response to a search strategy to be selected being a first-time selected search strategy, determining the target selection rate corresponding to the search strategy by sampling data obtained from the database, wherein the sampling data is determined based on a selected sampling granularity and/or a number of sampling lines (¶[0055]-[0058] and [0070], Day).
Day, however, does not explicitly disclose determining a plurality of search strategies that match target data as indicated by the data query request and determining a target search strategy based on the target rate corresponding to respective search strategy, and the data rate stored in the cache is determined based on real rates obtained from multiple historical data queries.
Zhao discloses receiving a data query request (step 510 of Fig.5; ¶[0052] and [0069], Zhao), determining a plurality of search strategies that match target data as indicated by the data query request (step 520 of Fig 5 and search strategy/second module of Fig.6; ¶[0052] and [0069]-[0070], Zhao, obtaining a plurality of search strategies matching the user query in response to the user query); in response to an existence of the data rate/score stored in association with the search strategy, taking the data rate/score as a target rate/score corresponding to the search strategy (¶[0070]-[0072] and [0074], Zhao, i.e., selecting a specific search strategy from the at least one recommended search strategy as a target search strategy matching the user query) and determining a target search strategy based on comparing the target selection rate corresponding to respective search strategy (step 550 of Fig 5, Fig.6; ¶[0071],[0074] and [0117], Zhao, determining at least one recommended search strategy among the plurality of search strategies based on the similarity scores), and the data selection rate stored in the cache is determined based on real selection rates obtained from multiple historical data queries (¶[0015]-[0016],[0074] and [0117], Zhao, i.e., the similarity score “selection rate” is determined based on the historical user query corresponding to the search record and the corresponding historical recommended search strategy based on the preliminary model for each search record of the first set and the second set).
It would have been obvious to a person having ordinary skill in the art before the effective filing date, having both Day and Zhao before them to modify the search strategies of Zhao into Day, as taught by Zhao. One of ordinary skill in the art would be motivated to integrate the search strategies into Day, with a reasonable expectation of success, in order to enhance execution strategy for database query.
The modified Day, however, does not explicitly disclose wherein the data selection rate is determined based on a proportion of an amount of data that has been queried in a database during one historical data query to a total amount of data in the database.
Oztekin disclose generating improved search document using historical search results (¶[0032]-[0033], Ozteikin), wherein the data selection rate is determined based on a proportion of an amount of data that has been queried in a database during one historical data query to a total amount of data in the database (¶[0032]-[0033] and [0062]-[0063], Ozteikin), determining a data selection rate corresponding to one search strategy based on an amount of data in a database (¶[0033], Oztekin) that does not need to be queried and is filtered out during one historical data query (¶[0033] and [0062]-[0063], Oztekin, i.e., selection ratio based on unfiltered category list “not need to be queried”) and is filtered out during one historical data query (¶ [0062]-[0063], Oztekin), the data selection rate representing a ratio of queried data in the database during the one historical data query to total data in the database (¶[0033] and [0062]-[0063], Oztekin).
It would have been obvious to a person having ordinary skill in the art before the effective filing date, having modified Day and Oztekin before them to modify the search strategies of Oztekin into the modified Day, as taught by Oztekin. One of ordinary skill in the art would be motivated to integrate the search strategies into the modified Day, with a reasonable expectation of success, in order to enhance execution strategy for search content query.
Regarding claim 3, Day/Zhao/Oztekin combination discloses wherein the determining the target selection rate corresponding to the search strategy by sampling data obtained from the database (¶[0074] and [0137]-[0141], Zhao) comprises: acquiring the sampling data from the database, wherein the sampling data is determined based on a selected sampling granularity and/or a number of sampling lines (¶[0074] and [0137]-[0141], Zhao); and determining sample data that has been queried in the sampling data by the search strategy, and taking a proportion of the sample data in the sampling data as the target selection rate associated with the search strategy (¶[0070]-[0072] and [0074], Zhao).
Regarding claim 4, Day/Zhao/Oztekin combination discloses wherein, after determining the plurality of search strategies that match the target data, the method further comprises: performing queries in the database using each search strategy respectively (¶[0067], [0074] and [0137]-[0141], Zhao), and determining a data selection rate corresponding to the search strategy based on a proportion of data that has been queried in the database during the query (¶[0057]-[0058] and [0067]-[0070], Day).
Regarding claim 5, Day/Zhao/Oztekin combination discloses wherein, after determining a data selection rate corresponding to the search strategy based on a proportion of data that has been queried in the database during the query (¶[0057]-[0058] and [0067]-[0070], Day), the method further comprises: comparing a difference between a currently determined data selection rate and a data selection rate corresponding to a historical query process to determine whether the currently determined data selection rate meets a stability condition (¶[0049]-[0052], Zhao); and if the stability condition is satisfied (¶[0049]-[0052], Zhao), taking the currently determined data selection rate as a fixed data selection rate of the data query request under the search strategy (¶[0070]-[0072] and [0074], Zhao).
Regarding claim 8, Day discloses an electronic device, comprising a processor and a non-transitory memory with instructions stored thereon, wherein the instructions upon execution by the processor, cause the processor to:
receiving a data query request (¶ [0035]-[0038] and [0055]-[0056], Day, optimizing index search or table scan for a search strategy);
determining a plurality of search strategies that match target data as indicated by the data query request (¶[0051]-[0052] and [0058]-[0059], Day, evaluating all of the records “a table scan strategy” or to evaluate some subset of records which satisfy one of the conditions, the subset being produced by comparing the condition to the corresponding index “an index search strategy”); for each search strategy, querying a data selection rate stored in association with the search strategy from a cache (¶[0056]-[0058], Day, generating an optimized execution strategy for the query, this optimized strategy is saved in cache as a strategy block with the query object based on user’s selection), wherein the cache is used to dynamically maintain the data selection rate corresponding to each search strategy (¶[0055]-[0058], Day, i.e., dynamic strategy queries); and
in response to an existence of the data selection rate stored in association with the search strategy (¶[0057]-[0058] and [0070], Day, i.e., If a suitable strategy does exist (the `Y` branch from step 504), a strategy is selected (step 506)), taking the data selection rate as a target selection rate corresponding to the search strategy (¶[0057]-[0058] and [0070], Day); and
in response to a search strategy to be selected being a first-time selected search strategy, determining the target selection rate corresponding to the search strategy by sampling data obtained from the database, wherein the sampling data is determined based on a selected sampling granularity and/or a number of sampling lines (¶[0055]-[0058] and [0070], Day).
Day, however, does not explicitly disclose determining a plurality of search strategies that match target data as indicated by the data query request and determining a target search strategy based on the target selection rate corresponding to respective search strategy, and the data selection rate stored in the cache is determined based on real selection rates obtained from multiple historical data queries.
Zhao discloses receiving a data query request (step 510 of Fig.5; ¶[0052] and [0069], Zhao), determining a plurality of search strategies that match target data as indicated by the data query request (step 520 of Fig 5 and search strategy/second module of Fig.6; ¶[0052] and [0069]-[0070], Zhao, obtaining a plurality of search strategies matching the user query in response to the user query); in response to an existence of the data selection rate/score stored in association with the search strategy, taking the data selection rate/score as a target selection rate/score corresponding to the search strategy (¶[0070]-[0072] and [0074], Zhao, i.e., selecting a specific search strategy from the at least one recommended search strategy as a target search strategy matching the user query) and determining a target search strategy based on the target selection rate corresponding to respective search strategy (step 550 of Fig 5, Fig.6; ¶[0071],[0074] and [0117], Zhao, determining at least one recommended search strategy among the plurality of search strategies based on the similarity scores), and the data selection rate stored in the cache is determined based on real selection rates obtained from multiple historical data queries (¶[0015]-[0016],[0074] and [0117], Zhao, i.e., the similarity score “selection rate” is determined based on the historical user query corresponding to the search record and the corresponding historical recommended search strategy based on the preliminary model for each search record of the first set and the second set).
It would have been obvious to a person having ordinary skill in the art before the effective filing date, having both Day and Zhao before them to modify the search strategies of Zhao into Day, as taught by Zhao. One of ordinary skill in the art would be motivated to integrate the search strategies into Day, with a reasonable expectation of success, in order to enhance execution strategy for database query.
The modified Day, however, does not explicitly disclose wherein the data selection rate is determined based on a proportion of an amount of data that has been queried in a database during one historical data query to a total amount of data in the database.
Oztekin disclose generating improved search document using historical search results (¶[0032]-[0033], Ozteikin), wherein the data selection rate is determined based on a proportion of an amount of data that has been queried in a database during one historical data query to a total amount of data in the database (¶[0032]-[0033] and [0062]-[0063], Ozteikin), determining a data selection rate corresponding to one search strategy based on an amount of data in a database (¶[0033], Oztekin) that does not need to be queried and is filtered out during one historical data query (¶[0033] and [0062]-[0063], Oztekin, i.e., selection ratio based on unfiltered category list “not need to be queried”) and is filtered out during one historical data query (¶ [0062]-[0063], Oztekin), the data selection rate representing a ratio of queried data in the database during the one historical data query to total data in the database (¶[0033] and [0062]-[0063], Oztekin).It would have been obvious to a person having ordinary skill in the art before the effective filing date, having modified Day and Oztekin before them to modify the search strategies of Oztekin into the modified Day, as taught by Oztekin. One of ordinary skill in the art would be motivated to integrate the search strategies into the modified Day, with a reasonable expectation of success, in order to enhance execution strategy for search content query.
Regarding claim 10, Day/Zhao/Oztekin combination discloses wherein the determining the target selection rate corresponding to the search strategy by sampling data obtained from the database (¶[0074] and [0137]-[0141], Zhao) comprises: acquiring the sampling data from the database, wherein the sampling data is determined based on a selected sampling granularity and/or a number of sampling lines (¶[0074] and [0137]-[0141], Zhao); and determining sample data that has been queried in the sampling data by the search strategy, and taking a proportion of the sample data in the sampling data as the target selection rate associated with the search strategy (¶[0070]-[0072] and [0074], Zhao).
Regarding claim 11, Day/Zhao/Oztekin combination discloses wherein, after determining the plurality of search strategies that match the target data, the method further comprises: performing queries in the database using each search strategy respectively (¶[0067], [0074] and [0137]-[0141], Zhao), and determining a data selection rate corresponding to the search strategy based on a proportion of data that has been queried in the database during the query (¶[0057]-[0058] and [0067]-[0070], Day).
Regarding claim 12, Day/Zhao/Oztekin combination discloses wherein, after determining a data selection rate corresponding to the search strategy based on a proportion of data that has been queried in the database during the query (¶[0057]-[0058] and [0067]-[0070], Day), the method further comprises: comparing a difference between a currently determined data selection rate and a data selection rate corresponding to a historical query process to determine whether the currently determined data selection rate meets a stability condition (¶[0049]-[0052], Zhao); and if the stability condition is satisfied (¶[0049]-[0052], Zhao), taking the currently determined data selection rate as a fixed data selection rate of the data query request under the search strategy (¶[0070]-[0072] and [0074], Zhao).
Regarding claim 15, Day discloses a non-transitory computer-readable storage medium storing instructions that cause a processor to:
receiving a data query request (¶ [0035]-[0038] and [0055]-[0056], Day, optimizing index search or table scan for a search strategy);
determining a plurality of search strategies that match target data as indicated by the data query request (¶[0051]-[0052] and [0058]-[0059], Day, evaluating all of the records “a table scan strategy” or to evaluate some subset of records which satisfy one of the conditions, the subset being produced by comparing the condition to the corresponding index “an index search strategy”); for each search strategy, querying a data selection rate stored in association with the search strategy from a cache (¶[0056]-[0058], Day, generating an optimized execution strategy for the query, this optimized strategy is saved in cache as a strategy block with the query object based on user’s selection), wherein the cache is used to dynamically maintain the data selection rate corresponding to each search strategy (¶[0055]-[0058], Day, i.e., dynamic strategy queries); and
in response to an existence of the data selection rate stored in association with the search strategy (¶[0057]-[0058] and [0070], Day, i.e., If a suitable strategy does exist (the `Y` branch from step 504), a strategy is selected (step 506)), taking the data selection rate as a target selection rate corresponding to the search strategy (¶[0057]-[0058] and [0070], Day); and
in response to a search strategy to be selected being a first-time selected search strategy, determining the target selection rate corresponding to the search strategy by sampling data obtained from the database, wherein the sampling data is determined based on a selected sampling granularity and/or a number of sampling lines (¶[0055]-[0058] and [0070], Day).
Day, however, does not explicitly disclose determining a plurality of search strategies that match target data as indicated by the data query request and determining a target search strategy based on the target selection rate corresponding to respective search strategy, and the data selection rate stored in the cache is determined based on real selection rates obtained from multiple historical data queries.
Zhao discloses receiving a data query request (step 510 of Fig.5; ¶[0052] and [0069], Zhao), determining a plurality of search strategies that match target data as indicated by the data query request (step 520 of Fig 5 and search strategy/second module of Fig.6; ¶[0052] and [0069]-[0070], Zhao, obtaining a plurality of search strategies matching the user query in response to the user query); in response to an existence of the data selection rate/score stored in association with the search strategy, taking the data selection rate/score as a target selection rate/score corresponding to the search strategy (¶[0070]-[0072] and [0074], Zhao, i.e., selecting a specific search strategy from the at least one recommended search strategy as a target search strategy matching the user query) and determining a target search strategy based on the target selection rate corresponding to respective search strategy (step 550 of Fig 5, Fig.6; ¶[0071],[0074] and [0117], Zhao, determining at least one recommended search strategy among the plurality of search strategies based on the similarity scores), and the data selection rate stored in the cache is determined based on real selection rates obtained from multiple historical data queries (¶[0015]-[0016],[0074] and [0117], Zhao, i.e., the similarity score “selection rate” is determined based on the historical user query corresponding to the search record and the corresponding historical recommended search strategy based on the preliminary model for each search record of the first set and the second set).
It would have been obvious to a person having ordinary skill in the art before the effective filing date, having both Day and Zhao before them to modify the search strategies of Zhao into Day, as taught by Zhao. One of ordinary skill in the art would be motivated to integrate the search strategies into Day, with a reasonable expectation of success, in order to enhance execution strategy for database query.
The modified Day, however, does not explicitly disclose wherein the data selection rate is determined based on a proportion of an amount of data that has been queried in a database during one historical data query to a total amount of data in the database.
Oztekin disclose generating improved search document using historical search results (¶[0032]-[0033], Ozteikin), wherein the data selection rate is determined based on a proportion of an amount of data that has been queried in a database during one historical data query to a total amount of data in the database (¶[0032]-[0033] and [0062]-[0063], Ozteikin), determining a data selection rate corresponding to one search strategy based on an amount of data in a database (¶[0033], Oztekin) that does not need to be queried and is filtered out during one historical data query (¶[0033] and [0062]-[0063], Oztekin, i.e., selection ratio based on unfiltered category list “not need to be queried”) and is filtered out during one historical data query (¶ [0062]-[0063], Oztekin), the data selection rate representing a ratio of queried data in the database during the one historical data query to total data in the database (¶[0033] and [0062]-[0063], Oztekin).It would have been obvious to a person having ordinary skill in the art before the effective filing date, having modified Day and Oztekin before them to modify the search strategies of Oztekin into the modified Day, as taught by Oztekin. One of ordinary skill in the art would be motivated to integrate the search strategies into the modified Day, with a reasonable expectation of success, in order to enhance execution strategy for search content query.
Regarding claim 17, Day/Zhao/Oztekin combination discloses wherein the determining the target selection rate corresponding to the search strategy by sampling data obtained from the database (¶[0074] and [0137]-[0141], Zhao) comprises: acquiring the sampling data from the database, wherein the sampling data is determined based on a selected sampling granularity and/or a number of sampling lines (¶[0074] and [0137]-[0141], Zhao); and determining sample data that has been queried in the sampling data by the search strategy, and taking a proportion of the sample data in the sampling data as the target selection rate associated with the search strategy (¶[0070]-[0072] and [0074], Zhao).
Regarding claim 18, Day/Zhao/Oztekin combination discloses wherein, after determining the plurality of search strategies that match the target data, the method further comprises: performing queries in the database using each search strategy respectively (¶[0067], [0074] and [0137]-[0141], Zhao), and determining a data selection rate corresponding to the search strategy based on a proportion of data that has been queried in the database during the query (¶[0057]-[0058] and [0067]-[0070], Day).
Regarding claim 19, Day/Zhao/Oztekin combination discloses wherein, after determining a data selection rate corresponding to the search strategy based on a proportion of data that has been queried in the database during the query (¶[0057]-[0058] and [0067]-[0070], Day), the method further comprises: comparing a difference between a currently determined data selection rate and a data selection rate corresponding to a historical query process to determine whether the currently determined data selection rate meets a stability condition (¶[0049]-[0052], Zhao); and if the stability condition is satisfied (¶[0049]-[0052], Zhao), taking the currently determined data selection rate as a fixed data selection rate of the data query request under the search strategy (¶[0070]-[0072] and [0074], Zhao).
Claims 6-7, 13-14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Day (US 2006/0074874 A1) in view of Zhao et al. (US 20210064665 A1), further in view of Oztekin et al. (US 20100262615 A1) and further in view of Azizi et al. (US 20180004668 A1).
Regarding claim 6, similar claim 13 and claim 20, Day/Zhao/Oztekin combination discloses wherein the performing queries in the database using each search strategy respectively (¶[0074] and [0137]-[0141], Zhao). However, the modified Day does not explicitly disclose querying tag information stored in the cache and associated with a search strategy under the data query request. Azizi discloses querying tag information stored in the cache and associated with a search strategy under the data query request (¶[0050], Azizi) and in response to the tag information indicates that a data selection rate in the cache corresponding to the search strategy does not meet the stability condition, querying in the database with the search strategy (¶[0030]-[0033], Azizi). It would have been obvious to a person having ordinary skill in the art before the effective filing date, having modified Day and Azizi before them to incorporate cache’s tag information of Azizi into the modified Day, as taught by Zhao. One of ordinary skill in the art would be motivated to integrate searchable cache’s content into the modified Day, with a reasonable expectation of success, in order to increase computer’s capabilities.
Regarding claim 7, similar claim 14, Day/Zhao/Oztekin combination discloses all of the claimed limitations as discussed above, except in response to a data variation of data in the database exceeding a preset variation threshold. Azizi discloses in response to a data variation of data in the database exceeding a preset variation threshold (¶[0046]-[0047] and [0054], Azizi), determining a search strategy to be deleted whose cache time exceeds a preset time threshold, and deleting the search strategy to be deleted and its associated stored data selection rate from the cache (¶[0046]-[0047] and [0054], Azizi). It would have been obvious to a person having ordinary skill in the art before the effective filing date, having modified Day and Azizi before them to incorporate cache’s tag information of Azizi into the modified Day, as taught by Zhao. One of ordinary skill in the art would be motivated to integrate searchable cache’s content into the modified Day, with a reasonable expectation of success, in order to increase computer’s capabilities.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Das et al. (US 20170017688 A1) disclose query results caching for database environments.
Abhinkar (US 20130262437 A1) discloses energy-efficient query optimization.
Galfond (US 20100325134 A1) discloses accuracy measurement of database search algorithms.
Tsuruta et al. (US 20100036802 A1) disclose repetitive fusion search method for search system.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HANH B THAI whose telephone number is (571)272-4029. The examiner can normally be reached Mon-Friday 7-4:30.
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/HANH B THAI/Primary Examiner, Art Unit 2163 March 4, 2026