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 .
The amendments were received on 9/18/2026. Claims 1-5, 7-15, and 17-20 are pending where claims 1-5, 7-15, and 17-20 were previously presented and claims 6 and 16 were cancelled.
35 USC § 112
The applicant amended the claims to address the 35 USC 112 rejections; in view of the amendments, the respective 35 USC 112 rejections have been withdrawn.
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 1-5, 7-15, and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
With regard to claim 1:
Step 2A, Prong One:
The claim recites the following limitations which are drawn towards an abstract idea:
A processing method, comprising: … obtaining first process information based on the first information, and obtaining second process information based on the second information (recites mental process steps of evaluating and analyzing information to selectively choose what information the user wants which is a judgement-type or decision step; see applicant’s paragraph 27 of specification for discussion of process information being feature information of the content);
generating a search request corresponding to the input information based on the first process information and the first form, and the second process information and the second form (recites mental process steps of evaluating and analyzing data to determine/translate the information to a different form, e.g. converting a user’s request in natural language sentence to a SQL query);
and determining a search result in a database based on the search request (recites mental process steps of evaluating/analyzing information via comparisons/matching to determine a result),
As seen from above, the identified limitations recite concepts associated with an abstract idea and thus the respective claim recites a judicial exception (see 2106.04(a)) and thus requires further analysis as discussed below.
Step 2A, Prong Two:
The following limitations have been identified as being additional elements as discussed below.
obtaining input information, the input information including first information in a first form and second information in a second form, the first form being different from the second form (recites insignificant extrasolution activity of receiving information, see MPEP 2106.05(g));
wherein the database includes information blocks obtained by dividing stored information based on different forms and preset information amounts (recites insignificant extrasolution activity of sorting information, see MPEP 2106.05(g)),
the different forms are associated with different modalities of data, and each of the information blocks corresponds to a first index and a second index (recites field of use limitations describing the intended data format or at least that multiple data formats are utilized by the system, see MPEP 2106.05(h)),
the first index includes summary information obtained by extracting information in the information blocks, and the second index includes information in the information blocks (recites field of use limitations describing at a high-level of generality the intended meaning of the information in the respective indexes, see MPEP 2106.05(h)).
As seen from the above discussion, the identified limitations did not integrate the judicial exception into a practical application (see MPEP 2106.04(d)). This judicial exception is not integrated into a practical application because the additional elements appear to merely receive the receiving of information (mere data gathering) and sorting/dividing information as well as intended meaning/formats of the respective data and add no meaningful limitation beyond that of the abstract idea.
Step 2B:
Below is the analysis of the claims:
obtaining input information, the input information including first information in a first form and second information in a second form, the first form being different from the second form (recites well-understood, routine, and conventional activity of receiving information, see MPEP 2106.05(d));
wherein the database includes information blocks obtained by dividing stored information based on different forms and preset information amounts (recites well-understood, routine, and conventional activity of sorting information, see MPEP 2106.05(d)),
the different forms are associated with different modalities of data, and each of the information blocks corresponds to a first index and a second index (recites field of use limitations describing the intended data format or at least that multiple data formats are utilized by the system, see MPEP 2106.05(h)),
the first index includes summary information obtained by extracting information in the information blocks, and the second index includes information in the information blocks (recites field of use limitations describing at a high-level of generality the intended meaning of the information in the respective indexes, see MPEP 2106.05(h)).
As seen from above, the respective claim elements taken individually do not amount to significantly more than the judicial exception. When taken as a whole (in combination), the claim also does not amount to significantly more than the abstract idea because the additional elements appear to merely receive the receiving of information (mere data gathering) and sorting/dividing information as well as intended meaning/formats of the respective data and add no meaningful limitation beyond that of the abstract idea.
With regard to claim 2, this claim recites converting the first information into third information in a third form (recites mental process steps of coding/encoding information from a first format to a second format such as Huffman coding),
wherein obtaining the first process information and obtaining the second process information includes: obtaining the first process information according to the first information, obtaining the second process information according to the second information, and obtaining third process information according to the third information (recites mental process steps of evaluating and analyzing information to selectively choose what information the user wants which is a judgement-type or decision step; see applicant’s paragraph 27 of specification for discussion of process information being feature information of the content),
and wherein generating the search request includes: generating the search request corresponding to the input information according to the first process information and the first form, the second process information and the second form, and the third process information and the third form, wherein the third form is the same as or different from the second form (recites mental process steps of evaluating and analyzing data to determine/translate the information to a different form, e.g. converting a user’s request in natural language sentence to a SQL query).
With regard to claim 3, this claim recites wherein obtaining the first process information and obtaining the second process information includes converting the first information into a first feature vector and converting the second information into a second feature vector (recites mental process steps of translating/converting content from a first format to a second format),
and wherein generating the search request includes generating the search request according to the first feature vector, the first form, the second feature vector, and the second form (recites mental process steps of evaluating and analyzing data to determine/translate the information to a different form, e.g. converting the input information into a particular request format).
With regard to claim 4, this claim recites wherein generating the search request includes: acquiring an association relationship between the first information and the second information (recites mental process steps of evaluating and analyzing information to determine how related two different datasets are and importance of each respective input dataset);
determining a first weighted coefficient of the first feature vector and a second weighted coefficient of the second feature vector based on the association relationship; and based on the first weighted coefficient and the second weighted coefficient, the first form corresponding to the first feature vector, and the second form corresponding to the second feature vector, weighting the first feature vector and the second feature vector to generate the search request (recites mental process steps of evaluating/determining what feature set the user is going to give most importance too with respect to how they are going to search and do comparisons to find results, e.g. if first information isn’t as important as second information, 20% vs 80%; finding a result that matches the first information exactly but isn’t relevant to the second information would be evaluated/analyzed and determined to not be a relevant result).
With regard to claim 5, this claim recites wherein determining the first weighted coefficient and the second weighted coefficient includes: determining a search form of a search result based on the input information, the search form being the first form or the second form (recites mental process steps of determining/thinking/deciding what the desired output format for a preferred result should be, e.g. if the user is thinking of searching for corgis, they might decide that whether they want text results such as scientific information about corgi breeds; images to see the dog; or videos of the dog);
and determining the first weighted coefficient and the second weighted coefficient based on the search form and the association relationship (recites mental process steps of evaluating/determining what feature set the user is going to give most importance too with respect to how they are going to search and do comparisons to find results, e.g. if first information isn’t as important as second information, 20% vs 80%; finding a result that matches the first information exactly but isn’t relevant to the second information would be evaluated/analyzed and determined to not be a relevant result).
With regard to claim 7, this claim recites obtaining the search result by mapping the search request with the first index in the database; or obtaining the search result by mapping the search request with the first index in the database to obtain at least one information block; and obtaining the search request that maps at least one piece of information in the at least one information block (recites mental process steps of comparing information such as requested information to stored information to determine where a result is, e.g. similar to how a user would use a card catalog to compare information to determine where a result is stored in order to retrieve it).
With regard to claim 8, this claim recites in response to an information amount of the search result being less than an information amount threshold, determining at least one target information block associated with the second index; and updating the search result based on the at least one target information block (recites mental process steps of determining when to stop researching/searching for information, e.g. for a student that is required to have at least some number (e.g. 5) of different authoritative sources for their research paper, if the initial index only resulted in 3 references/documents/sources being found, then the student would check another index to try to find more references/documents/sources).
With regard to claim 9, this claim recites determining a search result in a database based on the search request (recites mental process steps of evaluation and comparison steps to form a determination);
and sorting and outputting information blocks of different forms in the search result based on the first form and the second form (recites insignificant extrasolution activity of sorting and transmitting information which amounts to well-understood, routine, and conventional activity of sorting and transmitting information, see MPEP 2106.05(d)).
With regard to claim 10, this claim recites wherein sorting and outputting the information blocks includes: mapping information form of each information block in the search result with the first form and the second form to determine a first correlation coefficient of each information block (recites mental process steps of evaluating/analyzing the format type of the respective information);
keyword mapping summary information corresponding to each of information blocks in the search result with the search request to obtain a second correlation coefficient of the each of information blocks (recites mental process steps of evaluating/analyzing result items to determine their subject matter relevance);
semantically mapping information of the each of information blocks in the search result with the search request to obtain a third correlation coefficient of the each of information blocks (recites mental process steps of evaluating and forming judgements/decisions as to the relevance of the result as a whole versus its abstract or summary);
weighted averaging the first correlation coefficient, the second correlation coefficient and the third correlation coefficient to obtain target correlation coefficients of the information blocks (recites mental process steps involving mathematical calculation of prioritizing the various features of a result to determine the expected overall relevance of the result);
and sorting the target correlation coefficients to obtain a sorting result of the information blocks in the search result (recites insignificant extrasolution activity of sorting information which amounts to well-understood, routine, and conventional activity of sorting information, see MPEP 2106.05(d)).
With regard to claim 11, this claim is substantially similar to claim 1 and is rejected for similar reasons as discussed above. The main difference between claims 1 and 11 is that claim 11 recites an electric device comprising a memory and one or more processors which amounts to reciting generic computer elements at a high-level of generality to apply the abstract idea (see MPEP 2106.05(f)) and add no meaningful limitation beyond the abstract idea as discussed with regard to claim 1.
With regard to claims 12-19, these claims are substantially similar to claims 2-5 and 7-9 and are rejected for similar reasons as discussed above.
With regard to claim 20, this claim is substantially similar to claim 1 and is rejected for similar reasons as discussed above. The main difference between claims 1 and 20 is that claim 20 recites a computer-readable storage medium which amounts to reciting generic computer elements at a high-level of generality to apply the abstract idea (see MPEP 2106.05(f)) and add no meaningful limitation beyond the abstract idea as discussed with regard to claim 1.
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.
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, 3-5, 7, 9, 11, 13-15, 17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al [US 2017/0364594] in view of Aggarwal et al [US 2020/0380027 A1].
With regard to claim 1, Chen teaches a processing method, comprising: obtaining input information (see paragraph [0048]; the system can receive input information from a user as a search request),
generating a search request corresponding to the input information … (see paragraph [0068]; the system can utilize the input information to issue a query to respective underlying search engines, i.e. generate a search request);
and determining a search result in a database based on the search request (see paragraphs [0070] and [0048]; the system is able to utilize the search query to determine and return search results).
wherein the database includes information blocks obtained by dividing stored information based on different forms and preset information amounts, the different forms are associated with different modalities of data, and each of the information blocks corresponds to a first index and a second index, the first index includes summary information obtained by extracting information in the information blocks, and the second index includes information in the information blocks (see Figures 3 and 8 and paragraphs [0062]-[0064] and [0044] and [0046]; the system can extract/divide stored information into information blocks of different modalities such as text and images where at least one of the index relates to summarization information, e.g. text index 319, and another index stores information of an information block such as image/feature index).
Chen does not appear to explicitly teach:
the input information including first information in a first form and second information in a second form, the first form being different from the second form;
obtaining first process information based on the first information, and obtaining second process information based on the second information;
generating a search request corresponding to the input information based on the first process information and the first form, and the second process information and the second form.
Aggarwal teaches the input information including first information in a first form and second information in a second form, the first form being different from the second form (see paragraph [0079] and [0080]; the system can obtain input information including first information in a first form (e.g. text) and second information in a second form (e.g. image), “In some instances, the input (e.g., a search query input) includes both text and digital images”, para 80);
obtaining first process information based on the first information, and obtaining second process information based on the second information (see paragraph [0080]; the system provides means to obtain process information/feature information such as via embeddings/vectorization);
generating a search request corresponding to the input information based on the first process information and the first form, and the second process information and the second form (see paragraphs [0081], [0096], and [0098] and Figures 6 and 7; the system can generate a single search request that relates to respective inputs);
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the search system of Chen by being able to provide a multi-modal input as a query as taught by Aggarwal in order to allow for embeddings of the different input items to be generated and used in combination via vector algebra so that the system can support different weights of the input items thus helping to quickly find relevant results to the user while expanding functionality on how the user is able express their search input.
With regard to claim 3, Chen in view of Aggarwal teach wherein obtaining the first process information and obtaining the second process information includes converting the first information into a first feature vector and converting the second information into a second feature vector (see Aggarwal, paragraph [0080]; the system provides means to obtain process information/feature information such as via embeddings/vectorization),
and wherein generating the search request includes generating the search request according to the first feature vector, the first form, the second feature vector, and the second form (see Aggarwal, paragraphs [0081], [0096], and [0098] and Figures 6 and 7; the system can generate a single search request that relates to respective inputs).
With regard to claim 4, Chen in view of Aggarwal teach wherein generating the search request includes: acquiring an association relationship between the first information and the second information; determining a first weighted coefficient of the first feature vector and a second weighted coefficient of the second feature vector based on the association relationship; and based on the first weighted coefficient and the second weighted coefficient, the first form corresponding to the first feature vector, and the second form corresponding to the second feature vector, weighting the first feature vector and the second feature vector to generate the search request (see Aggarwal, paragraphs [0034], [0095], and [0051]-[0053]; the system can determine a relationship between the various input information as well as having means to specify a weight value/coefficient for the respective embeddings/vectors which will be utilized to find similar content, i.e. search results).
With regard to claim 5, Chen in view of Aggarwal teach wherein determining the first weighted coefficient and the second weighted coefficient includes: determining a search form of a search result based on the input information, the search form being the first form or the second form; and determining the first weighted coefficient and the second weighted coefficient based on the search form and the association relationship (see Aggarwal, paragraphs [0034] [“Weights may also be employed to specify the emphasis of each constraint, i.e., individual items in the search query. The weights, for instance, may be specified manually by a user (e.g., through use of a slide bar), specified automatically based on a modal type of constraint (e.g., to give different weights to text versus digital images), and so forth.”], and see paragraph [0053]; the system can determine various weights for coefficients/constraints of the desired result based on input information including the ability of the user to specify preference of a digital output and be able to calculate/determine the respective weighted coefficient based on the relationship of preferences between the respective form types).
With regard to claim 7, Chen in view of Aggarwal teach wherein the determining the search result includes: obtaining the search result by mapping the search request with the first index in the database; or mapping the search request with the first index in the database to obtain at least one information block; and obtaining the search result by retrieving at least one piece of information in the at least one information block (see Chen, paragraphs [0048] and [0070]; the system can find search results via mapping the request to the first index).
With regard to claim 9, Chen in view of Aggarwal teach sorting and outputting information blocks of different forms in the search result based on the first form and the second form (see Chen, paragraph [0070] and Figure 10; the system can sort and output the respective information blocks based on the input query).
With regard to claims 11 and 20, these claims are substantially similar to claim 1 and are rejected for similar reasons as discussed above.
With regard to claims 13-15, 17, and 19, these claims are substantially similar to claims 3-5, 7, and 9 and are rejected for similar reasons as discussed above.
Claims 2 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al [US 2017/0364594] in view of Aggarwal et al [US 2020/0380027 A1] in further view of Hu et al [US 2019/0236167 A1].
With regard to claim 2, Chen in view of Aggarwal teach all the claim limitations of claim 1 as discussed above.
Chen in view of Aggarwal do not appear to explicitly teach:
converting the first information into third information in a third form,
wherein obtaining the first process information and obtaining the second process information includes: obtaining the first process information according to the first information, obtaining the second process information according to the second information, and obtaining third process information according to the third information,
and wherein generating the search request includes: generating the search request corresponding to the input information according to the first process information and the first form, the second process information and the second form, and the third process information and the third form, wherein the third form is the same as or different from the second form.
Hu teaches converting the first information into third information in a third form (see paragraphs [0021] and [0035]; the system can convert/transform/generate the first input information such as an image into third information in a third form such as text).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the multi-modal search of Chen in view of Aggarwal by being able to generate a textual representation of image content and be able to utilize that textual representation in a search process as taught by Hu in order to not only capture the visual features of an image but also be able to analyze and discern description information about the image thereby allowing the search system to be able to utilize additional information to filter/match the query to potential results based, not only on similarity to the input image, but also concepts associated or represented by the image thereby helping to provide more contextually relevant results to the user versus results that are similar in visual style to the input query image.
Chen in view of Aggarwal in further view of Hu teach wherein obtaining the first process information and obtaining the second process information includes: obtaining the first process information according to the first information, obtaining the second process information according to the second information, and obtaining third process information according to the third information (see Hu, paragraphs [0021] and [0035]; see Aggarwal, paragraphs [0080] and [0051]-[0052]; the system can obtain feature/vector information for the respective input information and derived information and utilize that information as part of the query),
and wherein generating the search request includes: generating the search request corresponding to the input information according to the first process information and the first form, the second process information and the second form, and the third process information and the third form, wherein the third form is the same as or different from the second form (see Hu, paragraphs [0021] and [0035]; see Aggarwal, paragraphs [0081], [0096], and [0098] and Figures 6 and 7; the system can generate a single search request that relates to respective inputs that includes the various process information/embeddings).
With regard to claim 12, this claim is substantially similar to claim 2 and is rejected for similar reasons as discussed above.
Claims 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al [US 2017/0364594] in view of Aggarwal et al [US 2020/0380027 A1] in further view of Taank [US 2014/0310270 A1].
With regard to claim 8, Chen in view of Aggarwal teach all the claim limitations of claims 1 and 7 as discussed above.
Chen in view of Aggarwal teach search results but do not appear to explicitly teach: in response to an information amount of the search result being less than an information amount threshold, determining at least one target information block associated with the second index; and updating the search result based on the at least one target information block.
Taank teaches in response to an information amount of the search result being less than an information amount threshold, determining at least one target information block
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the multi-modal search of Chen in view of Aggarwal by including means dynamically adjust the amount of results that are provided response to a search request as taught by Taank in order to provide means to make the display of search results more concise and focused for users when the number of results to too many as well as expanding the number of results when the number of results is too few automatically thereby improving system versatility and flexibility by being able to both not overburden the user with lots of semi-relevant results while also being able to ensure that the user isn’t dissatisfied by not finding what they are looking for when the system provides too few results.
Chen in view of Aggarwal in further view of Taank teach in response to an information amount of the search result being less than an information amount threshold, determining at least one target information block associated with the second index; and updating the search result based on the at least one target information block (see Taank, paragraphs [0026]-[0028]; Chen, paragraphs [0070] and [0048]; the system can determine additional results responsive to the amount of results being too few).
With regard to claim 18, this claim is substantially similar to claim 8 and is rejected for similar reasons as discussed above.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Chen et al [US 2017/0364594] in view of Aggarwal et al [US 2020/0380027 A1] in further view of Zamir et al [US 2005/0240580 A1].
With regard to claim 10, Chen in view of Aggarwal teach all the claim limitations of claims 1 and 9 as discussed above.
Chen in view of Aggarwal teach wherein sorting and outputting the information blocks includes: mapping information form of each information block in the search result with the first form and the second form to determine a first correlation coefficient of each information block (see Aggarwal, paragraph [0034]; the system can give correlation coefficients/weights to the different format types).
Chen in view of Aggarwal do not appear to explicitly teach:
keyword mapping summary information corresponding to each of information blocks in the search result with the search request to obtain a second correlation coefficient of the each of information blocks;
semantically mapping information of the each of information blocks in the search result with the search request to obtain a third correlation coefficient of the each of information blocks;
weighted averaging the first correlation coefficient, the second correlation coefficient and the third correlation coefficient to obtain target correlation coefficients of the information blocks;
and sorting the target correlation coefficients to obtain a sorting result of the information blocks in the search result.
Zamir teaches semantically mapping information of the each of information blocks in the search result with the search request to obtain a third correlation coefficient of the each of information blocks (see paragraphs [0041]-[0042], [0050]-[0051], [0054], [0079]-[0080], and [0118]-[0124]; the system is able to determine a matching of the result to the search request while ranking of the result with respect to the user request including determining coefficients/scores for keyword mapping summary information such as importance of keywords to a user as well as semantically mapping information or topics/categories, e.g. TermScore and CategoryScore);
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the multi-modal search of Chen in view of Aggarwal by being able to utilize various pieces of information associated with user preferences such as preferred keywords and topics when determining relevance of a result with respect to a particular user as taught by Zamir in order to be able to personalize results instead of providing system generic results by leveraging user preferences to determine which of the relevant results are more likely preferred to a particular user thus saving the user time of having to scroll and review results to find the result(s) that they most desire.
Chen in view of Aggarwal in further view of Zamir teach weighted averaging the first correlation coefficient, the second correlation coefficient and the third correlation coefficient to obtain target correlation coefficients of the information blocks (see Zamir, paragraphs [0079]-[0080]; see Aggarwal, paragraphs [0091]-[0093] and [0101]-[0104]; the system has means to provide weighed averaging the various coefficients/scores to form an overall score);
and sorting the target correlation coefficients to obtain a sorting result of the information blocks in the search result (see Zamir, paragraphs [0079]-[0080] and [0098]-[0101]; see Aggarwal, paragraphs [0091]-[0093] and [0101]-[0104]; the system can sort/rank the respective results for the user).
Response to Arguments
Applicant’s arguments (see the second and third paragraphs on page 13) with respect to the objections to the specification/Title have been fully considered and are persuasive. The objections of the specification/Title have been withdrawn.
Applicant’s arguments (see the fourth and fifth paragraphs on page 13) with respect to the 35 USC 112 rejections have been fully considered and are persuasive. The 35 USC 112 rejections have been withdrawn. The applicant amended the claims to address the 35 USC 112 rejections; in view of the amendments, the respective 35 USC 112 rejections have been withdrawn.
Applicant's arguments (see the last paragraph on page 13 through the third from last paragraph on page 18) have been fully considered but they are not persuasive. The applicant argues that (a) the human mind is not equipped to extract machine-processable feature representations to generate a machine-usable search request or to determine search results in a database that is organized into form-based information blocks under a two-level index structure; (b) the claims integrate the judicial exception into a practical application via a technological improvement; (c) the respective data architecture is analogous to the self-referential table of Enfish; and (d) that the Office Action provides no evidence of the specific combination now claimed (amended) including the first index and second index. The Examiner respectfully disagrees.
With regard to argument (a), the Examiner notes that per MPEP 2106.04(a)(2)(III)(C) that a claim that requires a computer may still recite a mental process step. As noted in the 35 USC 101 rejections, the claims recite receiving a request and being able to identify desired information (generate a search request) and then determine/evaluate a search result (judgement/decision step). Although the claims may have the information in a computerized format, the respective usage of the computer is recited at a high-level of generality and merely recited to use the computer as a tool to perform the judicial exception. Accordingly, applicant’s arguments are not persuasive.
With regard to argument (b) regarding an improvement to the functioning of a computer or to any other technology or technical field, the Examiner notes that, per MPEP 2106.05(a), that “[a]n important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome. McRO, 837 F.3d at 1314-15, 120 USPQ2d at 1102-03; DDR Holdings, 773 F.3d at 1259, 113 USPQ2d at 1107.” (emphasis added). Additionally, it is important to note that “the judicial exception alone cannot provide the improvement” and that “the claim reflects the asserted improvement”. The claim limitations are recited at a fairly high-level of generality such that the broadest reasonable interpretation of various limitations including the preset information amounts can relate to preset information amounts being sentences. As seen from the 35 USC 101 rejections, although the database is organized the high-level recitation relates to sorting information where merely sorting information with the ‘determining a search result’ limitation merely indicating that it can find a result from the database with no other details on how that different indexes are utilized. Accordingly, applicant’s arguments are not persuasive.
With regard to argument (c) about the respective data architecture is analogous to the self-referential table of Enfish; the Examiner facts of Enfish appear to different significantly from the current claims and thus applicant’s arguments about their claims being analogous to Enfish is not persuasive.
With regard to argument (d), as shown in the 35 USC 101 rejections, the respective 35 USC 101 rejections have been updated to reflect the newly amended limitations including discussions of the intended data utilized in the database and respective indexes. Accordingly, in view of the updated 35 USC 101 rejections, applicant’s arguments are not persuasive.
Applicant’s arguments (see the second to last paragraph on page 18 through the last paragraph on page 20) with respect to the rejection(s) of claim(s) under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Chen. The applicant amended the claims to incorporate new limitations that changed claim scope and required further search and consideration. As shown in the 35 USC 103 rejections above, a new reference was found that, when combined, would teach the claim limitations as recited.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Sacheti et al [US 2024/0119095 A1] teaches at paragraph [0027] the system uses both a document index and search index.
Kotov et al [US 2022/0138247 A1] teaches at Figure 1 and paragraphs [0030], [0039], and [0077] the ability to form multiple different embeddings including having an embedding record for an image that includes an image embedding and text embedding for determining visual similarity and text similarity of two images.
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).
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/MARC S SOMERS/Primary Examiner, Art Unit 2159 10/6/2026
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