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 .
DETAILED ACTION
This action is response to the communication filed on July 24, 2026. Claims 1-20 are pending.
Response to Arguments
Applicant’s argument regarding art rejection filed on July 24, 2026 have been considered but are moot in the view of new ground of rejection. Applicant argument regarding 101 rejection is not persuasive. The argument regarding 101 rejection are addressed in the new rejection.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Regarding the claim 1, it recites an indexing component that generates and stores a first text representation and a first vector representation of a reference dataset; a query processing component that generates a second text representation and a second vector representation of a query pertaining to a designated target content; and a matching component that matches the second text representation and the second vector representation of the query against the first text representation and the first vector representation of the reference dataset using vector-based filtering and applies text-based similarity scoring to identify potential attribution against the designated target content; determines whether the vector-based filtering is sufficient to establish a match; and selects between: applies the text-based similarity scoring to identify potential attribution against the designated target content, wherein the application is based on a first determination that the vector-based filtering is sufficient to establish the match; or applies an adjustable similarity threshold to determine whether the match is exact, near exact, or reworded based on a second determination that the vector-based filtering fails to be sufficient to establish the match
Claim recites the limitations of generates and stores ---, matches --, identify ---, and determine as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. User can mentally generate and store (i.e. memorize) text representation (both first and second) and vector representation (both firs and second) and compare those representation by applying vector based filtering and text based similarity score using physical aid (pen and paper). Hence, the limitations are a mental process. See MPEP 2106.04(a)(2) III, B, If a claim recites a limitation that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper, the limitation falls within the mental processes grouping, and the claim recites an abstract idea. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand.").
The claim recited the additional elements of applies the text-based similarity or applies an adjustable similarity which are insignificant extra-solution activity as these limitation are nothing but data manipulation and can be done by generic computer component. Accordingly, even in combination, the additional element does not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim directed to the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. With respect to integration of the abstract idea into a practical application the recited limitations are no more than mere instructions to apply the exception using a generic computer component such as indexing component, query processing component and matching component. The courts have recognized these functions as well‐understood, routine, and conventional as they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II, Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Claim 2 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 2 recites the same abstract idea of text attribution via similarity assessment. The claim recites the limitations of wherein the indexing component stores the first text representation and the first vector representation together in a structured index to improve retrieval efficiency, which can be done mentally with or without the use of a physical aid (e.g., pen and paper) or with a generic computer and is not an inventive concept that meaningfully limits the abstract idea. Therefore, the limitation is a mental process.
Claim 3 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 3 recites the same abstract idea of text attribution via similarity assessment. The claim recites the limitations of wherein the query processing component generates the second vector representation of a query text using at least one of: machine learning model, a neural network, or an embedding-based method, which can be done mentally with or without the use of a physical aid (e.g., pen and paper) or with a generic computer and is not an inventive concept that meaningfully limits the abstract idea. Therefore, the limitation is a mental process.
Claim 4 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 4 recites the same abstract idea of text attribution via similarity assessment. The claim recites the limitations of wherein the query processing component generates a variable- length text representation of the second text representation and a fixed-length vector representation of the second vector representation based on runtime properties of a query text, which can be done mentally with or without the use of a physical aid (e.g., pen and paper) or with a generic computer and is not an inventive concept that meaningfully limits the abstract idea. Therefore, the limitation is a mental process.
Claim 5 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 5 recites the same abstract idea of text attribution via similarity assessment. The claim recites the limitations of wherein the matching component applies an adjustable similarity threshold to determine whether a match is exact, near exact, or reworded, which can be done mentally with or without the use of a physical aid (e.g., pen and paper) or with a generic computer and is not an inventive concept that meaningfully limits the abstract idea. Therefore, the limitation is a mental process.
Claim 6 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 6 recites the same abstract idea of text attribution via similarity assessment. The claim recites the limitations of wherein the matching component combines shingles of variable lengths with indexed text to improve an accuracy of similarity detection, which can be done mentally with or without the use of a physical aid (e.g., pen and paper) or with a generic computer and is not an inventive concept that meaningfully limits the abstract idea. Therefore, the limitation is a mental process.
Claim 7 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 7 recites the same abstract idea of text attribution via similarity assessment. The claim recites the limitations of wherein the matching component applies a runtime-adjustable strictness parameter that allows variations in word order and text structure, which can be done mentally with or without the use of a physical aid (e.g., pen and paper) or with a generic computer and is not an inventive concept that meaningfully limits the abstract idea. Therefore, the limitation is a mental process.
Claim 8 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 8 recites the same abstract idea of text attribution via similarity assessment. The claim recites the limitations of wherein the matching component performs the vector-based filtering before applying the text-based similarity scoring, which can be done mentally with or without the use of a physical aid (e.g., pen and paper) or with a generic computer and is not an inventive concept that meaningfully limits the abstract idea. Therefore, the limitation is a mental process.
Claim 9 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 9 recites the same abstract idea of text attribution via similarity assessment. The claim recites the limitations of wherein the matching component incorporates context-aware analysis by weighting different portions of the first text representation and the second text representation and the first vector representation and the second vector representation based on semantic importance, which can be done mentally with or without the use of a physical aid (e.g., pen and paper) or with a generic computer and is not an inventive concept that meaningfully limits the abstract idea. Therefore, the limitation is a mental process.
Claim 10 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 10 recites the same abstract idea of text attribution via similarity assessment. The claim recites the limitations of a segmentation component that generates a shingle from a query text at runtime, wherein a shingle configuration is determined based on a use case and a text length, which can be done mentally with or without the use of a physical aid (e.g., pen and paper) or with a generic computer and is not an inventive concept that meaningfully limits the abstract idea. Therefore, the limitation is a mental process.
As to claims 11-20, they have similar limitations as of claims 1-10 above. Hence, they are rejected under the same rational as of claims 1-10 above.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Pathak et al. (Pub. No. : US 20260089128 A1) in the view of O’Toole et al. (Pub. No. : 20210216928 A1)
As to claim 1 Pathak teaches a system, comprising:
a processor that executes computer executable components stored in memory (paragraph [0027]: various functions may be carried out by a processor executing instructions stored in memory), wherein the computer executable components comprise:
an indexing component that generates and stores a first text representation and a first vector representation of a reference dataset (paragraphs [0090], [0007], [0031]: documents are indexed, chunked, and applied to an embedding model to generate embeddings corresponding to the chunks, wherein the one or more circuits can store the representation of the text in a vector database such as database 112 may be any type of vector database, which can store encoded text data 114 in association with corresponding multimedia identifier(s));
a query processing component that generates a second text representation and a second vector representation of a query pertaining to a designated target content (paragraphs [0049]-[0053]: searching the database 112 using a search query to identify a corresponding multimedia identifier 116 that is relevant to the search query, wherein queries generated for the vector database may be determined using the same encoding process used to generate the encoded text data 114, such that similarity scores can between the query and encoded text data 114 can be calculated using a suitable searching function); and
a matching component that matches the second text representation and the second vector representation of the query against the first text representation and the first vector representation of the reference dataset using vector-based filtering and applies text-based similarity scoring to identify potential attribution against the designated target content (paragraphs [0054], [0076]: the multimedia retriever 120 can identify a set of top entries of encoded text data 114 in the database 112 having the greatest similarity (e.g., the smallest distance) to the search query, wherein the search function may be a vector search function, which may return a predetermined number (e.g., according “top-k” configuration setting) of results that identify corresponding multimedia identifiers).
Pathak does not explicitly disclose but O’Toole teaches determines whether the vector-based filtering is sufficient to establish a match (paragraph [0135], [0292]: user selects filtering options, wherein the matches are vector embedded and a cosine similarity analysis performed to determine the sub-category with the highest cosine similarity score); and
selects between: applies the text-based similarity scoring to identify potential attribution against the designated target content, wherein the application is based on a first determination that the vector-based filtering is sufficient to establish the match; or applies an adjustable similarity threshold to determine whether the match is exact, near exact, or reworded based on a second determination that the vector-based filtering fails to be sufficient to establish the match (paragraphs [0276]-[0278], [0293]-[0294]: In step 1018, the labeling tool can use the similarity score to filter which labels are recommended to a user for confirming which labels are appropriate for particular threats (e.g., suggest categories with a score above a predefined amount and/or select a predefined number of the highest scored categories)). It whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify Pathak by adding above limitation as taught by O’Toole to reduce the time and improve the user experience on the alarm monitors (O’Toole, paragraph [0204]).
As to claim 2 Pathak together with O’Toole teaches a system according to claim 1. Pathak teaches wherein the indexing component stores the first text representation and the first vector representation together in a structured index to improve retrieval efficiency (paragraph [0053]).
As to claim 3 Pathak together with O’Toole teaches a system according to claim 1. Pathak teaches wherein the query processing component generates the second vector representation of a query text using at least one of: machine learning model, a neural network, or an embedding-based method (paragraph [0023]).
As to claim 4 Pathak together with O’Toole teaches a system according to claim 1. Pathak teaches wherein the query processing component generates a variable- length text representation of the second text representation and a fixed-length vector representation of the second vector representation based on runtime properties of a query text (paragraphs [0040], [0063]).
As to claim 5 Pathak together with O’Toole teaches a system according to claim 1. Pathak teaches wherein the matching component applies an adjustable similarity threshold to determine whether a match is exact, near exact, or reworded (paragraph [0055]).
As to claim 6 Pathak together with O’Toole teaches a system according to claim 1. Pathak teaches wherein the matching component combines shingles of variable lengths with indexed text to improve an accuracy of similarity detection (paragraph [0050]-[0054]).
As to claim 7 Pathak together with O’Toole teaches a system according to claim 1. Pathak teaches wherein the matching component applies a runtime-adjustable strictness parameter that allows variations in word order and text structure (paragraphs [0038], [0054]).
As to claim 8 Pathak together with O’Toole teaches a system according to claim 1. Pathak teaches wherein the matching component performs the vector-based filtering before applying the text-based similarity scoring (paragraph [0053]).
As to claim 9 Pathak together with O’Toole teaches a system according to claim 1. Pathak teaches wherein the matching component incorporates context-aware analysis by weighting different portions of the first text representation and the second text representation and the first vector representation and the second vector representation based on semantic importance (paragraph [0052]).
As to claim 10 Pathak together with O’Toole teaches a system according to claim 1. Pathak teaches further comprises a segmentation component that generates a shingle from a query text at runtime, wherein a shingle configuration is determined based on a use case and a text length (paragraph [0038]).
As to claims 11-20, they have similar limitations as of claims 1-10 above. Hence, they are rejected under the same rational as of claims 1-10 above.
Examiner's Note: Examiner has cited particular columns and line numbers or paragraphs in the references as applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in its entirety as potentially teaching of all or part of the claimed invention, as well as the context.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record, listed on form PTO-892, and not relied upon, if any, is considered pertinent to applicant's disclosure.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MD I UDDIN whose telephone number is (571)270-3559. The examiner can normally be reached M-F, 8:00 am to 5:00 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sherief Badawi can be reached at 571-272-9782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MD I UDDIN/Primary Examiner, Art Unit 2169
