Notice of Pre-AIA or AIA Status
1. 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
2. This action is in response to the original filing on 07/10/2023. Claims 1-20 are pending and have been considered below.
Information Disclosure Statement
3. The information disclosure statement (IDS(s)) submitted on 07/10/2023 is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections – 35 USC § 103
4. 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 of this title, 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.
5. Claims 1-4 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Lee et al. (U.S. Patent Application Pub. No. US 20240097878 A1) in view of Fink et al. (U.S. Patent Application Pub. No. US 20220100884 A1).
Claim 1: Lee teaches a method comprising:
a plurality of metadata objects from a plurality of knowledge artifacts in a database (i.e. the above-described vector value calculation may be generated in advance at the server apparatus side. For example, a server apparatus may make in advance an index value corresponding to a document and a vector value for a corresponding document into one lookup table; para. [0173]), deriving the per-document index value and other document attributes (e.g., vector value) that function as metadata objects;
encrypting a portion of the plurality of metadata objects using homomorphic encryption (i.e. it has been described that the first comparison target data is made by inserting the vector value as it is to the slot, but in implementation, it is possible to homomorphically encrypt the vector value and store the same; para. [0142]) to generate a plurality of encrypted embeddings, wherein each encrypted embedding relates to content of a knowledge artifact (i.e. the server apparatus 200 may calculate a vector value having a preset size by using a preset encoding algorithm for each of a plurality of documents, and generate a calculation result ciphertext having a result of a preset homomorphic calculation between the calculated vector value for each of the plurality of documents and the query ciphertext; para. [0173]), encrypting document-derived representations using homomorphic encryption to generate encrypted embeddings;
receiving a plurality of encrypted similarity scores that are generated by processing a query, received from a user, against the plurality of encrypted embeddings (i.e. The server apparatus 200 may receive the query ciphertext from the electronic apparatus 100 and may, by using each of a plurality of documents and the query ciphertext, generate a calculation result ciphertext having similarity information about the query ciphertext with respect to each of a plurality of documents in operation S530; para. [0172, 0173, 0175]), a query ciphertext is compared against document vectors via homomorphic calculation, producing a calculation result ciphertext that contains similarity information for each document;
decrypting the plurality of encrypted similarity scores to obtain a decrypted plurality of similarity scores (i.e. the electronic apparatus 100 may receive a calculation result ciphertext having similarity information with a query for each of a plurality of indexes and may restore the calculation result ciphertext by using a secret key. Therefore, when the calculation result ciphertext is restored, similarity values with the transmitted query may be identified; para. [0177, 0178]);
identifying a particular knowledge artifact based on the decrypted plurality of similarity scores (i.e. when the calculation result ciphertext is restored, similarity values with the transmitted query may be identified, and a slot (or index) having similarity greater than or equal to a preset value may be identified in operation S550. At this time, one index may be determined, or a plurality of indexes may be determined; para. [0178]), the determined index corresponds to the document to request; and
providing a response to the user based on the particular knowledge artifact (i.e. the electronic apparatus 100 transmits the determined index to the server apparatus in operation S560. When receiving the index information from the electronic apparatus, the server apparatus 200 transmits a document corresponding to the index information, among a plurality of documents, to the electronic apparatus in operation S570. The electronic apparatus 100 receives a document corresponding to the index in operation S660; para. [0179-0181]).
Lee does not explicitly teach extracting metadata.
However, Fink teaches extracting a plurality of metadata objects from a plurality of knowledge artifacts in a database (i.e. The data repository server 210 performs a query analysis on each candidate document proceeding with the data repository server 210 by extracting information (including metadata (M)) from the server database 255 concerning a given document. The metadata (M) includes, but is not limited to, information such as document name, document summary, date, time, authorship; and the unique ID of the determined document nearest neighbor forest vector; para. [0059, 0060]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Lee to include the feature of Fink. One would have been motivated to make this modification because it provides a more complete and practical retrieval system, where metadata associated with stored documents is extracted and used for identifying and returning relevant documents.
Claim 2: Lee and Fink teach the method of claim 1. Lee does not explicitly teach wherein each knowledge artifact of the plurality of knowledge artifacts is selected from a group of: a frequently asked question and corresponding answer, and an article.
However, Fink further teaches wherein each knowledge artifact of the plurality of knowledge artifacts is selected from a group of: a frequently asked question and corresponding answer, and an article (i.e. a web search might include documents divided into metadata. The metadata may include the URL (uniform resource locator) identifier of a document, and the “content” or words in the document. Accordingly, any query submitted by the data requesting client 205 may aim to retrieve the metadata identifying a matching document stored in the database 255; para. [0029]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Lee to include the feature of Fink. One would have been motivated to make this modification because it provides a more complete and practical retrieval system, where metadata associated with stored documents is extracted and used for identifying and returning relevant documents.
Claim 3: Lee and Fink teach the method of claim 2. Lee further teaches wherein an encrypted embedding is generated for each paragraph (i.e. when the encryption target is text data, the processor 150 may perform processing for removing unnecessary symbols (for example, codes, special characters) and the like from the text data, and calculate vector values for each sentence by using a preset encoding algorithm for each sentence unit. At this time, the processor 150 may calculate a vector value for each sentence by using a Bidirectional Encoder Representations from Transformer (BERT) language model; para. [0114]).
Lee does not explicitly teach the article.
However, Fink further teaches the article (i.e. a web search might include documents divided into metadata. The metadata may include the URL (uniform resource locator) identifier of a document, and the “content” or words in the document. Accordingly, any query submitted by the data requesting client 205 may aim to retrieve the metadata identifying a matching document stored in the database 255; para. [0029]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Lee to include the feature of Fink. One would have been motivated to make this modification because it provides a more complete and practical retrieval system, where metadata associated with stored documents is extracted and used for identifying and returning relevant documents.
Claim 4: Lee and Fink teach the method of claim 1. Lee further teaches wherein the plurality of metadata objects that are not encrypted includes one or more of: a unique universal identifier for a corresponding knowledge artifact, a hash of the knowledge artifact, and a storage location of the knowledge artifact (i.e. the order index may be stored in a state of a plaintext; para. [0103, 0120]).
Fink further teaches wherein the plurality of metadata objects that are not encrypted includes one or more of: a unique universal identifier for a corresponding knowledge artifact, a hash of the knowledge artifact, and a storage location of the knowledge artifact (i.e. The database 255 may be a collection of data records (e.g., unencrypted documents) stored on a tangible memory device and accessible for reading or writing by the server processor 265. The data records may also include metadata associated with the documents. According to some example embodiments, the database 255 may be remote from the server processor 265 and may be accessible to the server processor 265 via the server communication interface 270. Via the server processor 265, the query executor module 260 may be configured to query the records in the database 255. As one example, a web search might include documents divided into metadata. The metadata may include the URL (uniform resource locator) identifier of a document, and the “content” or words in the document. Accordingly, any query submitted by the data requesting client 205 may aim to retrieve the metadata identifying a matching document stored in the database 255; para. [0029, 0059]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Lee to include the feature of Fink. One would have been motivated to make this modification because it provides a more complete and practical retrieval system, where metadata associated with stored documents is extracted and used for identifying and returning relevant documents.
Claim 6: Lee and Fink teach the method of claim 1. Lee further teaches comprising: providing the plurality of encrypted embeddings and the query to a remote computing entity, wherein the plurality of encrypted similarity scores are generated by the remote computing entity (i.e. a text search method of a server according to an example of the disclosure includes receiving a query ciphertext from an electronic apparatus, by using each of a plurality of documents and the query ciphertext, generating a calculation result ciphertext having similarity information with respect to the query ciphertext for each of the plurality of documents, transmitting the calculation result ciphertext to the electronic apparatus, and based on receiving index information from the electronic apparatus, transmitting a document corresponding to the index information, among the plurality of documents, to the electronic apparatus; para. [0020]), and wherein the query is encrypted using homomorphic embedding prior to being provided to the remote computing entity (i.e. the processor may generate a secret key and a public key corresponding to the secret key, and control the communication apparatus to transmit the query ciphertext and the public key together; para. [0018, 0019]).
6. Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Fink, and further in view of Krishna et al. (U.S. Patent Application Pub. No. US 20190325066 A1).
Claim 5: Lee and Fink teach the method of claim 1. Lee does not explicitly teach a topic or summary of the knowledge artifact, wherein the topic or the summary is generated using a trained machine learning model.
Fink further teaches a topic or summary of the knowledge artifact (i.e. The data repository server 210 performs a query analysis on each candidate document proceeding with the data repository server 210 by extracting information (including metadata (M)) from the server database 255 concerning a given document. The metadata (M) includes, but is not limited to, information such as document name, document summary, date, time, authorship; and the unique ID of the determined document nearest neighbor forest vector; para. [0059]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Lee to include the feature of Fink. One would have been motivated to make this modification because it provides a more complete and practical retrieval system, where metadata associated with stored documents is extracted and used for identifying and returning relevant documents.
However, Krishna teaches a topic or summary of the knowledge artifact, wherein the topic or the summary is generated using a trained machine learning model (i.e. The word generation model and the topic-aware encoding model are trained using machine learning techniques on artificially generated training data to generate the topic-based summaries; para. [0015]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the combination of Lee and Fink to include the feature of Krishna. One would have been motivated to make this modification because it improves the usability of the search responses.
7. Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Fink, and further in view of Roeder et al. (U.S. Patent Application Pub. No. US 20120078914 A1).
Claim 7: Lee and Fink teach the method of claim 1. Lee does not explicitly teach detecting an update to the database; and in response to detecting the update, generating an updated and providing the updated to the remote computing entity.
However Roeder teaches detecting an update to the database; and in response to detecting the update, generating an updated and providing the updated to the remote computing entity (i.e. the client device 102 generates at least one update-related token associated with the update operation to be performed. In block 1104, the client device 102 sends the updated-related token to the server 104. In block 1106, the server 104 receives the update-related token; para. [0073]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the combination of Lee and Fink to include the feature of Roeder. One would have been motivated to make this modification because it enables handling of databases updates and generation of updated to the remote computing entity.
8. Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Fink, and further in view of Vangala et al. (U.S. Patent Application Pub. No. US 20190318032 A1).
Claim 8: Lee and Fink teach the method of claim 1. Lee further teaches wherein an artificial conversation agent, the query from the user and provides the response to the user (i.e. the search method according to the disclosure may be applied to fields requiring protection while requiring natural language processing technologies such as voice recognition, chatbot, Ai speakers, and the like, and may be applied to various unstructured data such as text and voice as well as existing numerical data. In addition, it is possible to obtain a flexible search result that abundantly considers up to contextual information through the use of an embedding vector while protecting personal information from a server with respect to a query containing sensitive personal information; para. [0185, 0188, 0193]).
Lee does not explicitly teach wherein an artificial conversation agent obtains.
However, Vangala teaches wherein an artificial conversation agent obtains the query from the user and provides the response to the user (i.e. FIG. 16, a user 1690 may ask computerized personal assistant 1600, “What is a good restaurant near work?” as shown in dialogue bubble 1691. Accordingly, computerized personal assistant 1600 may recognize a computer-readable representation of the query (e.g., according to method 1800 at 1801). Computerized personal assistant 1600 may issue the query to be served by the user-centric AI knowledge base (e.g., via a query protocol useable by a plurality of different computer services, as described at 1804). The query may include a graph context constraint indicating “near work” and an answer type constraint indicating “restaurants.” Accordingly, computerized personal assistant 1600 may output a response to the query (e.g., as described at 1807) based on a subset of user-centric facts satisfying the graph context constraint and the answer type constraint; para. [0153]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the combination of Lee and Fink to include the feature of Vangala. One would have been motivated to make this modification because it improves usability of encrypted search
9. Claims 9-20 are similar in scope to Claims 1-8 and are rejected under a similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Ghafourifar et al. (Pub. No. US 11366839 B1), The Large Tag Cloud may then be compared at the server to other small and large tag clouds that have been generated for non-encrypted content that may share content-based similarities with the encrypted content in question. If a match is found between the tag clouds of the encrypted content in question and the tag clouds of one or more unencrypted (or encrypted) documents stored at the server, the encrypted content in question's tag cloud may be correlated with the tag clouds of the one or more matched unencrypted (or encrypted) documents, thus allowing the server to provide more relevant search results to the user-including the return of likely-relevant encrypted documents that the server does not actually have access to or the ability to decrypt.
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 U.S.P.Q. 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 U.S.P.Q. 275, 277 (C.C.P.A. 1968)).
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/TAN H TRAN/Primary Examiner, Art Unit 2141