# US 8,788,516 B1 · Generating and using social brains with complimentary semantic brains and indexes > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 8,788,516 B1 - Document ID: US8788516B1 - Status: Granted - Kind: B1 - Application number: 13/842,144 - Filed: 2013-03-15 - Granted: 2014-07-22 - Earliest claimed: 2013-03-15 - Assignees: PureDiscovery Corporation - Applicants: Paul A. Jakubik - Inventors: Paul A. Jakubik - Web page: https://patentgrep.com/patent/US8788516B1 ## CPC - G06Q 10/10: Office automation; Time management - G06Q 10/42: Determination of affinities or common interests between users - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract A method includes determining a plurality of social interactions associated with a plurality of people, generating a social object matrix using the determined social interactions, and generating a social brain by performing Singular Value Decomposition (SVD) on the social object matrix. The method further includes determining text from the social objects of the determined social interactions, generating a term-document matrix (TDM) using the determined text, generating a semantic brain by performing SVD on the TDM, generating an index using the determined text, and performing a query using the social brain, the semantic brain, and the index. The social brain is a singular value representation of the social object matrix and the semantic brain is a singular value representation of the TDM. Each social interaction is a particular person interacting with a particular social object. ## Claims ### Claim 1 A system, comprising: one or more memory units; and one or more processors operable to: determine a plurality of social interactions associated with a plurality of people, each social interaction comprising a particular person interacting with a particular social object of a plurality of social objects; generate a social object matrix using the determined social interactions; generate a social brain by performing Singular Value Decomposition (SVD) on the social object matrix, the social brain comprising a singular value representation of the social object matrix; determine text from the social objects of the determined social interactions; generate a term-document matrix (TDM) using the determined text; generate a semantic brain by performing SVD on the TDM, the semantic brain comprising a singular value representation of the TDM; generate an index using the determined text; and perform a query using the social brain, the semantic brain, and the index. ### Claim 2 (depends on 1) The system of claim 1, wherein determining text from the social objects of the determined social interactions comprises: capturing text from the plurality of social objects that are textual social objects; and determining proxies for the plurality of social objects that are non-textual social objects and capturing text from the determined proxies. ### Claim 3 (depends on 1) The system of claim 1, wherein performing the query using the social brain, the semantic brain, and the index comprises: determining, using the semantic brain and the index, one or documents in the social brain that are semantically related to a query document; creating a pseudo-document using the determined one or more semantically related documents; and determining one or more social recommendations using the social brain and the created pseudo-document. ### Claim 4 (depends on 1) The system of claim 1, wherein the one or more processors are further operable to group the determined social interactions into the plurality of groups according to the plurality of people or the plurality of social objects. ### Claim 5 (depends on 1) The system of claim 1, wherein generating the social object matrix comprises: determining a number of occurrences of each social object for each of the plurality of people; determining a number of occurrences of each social object across all of the plurality of people; determining a subset of the plurality of social objects; determining a weighting for each social object of the subset of social objects, the weighting based at least in part on a distribution of the social objects across all of the plurality of people; and creating the plurality of vectors based on the determined number of occurrences of each social object for each of the plurality of people and the determined weighting for each social object. ### Claim 6 (depends on 1) The system of claim 1, wherein the social object matrix comprises a person-by-social object matrix. ### Claim 7 (depends on 1) The system of claim 1, wherein the social object matrix comprises a social object-by-person matrix. ### Claim 8 A computer-implemented method, comprising: determining, by one or more computing systems, a plurality of social interactions associated with a plurality of people, each social interaction comprising a particular person interacting with a particular social object of a plurality of social objects; generating, by the one or more computing systems, a social object matrix using the determined social interactions; generating, by the one or more computing systems, a social brain by performing Singular Value Decomposition (SVD) on the social object matrix, the social brain comprising a singular value representation of the social object matrix; determining, by the one or more computing systems, text from the social objects of the determined social interactions; generating, by the one or more computing systems, a term-document matrix (TDM) using the determined text; generating, by the one or more computing systems, a semantic brain by performing SVD on the TDM, the semantic brain comprising a singular value representation of the TDM; generating, by the one or more computing systems, an index using the determined text; and performing, by the one or more computing systems, a query using the social brain, the semantic brain, and the index. ### Claim 9 (depends on 8) The computer-implemented method of claim 8, wherein determining text from the social objects of the determined social interactions comprises: capturing text from the plurality of social objects that are textual social objects; and determining proxies for the plurality of social objects that are non-textual social objects and capturing text from the determined proxies. ### Claim 10 (depends on 8) The computer-implemented method of claim 8, wherein performing the query using the social brain, the semantic brain, and the index comprises: determining, using the semantic brain and the index, one or documents in the social brain that are semantically related to a query document; creating a pseudo-document using the determined one or more semantically related documents; and determining one or more social recommendations using the social brain and the created pseudo-document. ### Claim 11 (depends on 8) The computer-implemented method of claim 8, further comprising grouping, by the one or more computing systems, the determined social interactions into the plurality of groups according to the plurality of people or the plurality of social objects. ### Claim 12 (depends on 8) The computer-implemented method of claim 8, wherein generating the social object matrix comprises: determining a number of occurrences of each social object for each of the plurality of people; determining a number of occurrences of each social object across all of the plurality of people; determining a subset of the plurality of social objects; determining a weighting for each social object of the subset of social objects, the weighting based at least in part on a distribution of the social objects across all of the plurality of people; and creating the plurality of vectors based on the determined number of occurrences of each social object for each of the plurality of people and the determined weighting for each social object. ### Claim 13 (depends on 8) The computer-implemented method of claim 8, wherein the social object matrix comprises a person-by-social object matrix. ### Claim 14 (depends on 8) The computer-implemented method of claim 8, wherein the social object matrix comprises a social object-by-person matrix. ### Claim 15 A non-transitory computer-readable medium comprising software, the software when executed by one or more processors operable to perform operations comprising: determining a plurality of social interactions associated with a plurality of people, each social interaction comprising a particular person interacting with a particular social object of a plurality of social objects; generating a social object matrix using the determined social interactions; generating a social brain by performing Singular Value Decomposition (SVD) on the social object matrix, the social brain comprising a singular value representation of the social object matrix; determining text from the social objects of the determined social interactions; generating a term-document matrix (TDM) using the determined text; generating a semantic brain by performing SVD on the TDM, the semantic brain comprising a singular value representation of the TDM; generating an index using the determined text; and performing a query using the social brain, the semantic brain, and the index. ### Claim 16 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein determining text from the social objects of the determined social interactions comprises: capturing text from the plurality of social objects that are textual social objects; and determining proxies for the plurality of social objects that are non-textual social objects and capturing text from the determined proxies. ### Claim 17 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein performing the query using the social brain, the semantic brain, and the index comprises: determining, using the semantic brain and the index, one or documents in the social brain that are semantically related to a query document; creating a pseudo-document using the determined one or more semantically related documents; and determining one or more social recommendations using the social brain and the created pseudo-document. ### Claim 18 (depends on 15) The non-transitory computer-readable medium of claim 15, the operations further comprising grouping the determined social interactions into the plurality of groups according to the plurality of people or the plurality of social objects. ### Claim 19 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein generating the social object matrix comprises: determining a number of occurrences of each social object for each of the plurality of people; determining a number of occurrences of each social object across all of the plurality of people; determining a subset of the plurality of social objects; determining a weighting for each social object of the subset of social objects, the weighting based at least in part on a distribution of the social objects across all of the plurality of people; and creating the plurality of vectors based on the determined number of occurrences of each social object for each of the plurality of people and the determined weighting for each social object. ### Claim 20 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein the social object matrix comprises a person-by-social object matrix or a social object-by-person matrix.