# US 11,308,165 B2 · Methods and systems for merging point-of-interest datasets > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,308,165 B2 - Document ID: US11308165B2 - Status: Granted - Kind: B2 - Application number: 16/396,166 - Filed: 2019-04-26 - Published: 2020-10-29 - Granted: 2022-04-19 - Earliest claimed: 2019-04-26 - Assignees: Verizon Patent and Licensing Inc. - Applicants: Verizon Patent and Licensing Inc. - Inventors: Wesley Boyer; Aleksei Maximillian Kac; Mark Romanak; Thomas M. Baker, Jr.; Jeremy McKay; Jared David Barnes; Rossi Guiliani - Web page: https://patentgrep.com/patent/US11308165B2 ## CPC - G06F 16/906: Clustering; Classification - G06F 16/29: Geographical information databases - G06F 16/687: using geographical or spatial information, e.g. location - G06F 16/75: Clustering; Classification - G06F 16/22: Indexing; Data structures therefor; Storage structures - G06F 16/2457: with adaptation to user needs - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract An exemplary point-of-interest merging system accesses point-of-interest data records. Each point-of-interest data record includes data representative of a distinct set of features for a distinct point-of-interest. The merging system generates, based on the distinct sets of features of the point-of-interest data records, a graph data structure that includes the point-of-interest data records and weighted feature relationships interconnecting the point-of-interest data records. The merging system clusters, based on the graph data structure, the point-of-interest data records into subset groups of point-of-interest data records. The merging system generates one or more merged point-of-interest data records based on the clustered subset groups of point-of-interest data records. ## Claims ### Claim 1 A method comprising: accessing, by a computing system, a plurality of point-of-interest datasets from different sources; batching, by the computing system and from the plurality of point-of-interest datasets from different sources, a plurality of point-of-interest data records together based on similarity between a feature included in distinct sets of features of the plurality of point-of-interest data records, each of the plurality of point-of-interest data records including data representative of a distinct set of features for a distinct point-of-interest; generating, by the computing system based on the distinct sets of features of the plurality of point-of-interest data records, a graph data structure that includes the plurality of point-of-interest data records and a plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records; clustering, by the computing system based on the graph data structure, the plurality of point-of-interest data records into groups of point-of-interest data records, each group of point-of-interest data records including a different subset of the plurality of point-of-interest data records; and generating, by the computing system, one or more merged point-of-interest data records based on the clustered groups of point-of-interest data records. ### Claim 2 (depends on 1) The method of claim 1, further comprising providing, by the computing system, the one or more merged point-of-interest data records to a computer-implemented mapping system for use by the computer-implemented mapping system to indicate one or more points-of-interest on a user interface map of a geographic area. ### Claim 3 (depends on 1) The method of claim 1, wherein the generating of the graph data structure comprises: comparing the distinct sets of features of the plurality of point-of-interest data records to one another; and generating the plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records based on the comparing. ### Claim 4 (depends on 1) The method of claim 1, wherein the clustering of the plurality of point-of-interest data records into the groups of point-of-interest data records comprises: determining, based on the plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records, strengths of relationships between the plurality of point-of-interest data records; and defining the groups of point-of-interest data records based on the strengths of relationships between the plurality of point-of-interest data records. ### Claim 5 (depends on 1) The method of claim 1, wherein the distinct set of features for a point-of-interest data record of the plurality of point-of-interest data records comprises at least two of: a point-of-interest name; a point-of-interest phone number; a point-of-interest website; a point-of-interest email address; a point-of-interest street address; and a point-of-interest category. ### Claim 6 (depends on 1) The method of claim 1, wherein the feature on which the batching is based comprises at least one of a point-of-interest name and a point-of-interest geographic location. ### Claim 7 (depends on 6) The method of claim 6, wherein the point-of-interest geographic location comprises at least one of a point-of-interest street address and a point-of-interest postal code. ### Claim 8 (depends on 1) The method of claim 1, wherein the generating of the graph data structure based on the plurality of point-of-interest data records comprises associating a tag with each weighted feature relationship of the plurality of weighted feature relationships, the tag indicating the feature based upon which the plurality of point-of-interest data records are batched. ### Claim 9 A system comprising: a memory storing instructions; a processor communicatively coupled to the memory and configured to execute the instructions to: access a plurality of point-of-interest datasets from different sources; batch, from the plurality of point-of-interest datasets from different sources, a plurality of point-of-interest data records together based on similarity between a feature included in distinct sets of features of the plurality of point-of-interest data records, each of the plurality of point-of-interest data records including data representative of a distinct set of features for a distinct point-of-interest; generate, based on the distinct sets of features of the plurality of point-of-interest data records, a graph data structure that includes the plurality of point-of-interest data records and a plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records; cluster, based on the graph data structure, the plurality of point-of-interest data records into groups of point-of-interest data records, each group of point-of-interest data records including a different subset of the plurality of point-of-interest data records; and generate one or more merged point-of-interest data records based on the clustered groups of point-of-interest data records. ### Claim 10 (depends on 9) The system of claim 9, wherein the processor is further configured to execute the instructions to provide the one or more merged point-of-interest data records to a computer-implemented mapping system for use by the computer-implemented mapping system to indicate one or more points-of-interest on a user interface map of a geographic area. ### Claim 11 (depends on 9) The system of claim 9, wherein the generating of the graph data structure comprises: comparing the distinct sets of features of the plurality of point-of-interest data records to one another; and generating the plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records based on the comparing. ### Claim 12 (depends on 9) The system of claim 9, wherein the clustering of the plurality of point-of-interest data records into the groups of point-of-interest data records comprises: determining, based on the plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records, strengths of relationships between the plurality of point-of-interest data records; and defining the groups of point-of-interest data records based on the strengths of relationships between the plurality of point-of-interest data records. ### Claim 13 (depends on 9) The system of claim 9, wherein the generating of the graph data structure based on the plurality of point-of-interest data records comprises associating a tag with each weighted feature relationship of the plurality of weighted feature relationships, the tag indicating the feature based upon which the plurality of point-of-interest data records are batched. ### Claim 14 A non-transitory computer-readable medium storing instructions that, when executed, direct at least one processor of a computing device to: access a plurality of point-of-interest datasets from different sources; batch, from the plurality of point-of-interest datasets from different sources, a plurality of point-of-interest data records together based on similarity between a feature included in distinct sets of features of the plurality of point-of-interest data records, each of the plurality of point-of-interest data records including data representative of a distinct set of features for a distinct point-of-interest; generate, based on the distinct sets of features of the plurality of point-of-interest data records, a graph data structure that includes the plurality of point-of-interest data records and a plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records; cluster, based on the graph data structure, the plurality of point-of-interest data records into groups of point-of-interest data records, each group of point-of-interest data records including a different subset of the plurality of point-of-interest data records; and generate one or more merged point-of-interest data records based on the clustered groups of point-of-interest data records. ### Claim 15 (depends on 14) The computer-readable medium of claim 14, the computer-readable medium further storing instructions that, when executed, further direct the at least one processor of the computing device to provide the one or more merged point-of-interest data records to a computer-implemented mapping system for use by the computer-implemented mapping system to indicate one or more points-of-interest on a user interface map of a geographic area. ### Claim 16 (depends on 14) The computer-readable medium of claim 14, wherein the generating of the graph data structure comprises: comparing the distinct sets of features of the plurality of point-of-interest data records to one another; and generating the plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records based on the comparing. ### Claim 17 (depends on 14) The computer-readable medium of claim 14, wherein the clustering of the plurality of point-of-interest data records into the groups of point-of-interest data records comprises: determining, based on the plurality of weighted feature relationships interconnecting the plurality of point-of-interest data records, strengths of relationships between the plurality of point-of-interest data records; and defining the groups of point-of-interest data records based on the strengths of relationships between the plurality of point-of-interest data records. ### Claim 18 (depends on 1) The method of claim 1, further comprising providing, by the computer-implemented mapping system and based on the merged point-of-interest data records, the user interface map of the geographic area, the user interface map indicating the one or more points-of-interest at one or more locations within the geographic area. ### Claim 19 (depends on 1) The method of claim 1, wherein the one or more points-of-interest comprise one or more businesses. ### Claim 20 (depends on 1) The method of claim 1, wherein the one or more points-of-interest comprise one or more places of transit.