Abstract: The disclosure provides an efficient dataset search and/or deduplication that improve the speed and efficiency of dataset record search and/or deduplication over traditional methods. Certain implementations apply field-level deletion neighborhood processing to ordered field permutations of dataset records encoded with hash values. A method includes determining a field-level deletion neighborhood for two or more field combinations of the record by determining field hash values, creating field permutations, determining combined record hash values for each permutation; and associating each record hash value to the unique entity identifier. The method includes searching other entity representation records for matching combined record hash values, and assigning one or more of a unique entity identifier and a duplicate entity identifier to the other entity representation records having the matching combined record hash values.

Abstract: The disclosure provides an efficient dataset search and/or deduplication that improve the speed and efficiency of dataset record search and/or deduplication over traditional methods. Certain implementations apply field-level deletion neighborhood processing to ordered field permutations of dataset records encoded with hash values. A method includes determining a field-level deletion neighborhood for two or more field combinations of the record by determining field hash values, creating field permutations, determining combined record hash values for each permutation; and associating each record hash value to the unique entity identifier. The method includes searching other entity representation records for matching combined record hash values, and assigning one or more of a unique entity identifier and a duplicate entity identifier to the other entity representation records having the matching combined record hash values.

Abstract: The disclosure provides an efficient dataset search and/or deduplication that improve the speed and efficiency of dataset record search and/or deduplication over traditional methods. Certain implementations apply field-level deletion neighborhood processing to ordered field permutations of dataset records encoded with hash values. A method includes determining a field-level deletion neighborhood for two or more field combinations of the record by determining field hash values, creating field permutations, determining combined record hash values for each permutation; and associating each record hash value to the unique entity identifier. The method includes searching other entity representation records for matching combined record hash values, and assigning one or more of a unique entity identifier and a duplicate entity identifier to the other entity representation records having the matching combined record hash values.

Abstract: The disclosure provides an efficient dataset search and/or deduplication that improve the speed and efficiency of dataset record search and/or deduplication over traditional methods. Certain implementations apply field-level deletion neighborhood processing to ordered field permutations of dataset records encoded with hash values. A method includes determining a field-level deletion neighborhood for two or more field combinations of the record by determining field hash values, creating field permutations, determining combined record hash values for each permutation; and associating each record hash value to the unique entity identifier. The method includes searching other entity representation records for matching combined record hash values, and assigning one or more of a unique entity identifier and a duplicate entity identifier to the other entity representation records having the matching combined record hash values.

Abstract: There is provided a method that includes (a) sending to a geocoding service, an indicator of a location, where the geocoding service returns a bounding box that defines a geographic area, (b) sending to a search engine, a first query that includes the bounding box and a first parameter, where the search engine returns an identifier of a first business entity located within the geographic area and an indicator of an industry in which the first business entity is engaged, and (c) sending to the search engine, a second query that includes the bounding box and the indicator of the industry in which the first business entity is engaged, where the search engine returns coordinates of a second business entity located within the geographic area.

Abstract: There is provided a method that includes (a) receiving image data, (b) processing the image data to yield first data, (c) obtaining second data from a repository, based on the first data, and (d) storing the first data and the second data as a record in a database. There is also provided a method that includes (a) receiving image data, (b) processing the image data to yield first data and second data, (c) matching the first data to a record that is stored in a database, and (d) updating the record to include the second data. There is also provided a system that performs the methods, and a storage medium that contains instructions that control a processor to perform the methods.

Abstract: There is provided a method that includes (a) sending to a geocoding service, an indicator of a location, where the geocoding service returns a bounding box that defines a geographic area, (b) sending to a search engine, a first query that includes the bounding box and a first parameter, where the search engine returns an identifier of a first business entity located within the geographic area and an indicator of an industry in which the first business entity is engaged, and (c) sending to the search engine, a second query that includes the bounding box and the indicator of the industry in which the first business entity is engaged, where the search engine returns coordinates of a second business entity located within the geographic area.