# US 2020/0401633 A1 · Automatic false positive estimation for website matching > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401633 A1 - Document ID: US20200401633A1 - Status: Published application - Kind: A1 - Application number: 16/444,444 - Filed: 2019-06-18 - Published: 2020-12-24 - Earliest claimed: 2019-06-18 - Assignees: Paypal, Inc. - Applicants: PayPal, Inc. - Inventors: Avishay Meron; Tomer Handelman; Shay Elbaz; Shuly Lev-Yehudi - Web page: https://patentgrep.com/patent/US20200401633A1 ## CPC - G06F 16/951: Indexing; Web crawling techniques - G06F 16/958: Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking - G06N 7/02: using fuzzy logic (computing arrangements based on biological models G06N3/00; computing arrangements using knowledge-based models G06N5/00) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract A system and method for generating automatic false positive estimations for website matching is described. Several sets of assets and Uniform Resource Locators (URLs) are aggregated. Each of the several sets of assets is searched across webpage content corresponding to the several URLs to determine matches between the sets of assets and webpage content. One or more false positive estimations is determined, where each of the one or more false positive estimations corresponds to the one or more matches. A combined score is generated based on the one or more false positive estimations. ## Claims ### Claim 1 A system for performing an automatic false positive estimation for website matching comprising: a non-transitory memory storing instructions; and one or more hardware processors coupled to the non-transitory memory and configured to read the instructions from the non-transitory memory to cause the system to perform operations comprising: aggregating a plurality of sets of assets and a plurality of uniform resource locators (URLs); search each of the plurality of sets of assets across webpage content corresponding to the plurality of URLs determine one or more matches between the plurality of sets of assets and the webpage content; determine one or more false positive estimations, each of the one or more false positive estimations corresponding to the one or more matches; and generating a combined score based on the one or more false positive estimations. ### Claim 2 (depends on 1) The system of claim 1, wherein each set of the plurality of sets of assets and each of the plurality of URLs correspond to one of a plurality of unique customers. ### Claim 3 (depends on 2) The system of claim 2, wherein a URL is determined to be a match to one of the plurality of unique customers when the generated combined score exceeds a predetermined threshold. ### Claim 4 (depends on 3) The system of claim 3, wherein the operations further comprise crawling, in response to determining that the URL matches the one of the plurality of unique customers, webpages corresponding to the URL to extract information associated with the one of the plurality of unique customers. ### Claim 5 (depends on 1) The system of claim 1, wherein each set of the plurality of sets of assets comprises at least one of a name, a phone number, an address, and an email address. ### Claim 6 (depends on 1) The system of claim 1, wherein the one or more matches are determined in a fuzzy manner. ### Claim 7 (depends on 6) The system of claim 6, wherein a Levenshtein distance is used to determine the one or more matches in the fuzzy manner. ### Claim 8 A method for performing an automatic false positive estimation for website matching comprising: aggregating a plurality of sets of assets and a plurality of URLs; search each of the plurality of sets of assets across webpage content corresponding to the plurality of URLs determine one or more matches between the plurality of sets of assets and the webpage content; determine one or more false positive estimations, each of the one or more false positive estimations corresponding to the one or more matches; and generating a combined score based on the one or more false positive estimations. ### Claim 9 (depends on 8) The method of claim 8, wherein each set of the plurality of sets of assets and each of the plurality of URLs correspond to one of a plurality of unique customers. ### Claim 10 (depends on 9) The method of claim 9, wherein a URL is determined to be a match to one of the plurality of unique customers when the generated combined score exceeds a predetermined threshold. ### Claim 11 (depends on 10) The method of claim 10, further comprising crawling, in response to determining that the URL matches the one of the plurality of unique customers, webpages corresponding to the URL to extract information associated with the one of the plurality of unique customers. ### Claim 12 (depends on 8) The method of claim 8, wherein each set of the plurality of sets of assets comprises at least one of a name, a phone number, an address, and an email address. ### Claim 13 (depends on 8) The method of claim 8, wherein the one or more matches are determined in a fuzzy manner. ### Claim 14 (depends on 13) The method of claim 13, wherein a Levenshtein distance is used to determine the one or more matches in the fuzzy manner. ### Claim 15 A non-transitory machine-readable medium having stored thereon machine-readable instructions executable to cause performance of operations comprising: aggregating a plurality of sets of assets and a plurality of URLs; search each of the plurality of sets of assets across webpage content corresponding to the plurality of URLs determine one or more matches between the plurality of sets of assets and the webpage content; determine one or more false positive estimations, each of the one or more false positive estimations corresponding to the one or more matches; and generating a combined score based on the one or more false positive estimations. ### Claim 16 (depends on 15) The non-transitory machine-readable medium of claim 15, wherein each set of the plurality of sets of assets and each of the plurality of URLs correspond to one of a plurality of unique customers. ### Claim 17 (depends on 16) The non-transitory machine-readable medium of claim 16, wherein a URL is determined to be a match to one of the plurality of unique customers when the generated combined score exceeds a predetermined threshold. ### Claim 18 (depends on 17) The non-transitory machine-readable medium of claim 17, wherein the operations further comprise crawling, in response to determining that the URL matches the one of the plurality of unique customers, webpages corresponding to the URL to extract information associated with the one of the plurality of unique customers. ### Claim 19 (depends on 15) The non-transitory machine-readable medium of claim 15, wherein each set of the plurality of sets of assets comprises at least one of a name, a phone number, an address, and an email address. ### Claim 20 (depends on 15) The non-transitory machine-readable medium of claim 15, wherein the one or more matches are determined in a fuzzy manner, and wherein a Levenshtein distance is used to determine the one or more matches in the fuzzy manner.