{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11494253","patent":{"patent_number":"US-11494253","title":"Data record anomaly reconciliation using machine learning models","assignee":null,"inventors":[],"filing_date":"2019-09-30T00:00:00.000Z","publication_date":"2022-11-08T00:00:00.000Z","cpc_codes":["G06F","G06F","G06F","G06F","G06F","G06N","G06Q"],"num_claims":20,"abstract":"Techniques are provided for data record anomaly reconciliation using machine learning models. One method comprises obtaining a data record comprising multiple line items; assigning the line items to a given cluster of similar line items to determine a line item neighborhood score for each line item based on a comparison of a given line item to other available line items in the assigned cluster; applying features of the data record to a machine learning model to determine a data record score for the data record based on a combination of the line item neighborhood scores for the data record; identifying anomalies in the data record based on the data record score and/or the line item neighborhood scores for the data record; and adjusting parameters of the line items to address the anomalies identified in the data record to produce a reconciled data record, based on the line item neighborhood scores and/or predefined adjustment rules."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Data record anomaly reconciliation using machine learning models","description":"Techniques are provided for data record anomaly reconciliation using machine learning models. One method comprises obtaining a data record comprising multiple line items; assigning the line items to a","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11494253","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11494253","citation_suggestion":"Patentable. \"Data record anomaly reconciliation using machine learning models\" (US-11494253). https://patentable.app/patents/US-11494253","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11494253","json":"https://patentable.app/api/llm-context/US-11494253","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T08:34:55.579Z"}