{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11983747","patent":{"patent_number":"US-11983747","title":"Using machine learning to identify hidden software issues","assignee":null,"inventors":[],"filing_date":"2023-03-31T00:00:00.000Z","publication_date":"2024-05-14T00:00:00.000Z","cpc_codes":["G06Q","G06F","G06N","G06F","G06N","G06N","G06N","G06N","G06N"],"num_claims":20,"abstract":"A method including preprocessing natural language text by cleaning and vectorizing the natural language text. A first machine learning model (MLM) extracts negative reviews. A first input to the first MLM is the natural language text and a first output of the first MLM is first probabilities that the negative reviews have negative sentiments. The method also includes categorizing the negative reviews by executing a second MLM. A second input to the second MLM is the negative reviews. A second output of the second MLM is second probabilities that the negative reviews are assigned to categories. The method also includes identifying, using a name recognition controller and based on categorizing, a name of a software application in the negative reviews and sorting the negative reviews into a subset of negative reviews relating to the name. The software application is adjusted based on the subset of negative reviews."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Using machine learning to identify hidden software issues","description":"A method including preprocessing natural language text by cleaning and vectorizing the natural language text. A first machine learning model (MLM) extracts negative reviews. A first input to the first","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11983747","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-11983747","citation_suggestion":"Patentable. \"Using machine learning to identify hidden software issues\" (US-11983747). https://patentable.app/patents/US-11983747","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11983747","json":"https://patentable.app/api/llm-context/US-11983747","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T16:57:37.933Z"}