UnitedHealth Group had 14 patents in big data during Q4 2023. The UnitedHealth Group Inc filed patents in Q4 2023 for methods and systems related to retrieving relevant items for user queries using machine learning models, predicting healthcare paths for patients based on eligibility and medical claims data, converting multilabel classification models into binary classification models, controlling and tracking access to secured data independently of the storing asset, and performing predictive data analysis using semi-structured input data. These inventions aim to improve search engine results, healthcare planning, data security, and data analysis processes. GlobalData’s report on UnitedHealth Group gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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UnitedHealth Group grant share with big data as a theme is 14% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Search analysis and retrieval via machine learning embeddings (Patent ID: US20230409614A1)
The patent filed by UnitedHealth Group Inc. describes a computer-implemented method for retrieving relevant items for user queries using a search engine machine learning model. The method involves generating query input embeddings, performing k-Nearest-Neighbor searches, and navigating a semantic graph to generate search results. The search engine machine learning model is trained by creating embeddings for search engine repository items and constructing a semantic graph based on similarity measures between these embeddings. Various embedding techniques are utilized, including syntactic, semantic, and geospatial embedding methods.
Additionally, the patent outlines the apparatus and computer program product for implementing the method, including components such as processors, memory, and program code. The apparatus is designed to receive query inputs, generate prediction-based actions using the search engine machine learning model, and train the model by assigning content category labels and creating embeddings for search engine repository items. The semantic graph is constructed based on similarity measures between pairs of item embeddings. The patent also covers the generation of user profiles and history embeddings, as well as the computation of user relevance scores for ranking search results based on semantic, syntactic, geospatial, and user relevance factors. Overall, the patent details a comprehensive approach to enhancing search engine capabilities through advanced machine learning techniques and semantic graph navigation.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
