Microsoft has patented a method for targeted searching based on user profiles. The system retrieves user embeddings, identifies document embeddings based on user interests, generates rankings, and recommends documents to users. The technology uses machine learning models to personalize search results. GlobalData’s report on Microsoft gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Microsoft, AI for workflow management was a key innovation area identified from patents. Microsoft's grant share as of February 2024 was 61%. Grant share is based on the ratio of number of grants to total number of patents.
Targeted search based on user interests using machine learning
A recently granted patent (Publication Number: US11921728B2) outlines a method and system for performing a targeted search based on user interests. The method involves receiving a user identifier, retrieving a user embedding generated using a machine learning model based on user characteristics, interests, and actions, identifying document embeddings within a certain distance of the user embedding, generating rankings for these document embeddings, and recommending at least one document to the user based on these rankings. The system includes a processor, memory with instructions for generating document embeddings, user embeddings, and rankings, and recommending documents to the user. It also allows for user interaction by receiving feedback on recommended documents and adjusting recommendations accordingly.
Furthermore, the system can extract information from documents, receive user characteristics and actions, and generate user embeddings in a low-dimensional space representation. It can also identify document embeddings based on user embeddings, generate rankings using machine learning models based on relevancy, novelty, and diversity, and recommend documents to users based on these rankings. The system is designed to enhance user experience by providing personalized recommendations tailored to individual interests and actions, ultimately improving the efficiency and effectiveness of targeted searches. The patent also includes a computer storage medium with instructions for performing the method, ensuring the scalability and accessibility of the system across different platforms and devices for a seamless user experience.
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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.
