Morgan Stanley‘s patent involves a method for classifying RDF triples using a domain-specific knowledge base. By identifying topics through computational cluster graphs and scoring algorithms, concepts are stored with unique URIs for classification. This innovative approach enhances semantic understanding and organization of information. GlobalData’s report on Morgan Stanley 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 Morgan Stanley, Retail trading platforms was a key innovation area identified from patents. Morgan Stanley's grant share as of February 2024 was 92%. Grant share is based on the ratio of number of grants to total number of patents.
Method for classifying rdf triples using domain-specific knowledge base
A recently granted patent (Publication Number: US11922327B2) discloses a method and computer system for classifying Resource Description Framework (RDF) triples. The method involves identifying topics in a domain-specific knowledge base (KB) by constructing computational cluster graphs around concepts in the KB and computing scores for these graphs. The topics are then classified based on the domain-specific KB stored in the memory of a knowledge base computer system. The method further includes validating identified topic candidates and discovering relations between concepts using a deep learning algorithm. Additionally, the system can generate the domain-specific KB from an ontology and extract semantic triples from domain-specific electronic documents.
The computer system described in the patent comprises a knowledge base computer system and a remote computer system in communication via a data network. The knowledge base system is equipped with a processor core and memory storing software to extract semantic triples, identify topics in the domain-specific KB, and classify RDF triples based on the KB. The system utilizes computational cluster graphs to identify topic candidates and validate them based on specific conditions. Furthermore, the system can generate the domain-specific KB from an ontology and extract semantic triples from electronic documents. Overall, the patented method and system provide a comprehensive approach to classifying RDF triples based on a domain-specific KB, enhancing knowledge organization and retrieval in a structured manner.
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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.
