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Engineering Knowledge Graph from Patent Database

التفاصيل البيبلوغرافية
العنوان: Engineering Knowledge Graph from Patent Database
المؤلفون: Jianxi Luo, L. Siddharth, Kristin L. Wood, Lucienne Blessing
بيانات النشر: arXiv, 2021.
سنة النشر: 2021
مصطلحات موضوعية: FOS: Computer and information sciences, Computer Science - Computation and Language, Database, Computer Science - Artificial Intelligence, Computer science, Aggregate (data warehouse), Inference, Databases (cs.DB), computer.software_genre, Computer Graphics and Computer-Aided Design, Industrial and Manufacturing Engineering, Semantic network, Computer Science - Information Retrieval, Computer Science Applications, Set (abstract data type), Artificial Intelligence (cs.AI), Computer Science - Databases, Knowledge graph, Scalability, Patent document, computer, Computation and Language (cs.CL), Software, Information Retrieval (cs.IR)
الوصف: We propose a large, scalable engineering knowledge graph, comprising sets of real-world engineering “facts” as < entity, relationship, entity > triples that are found in the patent database. We apply a set of rules based on the syntactic and lexical properties of claims in a patent document to extract facts. We aggregate these facts within each patent document and integrate the aggregated sets of facts across the patent database to obtain an engineering knowledge graph. Such a knowledge graph is expected to support inference, reasoning, and recalling in various engineering tasks. The knowledge graph has a greater size and coverage in comparison with the previously used knowledge graphs and semantic networks in the engineering literature.
DOI: 10.48550/arxiv.2106.06739
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::162e0f86fdbc4801ce73083717f18162
Rights: OPEN
رقم الانضمام: edsair.doi.dedup.....162e0f86fdbc4801ce73083717f18162
قاعدة البيانات: OpenAIRE
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