4 Papers
9 Citations
Pu Li is an academic researcher from Zhengzhou University of Light Industry. The author has contributed to research in topics: Computer science & Similarity (geometry). The author has an hindex of 1, co-authored 1 publications.
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Papers
A fuzzy semantic representation and reasoning model for multiple associative predicates in knowledge graph
TL;DR: In this paper , a new semantic representation and reasoning model for multiple associative predicates by introducing fuzzy theory is presented, which can discover more implicit valid knowledge with fuzzy semantic and have a good consistency with the intuition of human judgments.
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Scholar Recommendation Based on High-Order Propagation of Knowledge Graphs
TL;DR: A scholar recommendation method based on the high-order propagation of knowledge graph (HoPKG) is proposed, which analyzes thehigh-order semantic information in the knowledge graph, and generates richer entity representations to obtain users’ potential interest by distinguishing the importance of different entities.
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Semantic Extension of Query for the Linked Data
TL;DR: In this paper, the authors present some new semantic properties for predicates in RDF triples and design a Semantic Matrix for Predicates (SMP), which is a well-defined framework for the notion of Semantically Extended Query Model for the Linked Data (SEQMLD).
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A comprehensive social matrix factorization for recommendations with prediction and feedback mechanisms by fusing trust relationships and social tags
TL;DR: A social recommendation method incorporating trust relationships and social tags is proposed, which obtains user similarity and item similarity through potential feature vectors of users and items, and continuously trains them to obtain accurate similarity relationships to improve recommendation performance.
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