Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/212725
Title: RELATIONSHIP DISCOVERY FROM OPEN KNOWLEDGE GRAPHS AND ITS APPLICATIONS
Authors: YANG YUEJI
Keywords: knowledge graph,data mining,relationship discovery
Issue Date: 14-Jul-2021
Citation: YANG YUEJI (2021-07-14). RELATIONSHIP DISCOVERY FROM OPEN KNOWLEDGE GRAPHS AND ITS APPLICATIONS. ScholarBank@NUS Repository.
Abstract: Open Knowledge Graphs (KGs), such as Wikidata and Freebase, have become increasingly popular. They contain hundreds of millions of facts about real-world entities. This kind of rich information can aid many tasks such as question answering, fact-checking and recommendation. However, it is challenging to extract and use such information from those heterogeneous KGs with huge data volume. In this thesis, we propose novel approaches for efficient and effective relationship discovery from open KGs as well as innovative applications that are built upon the discovered relationships. More specifically, we have focused on three research problems. First, we study how to provide a simple and efficient relationship query engine. Second, we explore how to use relationship discovery to improve news search. Third, we investigate the problem of mining outstanding facts with a given context. Lastly, we have conducted extensive experiments on real-world KGs to validate the efficiency and effectiveness of our approaches.
URI: https://scholarbank.nus.edu.sg/handle/10635/212725
Appears in Collections:Ph.D Theses (Open)

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