Improving Question Answering over Knowledge Graphs using Graph Summarization

Improving Question Answering over Knowledge Graphs using Graph Summarization

Question Answering (QA) systems over Knowledge Graphs (KGs) (KGQA) automatically answer natural language questions using triples contained in a KG. The key idea is to represent questions and entities of a KG as low-dimensional embeddings. Previous KGQAs have attempted to represent entities using Kno...

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Bibliographic Details
Main Authors: Li, Sirui, Wong, Kok Wai, Fung, Chun Che, Zhu, Dengya
Format: Conference Paper
Published: Springer 2021
Online Access:https://link.springer.com/chapter/10.1007/978-3-030-92273-3_40
http://hdl.handle.net/20.500.11937/87131

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