Relations expansion: Extracting relationship instances from the web

Haibo Li, Yutaka Matsuo, Mitsuru Ishizuka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a Relation Expansion framework, which uses a few seed sentences marked up with two entities to expand a set of sentences containing target relations. During the expansion process, label propagation algorithm is used to select the most confident entity pairs and context patterns. The label propagation algorithm is a graph based semi-supervised learning method which models the entire data set as a weighted graph and the label score is propagated on this graph. We test the proposed framework with four relationships, the results show that the label propagation is quite competitive comparing with existing methods.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010
Pages184-187
Number of pages4
Volume1
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010 - Toronto, ON
Duration: 2010 Aug 312010 Sep 3

Other

Other2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010
CityToronto, ON
Period10/8/3110/9/3

Keywords

  • Relation extraction
  • Semi-supervised learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

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  • Cite this

    Li, H., Matsuo, Y., & Ishizuka, M. (2010). Relations expansion: Extracting relationship instances from the web. In Proceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010 (Vol. 1, pp. 184-187). [5616251] https://doi.org/10.1109/WI-IAT.2010.269