Research on semantic label extraction of domain entity relation based on CRF and rules

Authors:
Jianyi Guo;Jun Zhao;Zhengtao Yu;Lei Su;Nianshu Jiang
Affiliations:
The School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China and The Institute of Intelligent Information Processing, Computer Technology Appl ...;The School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China;The School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China and The Institute of Intelligent Information Processing, Computer Technology Appl ...;The School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China and The Institute of Intelligent Information Processing, Computer Technology Appl ...;The School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
Venue:
APWeb'12 Proceedings of the 14th international conference on Web Technologies and Applications
Year:
2012

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Abstract

For the vast amounts of data on the Web, this paper presents an extraction method of semantic label of entity relation in the tourism domain based on the conditional random fields and rules. In this method, firstly making use of the ideas of classification in named entity recognition, semantic items reflecting entity relations are seen as semantic labels in the contextual information to be labeled, and identify the semantic label with CRF, then respectively according to the relative location information of the two entities and semantic label and rules, the semantic labels are assigned to the associated entities. The experimental results on the corpus in the field of tourism show that this method can reach the F-measure of 73.68%, indicating that the method is feasible and effective for semantic label extraction of entity relation.