Title
Research on semantic label extraction of domain entity relation based on CRF and rules
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.
Year
DOI
Venue
2012
10.1007/978-3-642-29426-6_19
APWeb Workshops
Keywords
Field
DocType
tourism domain,entity relation,extraction method,semantic label,semantic item,domain entity relation,associated entity,entity recognition,semantic label extraction,contextual information,relative location information
Entity linking,Conditional random field,Semantic similarity,Data mining,Contextual information,Information retrieval,Computer science,Semantic equivalence,Named-entity recognition
Conference
Citations 
PageRank 
References 
0
0.34
9
Authors
5
Name
Order
Citations
PageRank
Jianyi Guo12010.99
Jun Zhao200.34
Zhengtao Yu346069.08
Lei Su400.34
Nianshu Jiang500.34