DocumentCode :
2682106
Title :
A Novel Ontology-Based Approach of Chinese Person Name Disambiguation
Author :
Zhu, Xiaoting ; Lu, Zhao
Author_Institution :
Dept. of Comput. Sci. & Technol., East China Normal Univ., Shanghai, China
fYear :
2012
fDate :
22-24 Oct. 2012
Firstpage :
197
Lastpage :
200
Abstract :
It is very common that various people share same name or a person has various names, which causes person name ambiguities. Existing methods group documents containing person names into various clusters and each cluster refers to an individual, while which target individual a person name occurring in a document refers to is still a challenged problem. In this paper, we firstly construct a person ontology with lots of person instances. Then, an approach of Chinese person name disambiguation based on the person ontology is presented: (1) Extract relevant personal features of a person name contained in a Chinese document, and (2) An improved person ontology tree matching algorithm is suggested to calculate similarities between the individual the person name represents and one of person instances sharing same name, rank the similarities and the top one is returned. To verify the validity of the proposed approach, three experiments are conducted on real web documents. Experimental results show that the proposed approach not only can effectively distinguish Chinese person name, but also can determine an individual for the person name.
Keywords :
natural language processing; ontologies (artificial intelligence); text analysis; Chinese document; Chinese person name disambiguation; ontology-based approach; person instances; person name; person ontology; real Web document; Data mining; Educational institutions; Feature extraction; Internet; Ontologies; Social network services; Web pages; Ontology; Ontology matching; Person name disambiguation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantics, Knowledge and Grids (SKG), 2012 Eighth International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2561-5
Type :
conf
DOI :
10.1109/SKG.2012.8
Filename :
6391831
Link To Document :
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