Title :
Identifying Document Topics Using the Wikipedia Category Network
Author :
Schonhofen, Peter
Author_Institution :
Comput. & Autom. Res. Inst., Hungarian Acad. of Sci., Budapest
Abstract :
In the size and coverage of Wikipedia, a freely available online encyclopedia has reached the point where it can be utilized similar to an ontology or taxonomy to identify the topics discussed in a document. In this paper we show that even a simple algorithm that exploits only the titles and categories of Wikipedia articles can characterize documents by Wikipedia categories surprisingly well. We test the reliability of our method by predicting categories of Wikipedia articles themselves based on their bodies, and by performing classification and clustering on 20 newsgroups and RCV1, representing documents by their Wikipedia categories instead of their texts
Keywords :
Web sites; document handling; encyclopaedias; ontologies (artificial intelligence); pattern classification; pattern clustering; Wikipedia category network; document topics; newsgroups; online encyclopedia; ontology; Automation; Clustering algorithms; Computer networks; Content based retrieval; Encyclopedias; Information retrieval; Ontologies; Taxonomy; Testing; Wikipedia;
Conference_Titel :
Web Intelligence, 2006. WI 2006. IEEE/WIC/ACM International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2747-7