DocumentCode
2418840
Title
Association rules mining for name entity recognition
Author
Budi, Indra ; Bressan, Stéphane
Author_Institution
Comput. Sci. Fac., Indonesia Univ., Jakarta, Indonesia
fYear
2003
fDate
10-12 Dec. 2003
Firstpage
325
Lastpage
328
Abstract
We propose a new name entity class extraction method based on association rules. We evaluate and compare the performance of our method with the state of the art maximum entropy method. We show that our method consistently yields a higher precision at a competitive level of recall. This result makes our method particularly suitable for tasks whose requirements emphasize the quality rather than the quantity of results.
Keywords
XML; computational linguistics; data mining; digital libraries; information analysis; information retrieval; maximum entropy methods; pattern recognition; Indonesian digital library; XML; association rule mining; information retrieval; linguistic systems; maximum entropy method; name entity class extraction; name entity recognition; Association rules; Computer science; Costs; Data mining; Decision trees; Dictionaries; Entropy; Information retrieval; Text recognition; Thesauri;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Information Systems Engineering, 2003. WISE 2003. Proceedings of the Fourth International Conference on
Print_ISBN
0-7695-1999-7
Type
conf
DOI
10.1109/WISE.2003.1254504
Filename
1254504
Link To Document