DocumentCode
3231598
Title
A Lazy Approach for Category Model Construction Using Training Texts
Author
Tan, Saravadee Sae ; Hoon, Gan Keng ; Kong, Tang Enya
Author_Institution
Comput. Aided Translation Unit, Univ. Sains Malaysia
fYear
2006
fDate
18-22 Dec. 2006
Firstpage
1005
Lastpage
1011
Abstract
Categories are used to organize information and knowledge in directory system, folder etc. As the amount of information increase and the types of information diversify, it is common to have more categories created. As the number of categories increases, it becomes more difficult to organize, manage and look up information from existing categories. In this paper, categories are annotated with concept features to facilitate the access, retrieval and sharing of information in the categories. We have observed that training texts is crucial in learning the concept of a category and serves as a good measure to help human to construct the category model. Hence, we present a study on training texts selection and evaluate the effectiveness of training texts, as well as its capability to complement human´s knowledge in constructing the category model. Experimental evaluation shows that using training texts approach in category model construction gives promising results in both effectiveness and complement measures
Keywords
classification; information retrieval; learning (artificial intelligence); text analysis; category model construction; classification; information access; information retrieval; information sharing; training text selection; Anthropometry; Bonding; Buildings; Design methodology; Gallium nitride; Humans; Information retrieval; Management training; Ontologies;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence, 2006. WI 2006. IEEE/WIC/ACM International Conference on
Conference_Location
Hong Kong
Print_ISBN
0-7695-2747-7
Type
conf
DOI
10.1109/WI.2006.17
Filename
4061512
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