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
Link To Document :
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