A hybrid classifier approach for Web retrieved documents classification
Document Type
Conference Proceeding
Publication Date
7-7-2004
Abstract
The paper presents a hybrid technique for the classification of web returned hits into concept hierarchies. The technique involves a combination of manual and automatic classifiers. At first, all web returned documents are assigned to human defined categories using manual classifiers, and then automatic classifiers are used to generate a concept hierarchy for each of these categories. The results of the evaluation reveal the following: (a) for polysemous queries, our system is able to generate meaningful categories corresponding to (but not limited to), the different semantic facets of the queries; (b) as expected, for non-polysemous queries the system generates fewer categories; (c) the hierarchy precision of the concept hierarchies generated for polysemous queries is found to be significantly better when compared to the one obtained using a baseline system.
Identifier
3042601662 (Scopus)
ISBN
[0769521088, 9780769521084]
Publication Title
International Conference on Information Technology Coding Computing ITCC
External Full Text Location
https://doi.org/10.1109/ITCC.2004.1286474
First Page
326
Last Page
330
Volume
1
Recommended Citation
Bot, Razvan Stefan; Wu, Yi Fang Brook; Chen, Xin; and Li, Quanzhi, "A hybrid classifier approach for Web retrieved documents classification" (2004). Faculty Publications. 20293.
https://digitalcommons.njit.edu/fac_pubs/20293
