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Title
Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path Information
Author(s)
Heung-Seon OhYuchul Jung
Publication Year
2017-09-30
Abstract
The narrow-down approach, separately composed of search and classification stages, is an effective way of dealing with large-scale hierarchical text classification. Recent approaches introduce methods of incorporating global, local, and path information extracted from web taxonomies in the classification stage. Meanwhile, in the case of utilizing path information, there have been few efforts to address existing limitations and develop more sophisticated methods. In this paper, we propose an expansion method to effectively exploit category path information based on the observation that the existing method is exposed to a term mismatch problem and low discrimination power due to insufficient path information. The key idea of our method is to utilize relevant information not presented on category paths by adding more useful words. We evaluate the effectiveness of our method on state-of-the art narrow-down methods and report the results with in-depth analysis.
Keyword
Hierarchical text classification; Query expansion; Narrow-down approach
Journal Title
Journal of Information Science Theory and Practice
Citation Volume
5
ISSN
2287-4577
DOI
10.1633/JISTaP.2017.5.3.3
Files in This Item:
Thumbnail E1JSCH_2017_v5n3_31.pdf812.41 kBDownload
Appears in Collections:
8. KISTI 간행물 > JISTaP > Vol. 5 - No. 3
Type
Article
URI
https://repository.kisti.re.kr/handle/10580/8688
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