Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path Information

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 classific...

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Main Authors: Oh, Heung-Seon, Jung, Yuchul
Format: Article
Language:English
Published: Korea Institute of Science and Technology Information 2017-09-01
Series:Journal of Information Science Theory and Practice
Subjects:
Online Access:http://society.kisti.re.kr/sv/SV_svpsbs03V.do?method=download&cn1=JAKO201727038079760
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spelling doaj-e24681531e7b4fc4a99b7354180924902020-11-24T21:36:15ZengKorea Institute of Science and Technology InformationJournal of Information Science Theory and Practice2287-90992287-45772017-09-0153314710.1633/JISTaP.2017.5.3.322879099Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path InformationOh, Heung-Seon0Jung, Yuchul1Korea Institute of Science and Technology InformationKumoh National Institute of Technology (KIT)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.http://society.kisti.re.kr/sv/SV_svpsbs03V.do?method=download&cn1=JAKO201727038079760Hierarchical text classificationQuery expansionNarrow-down approach
collection DOAJ
language English
format Article
sources DOAJ
author Oh, Heung-Seon
Jung, Yuchul
spellingShingle Oh, Heung-Seon
Jung, Yuchul
Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path Information
Journal of Information Science Theory and Practice
Hierarchical text classification
Query expansion
Narrow-down approach
author_facet Oh, Heung-Seon
Jung, Yuchul
author_sort Oh, Heung-Seon
title Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path Information
title_short Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path Information
title_full Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path Information
title_fullStr Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path Information
title_full_unstemmed Enhancing the Narrow-down Approach to Large-scale Hierarchical Text Classification with Category Path Information
title_sort enhancing the narrow-down approach to large-scale hierarchical text classification with category path information
publisher Korea Institute of Science and Technology Information
series Journal of Information Science Theory and Practice
issn 2287-9099
2287-4577
publishDate 2017-09-01
description 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.
topic Hierarchical text classification
Query expansion
Narrow-down approach
url http://society.kisti.re.kr/sv/SV_svpsbs03V.do?method=download&cn1=JAKO201727038079760
work_keys_str_mv AT ohheungseon enhancingthenarrowdownapproachtolargescalehierarchicaltextclassificationwithcategorypathinformation
AT jungyuchul enhancingthenarrowdownapproachtolargescalehierarchicaltextclassificationwithcategorypathinformation
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