Generating better concept hierarchies using automatic document classification

Razvan Stefan Bot, Yi Fang Brook Wu, Xin Chen, Quanzhi Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This paper presents a hybrid concept hierarchy development technique for web returned documents retrieved by a meta-search engine. The aim of the technique is to separate the initial retrieved documents into topical oriented categories, prior to the actual concept hierarchy generation. The topical categories correspond to different semantic aspects of the query. This is done using a 1-of-n automatic document classification, on the initial set of returned documents. Then, an individual topical concept hierarchy is automatically generated inside each of the resulted categories. Both steps are executed on the fly at retrieval time. Due to the efficiency constraints imposed by the web retrieval context, the algorithm only uses document snippets (rather than full web pages) for both document classification and concept hierarchy generation. Experimental results show that the algorithm is able to improve the quality of the concept hierarchy presented to the searcher; at the same time, the efficiency parameters are kept within reasonable intervals.

Original languageEnglish (US)
Title of host publicationCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
Pages281-282
Number of pages2
DOIs
StatePublished - Dec 1 2005
EventCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management - Bremen, Germany
Duration: Oct 31 2005Nov 5 2005

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

OtherCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
CountryGermany
CityBremen
Period10/31/0511/5/05

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

Keywords

  • Automatic classification
  • Concept hierarchy
  • Document classification
  • Information retrieval
  • Manual classification

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