Technique for eliminating irrelevant terms in term rewriting for annotated media retrieval

Y. Park, F. Golshani, Sethuraman Panchanathan, P. Kim

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

1 Scopus citations

Abstract

In this paper, we present an efficient term rewriting technique that computes a degree of term to domain relevance. The proposed method resolves the problems in ontology integrated concept search. Those problems are (i) Pre-defined concept classes in ontology are not relevant to users (no proper concept class for a target annotation has not found). (ii) Too many similar concept classes are provided to a user therefore, a user may fail to choose a correct semantic class for a target annotation (ordinary users are not an expert in concept classification). The method uses sense disambiguation task for finding relevant terms for a given domain. Sense disambiguation requires term-to-term similarity measurement and term frequency measurement. For fair modeling of not observed term frequencies, discounting and redistribution model is applied. The proposed method is a compliment to our previous work presented in [13][14]. Robustness of our method is demonstrated through human judgement test that shows our method allows prediction of precise term list (overall 75% of correct prediction) that are relevant to a given domain.

Original languageEnglish (US)
Title of host publicationProceedings of the ACM International Multimedia Conference and Exhibition
Pages582-584
Number of pages3
EditionIV
StatePublished - 2001
Externally publishedYes
Event-ACM Multimedia 2001 Workshops- 2001 Multimedia Conference - Ottawa, Ont., Canada
Duration: Sep 30 2001Oct 5 2001

Other

Other-ACM Multimedia 2001 Workshops- 2001 Multimedia Conference
CountryCanada
CityOttawa, Ont.
Period9/30/0110/5/01

Keywords

  • Concept retrieval
  • Semantic query processing

ASJC Scopus subject areas

  • Computer Science(all)

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