Concept-based visual information management with large lexical corpus

Youngchoon Park, Pankoo Kim, Forouzan Golshani, Sethuraman Panchanathan

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

2 Scopus citations

Abstract

Most users want to find visual information based on the semantics of visual contents such as a name of person, semantic relations, an action happening in a scene,…etc. However, techniques for content-based image or video retrieval are not mature enough to recognize visual semantic completely, whereas retrieval based on color, size, texture and shape are within the state of the art. Therefore, smart ways to manage textual annotations in visual information retrieval are necessary. In this paper, a framework for integration of textual and visual content searching mechanism is presented. The proposed framework includes ontology-based semantic query processing through efficient semantic similarity measurement. A new conceptual similarity distance measure between two conceptual entities in a large taxonomy structure is proposed and its efficiency is demonstrated. With the proposed method, an information retrieval system can benefit such as (1) reduction of the number of trial-and-errors to find correct keywords, (2) Improvement of precision rates by eliminating the semantic heterogeneity in description, and (3) Improvement of recall rates through precise modeling of concepts and their relations.

Original languageEnglish (US)
Title of host publicationDatabase and Expert Systems Applications - 12th International Conference, DEXA 2001, Proceedings
EditorsPavel Vogel, Gerald Quirchmayr, Heinrich C. Mayr, Jiri Lazansky
PublisherSpringer Verlag
Pages350-359
Number of pages10
ISBN (Print)3540425276, 9783540425274
StatePublished - Jan 1 2001
Event12th International Conference on Database and Expert Systems Applications, DEXA 2001 - Munich, Germany
Duration: Sep 3 2001Sep 5 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2113
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Database and Expert Systems Applications, DEXA 2001
CountryGermany
CityMunich
Period9/3/019/5/01

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Park, Y., Kim, P., Golshani, F., & Panchanathan, S. (2001). Concept-based visual information management with large lexical corpus. In P. Vogel, G. Quirchmayr, H. C. Mayr, & J. Lazansky (Eds.), Database and Expert Systems Applications - 12th International Conference, DEXA 2001, Proceedings (pp. 350-359). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2113). Springer Verlag.