Concept chaining utilizing meronyms in text characterization

Lori Watrous-DeVersterre, Chong Wang, Min Song

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

3 Scopus citations


For most, the web is the first source to answer a question formulated by curiosity, need, or research reasons. This phenomenon is due to the internet's ubiquitous access, ease of use, and the extensive and ever expanding content. The problem is no longer the need to acquire content to encourage use, but to provide organizational tools to support content categorization that will facilitate improved access methods. This paper presents the results of a new text characterization algorithm that combines semantic and linguistic techniques utilizing domain-based ontology background knowledge. It explores the combination of meronym, synonym, and hypernym linguistic relationships to create a set of concept chains used to represent concepts found in a document. The experiments show improved accuracy over bag-of-words based term weighting methods and reveal characteristics of the meronym contribution to document representation.

Original languageEnglish (US)
Title of host publicationJCDL '12 - Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries
Number of pages8
StatePublished - 2012
Event12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL '12 - Washington, DC, United States
Duration: Jun 10 2012Jun 14 2012

Publication series

NameProceedings of the ACM/IEEE Joint Conference on Digital Libraries
ISSN (Print)1552-5996


Other12th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL '12
Country/TerritoryUnited States
CityWashington, DC

All Science Journal Classification (ASJC) codes

  • General Engineering


  • clustering
  • concept extraction
  • digital libraries
  • machine learning
  • natural language processing
  • ontology
  • text characterization


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