Growing Fields of Interest: Using an Expand and Reduce Strategy for Domain Model Extraction

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Article

Abstract

Domain hierarchies are widely used as models underlying information retrieval tasks. Formal ontologies and taxonomies enrich such hierarchies further with properties and relationships associated with concepts and categories but require manual effort; therefore they are costly to maintain, and often stale. Folksonomies and vocabularies lack rich category structure and are almost entirely devoid of properties and relationships. Classification and extraction require the coverage of vocabularies and the alterability of folksonomies and can largely benefit from category relationships and other properties. With Doozer, a program for building conceptual models of information domains, we want to bridge the gap between the vocabularies and Folksonomies on the one side and the rich, expert-designed ontologies and taxonomies on the other. Doozer mines Wikipedia to produce tight domain hierarchies, starting with simple domain descriptions. It also adds relevancy scores for use in automated classification of information. The output model is described as a hierarchy of domain terms that can be used immediately for classifiers and IR systems or as a basis for manual or semi-automatic creation of formal ontologies.

APA Citation

Thomas, C., Mehra, P., Brooks, R., & Sheth, A. P. (2008). Growing Fields of Interest: Using an Expand and Reduce Strategy for Domain Model Extraction. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 496-502.
https://corescholar.libraries.wright.edu/knoesis/544

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