DocumentCode :
480719
Title :
Growing Fields of Interest - Using an Expand and Reduce Strategy for Domain Model Extraction
Author :
Thomas, Christopher ; Mehra, Pankaj ; Brooks, Roger ; Sheth, Amit
Author_Institution :
HP Labs., Palo Alto, CA
Volume :
1
fYear :
2008
fDate :
9-12 Dec. 2008
Firstpage :
496
Lastpage :
502
Abstract :
Domain hierarchies are widely used as models underlying information retrieval tasks. Formal ontologies and taxonomies enrich such hierarchies further with properties and relationships but require manual effort; therefore they are costly to maintain, and often stale. Folksonomies and vocabularies lack rich category structure. 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.
Keywords :
data mining; information retrieval; ontologies (artificial intelligence); pattern classification; search engines; Doozer; Wikipedia; category relationships; domain model extraction; expert-designed ontologies; folksonomies; formal ontologies; information classification; information retrieval tasks; taxonomies; vocabularies; Bridges; Buildings; Data mining; Encyclopedias; Information retrieval; Intelligent agent; Ontologies; Taxonomy; Vocabulary; Wikipedia; Domain Model creation; Expand and Reduce; Taxonomy extraction; Wikipedia;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-0-7695-3496-1
Type :
conf
DOI :
10.1109/WIIAT.2008.358
Filename :
4740498
Link To Document :
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