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IIT at TREC-2002 Linear Combinations Based on Document Structure and
 

Summary: IIT at TREC-2002
Linear Combinations Based on Document Structure and
Varied Stemming for Arabic Retrieval
Information Retrieval Laboratory
Department of Computer Science
Illinois Institute of Technology
Chicago, IL 60616
Abdur Chowdhury, Mohammed Aljlayl, Eric Jensen, Steve Beitzel,
David Grossman, Ophir Frieder
{abdur, aljlayl, ej, steve, grossman, ophir}@ir.iit.edu
Abstract
For TREC 10 we participated in the Named Page Finding Task and the Cross-Lingual Task. In the web
track, we explored the use of linear combinations of term collections based on document structure. Our
goal was to examine the effects of different term collection statistics based on document structure in respect
to known item retrieval. We parsed documents into structural components and built specific term indexes
based on that document structure. Each of those indices have their own collection statistics for term
weighting based on the type of language used for that structure in the collection. For producing a single
ranked list, we examined a weighted linear combination approach to merging results. Our approach to
known item retrieval was equal or above the median 58% of the time and 71% above the mean score of
submitted runs. In the Arabic track we participated in Arabic Cross-language Information Retrieval

  

Source: Argamon, Shlomo - Department of Computer Science, Illinois Institute of Technology

 

Collections: Computer Technologies and Information Sciences