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Weighting Query Terms Based on Distributional Statistics
RISE, Swedish ICT, SICS.ORCID iD: 0000-0003-4042-4919
RISE, Swedish ICT, SICS.
RISE, Swedish ICT, SICS.
Number of Authors: 3
2006 (English)In: Accessing Multilingual Information Repositories, 6th Workshop of the Cross-Language Evalution Forum, CLEF 2005, Vienna, Austria, 21-23 September, 2005: Revised Papers, 2006, 1, , 5 p.Conference paper, Published paper (Refereed)
Abstract [en]

This year, the SICS team has concentrated on query processing and on the internal topical structure of the query, specifically compound translation. Compound translation is non-trivial due to dependencies between compound elements. This year, we have investigated topical dependencies between query terms: if a query term happens to be non-topical or noise, it should be discarded or given a low weight when ranking retrieved documents; if a query term shows high topicality its weight should be boosted. The two experiments described here are based on the analysis of the distributional character of query terms: one using similarity of occurrence context between query terms globally across the entire collection; the other using the likelihood of individual terms to appear topically in individual texts. Both -- complementary -- boosting schemes tested delivered improved results.

Place, publisher, year, edition, pages
2006, 1. , 5 p.
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:ri:diva-21049OAI: oai:DiVA.org:ri-21049DiVA: diva2:1041083
Conference
6th Workshop of the Cross-Language Evalution Forum, CLEF 2005, Vienna, Austria, 21-23 September, 2005
Available from: 2016-10-31 Created: 2016-10-31 Last updated: 2016-12-29Bibliographically approved

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