Improving Document Transformation Techniques with Collaborative Learned Term-Based Concepts
Identifieur interne : 001912 ( Main/Exploration ); précédent : 001911; suivant : 001913Improving Document Transformation Techniques with Collaborative Learned Term-Based Concepts
Auteurs : Stefan Klink [Allemagne]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2004.
Descripteurs français
- Pascal (Inist)
English descriptors
Abstract
Abstract: Document Transformation techniques have been studied for decades. In this paper, a new approach for a significant improvement is presented based on using a new query expansion method. In contrast to other methods, the regarded query is expanded by adding those terms that are most similar to the concept of individual query terms, rather than selecting terms that are similar to the complete query or that are directly similar to the query terms. Experiments have shown that Document Transformation techniques are significantly improved in the retrieval effectiveness when measuring the recall-precision.
Url:
DOI: 10.1007/978-3-540-24642-8_16
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">Abstract: Document Transformation techniques have been studied for decades. In this paper, a new approach for a significant improvement is presented based on using a new query expansion method. In contrast to other methods, the regarded query is expanded by adding those terms that are most similar to the concept of individual query terms, rather than selecting terms that are similar to the complete query or that are directly similar to the query terms. Experiments have shown that Document Transformation techniques are significantly improved in the retrieval effectiveness when measuring the recall-precision.</div>
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