Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic models of information retrieval based on measuring the divergence from randomness
ACM Transactions on Information Systems (TOIS)
Knowledge-Based Approaches to Query Expansion in Information Retrieval
AI '96 Proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
X-IOTA: an open XML framework for IR experimentation
AIRS'04 Proceedings of the 2004 international conference on Asian Information Retrieval Technology
Conceptual indexing based on document content representation
CoLIS'05 Proceedings of the 5th international conference on Context: conceptions of Library and Information Sciences
Analysis of word sense disambiguation-based information retrieval
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
| Hi-index | 0.00 |
To improve the precision of an information retrieval system in a specific domain we propose a new indexing scheme based on external knowledge resources such as thesauri or ontologies.We introduce the notion of domain dimension, which is a substructure of a knowledge resource, to formally represent the different aspects of a domain that appear in a document. Then, we identify dimensions in documents and queries using a conceptual indexing. The result of this indexing is a representation of each document along its semantic dimensions. We also propose a query processing based on multi-dimensional indexing. It is comprised of a dimensional filtering followed by a dimensional ranking. Experimental results on medical imaging documents (ImageCLEFmed-2005 collection) show that the dimensional filtering, using three dimensions, can improves the mean average precision by about 25%.