Relevance feedback and other query modification techniques
Information retrieval
Use of syntactic context to produce term association lists for text retrieval
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
The impact of query structure and query expansion on retrieval performance
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Improving automatic query expansion
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Searching the Web: the public and their queries
Journal of the American Society for Information Science and Technology
A framework for selective query expansion
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Query Expansion on a Corporate Intranet: Using LSI to Increase Precision in Explorative Search
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 4 - Volume 04
Analysis of the query logs of a web site search engine
Journal of the American Society for Information Science and Technology
Developing a semantic-enable information retrieval mechanism
Expert Systems with Applications: An International Journal
Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium
Natural language technology and query expansion: issues, state-of-the-art and perspectives
Journal of Intelligent Information Systems
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Query Expansion (QE) is one of the most important mechanisms in the information retrieval field. A typical short Internet query will go through a process of refinement to improve its retrieval power. Most of the existing QE techniques suffer from retrieval performance degradation due to imprecise choice of query's additive terms in the QE process. In this paper, we introduce a novel automated QE mechanism. The new expansion process is guided by the semantics relations between the original query and the expanding words, in the context of the utilized corpus. Experimental results of our ''controlled'' query expansion, using the Arabic TREC-10 data, show a significant enhancement of recall and precision over current existing mechanisms in the field.