Experiments on incorporating syntactic processing of user queries into a document retrieval strategy
SIGIR '88 Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval
Lexical ambiguity and information retrieval
ACM Transactions on Information Systems (TOIS)
Using WordNet to disambiguate word senses for text retrieval
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Viewing morphology as an inference process
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Word sense disambiguation and information retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Word sense disambiguation using a second language monolingual corpus
Computational Linguistics
Word sense disambiguation for large text databases
Word sense disambiguation for large text databases
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
A stochastic parts program and noun phrase parser for unrestricted text
ANLC '88 Proceedings of the second conference on Applied natural language processing
A tool for investigating the synonymy relation in a sense disambiguated thesaurus
ANLC '88 Proceedings of the second conference on Applied natural language processing
Word-sense disambiguation using statistical models of Roget's categories trained on large corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Automatic Information Organization and Retrieval.
Automatic Information Organization and Retrieval.
A Machine Learning Approach to POS Tagging
Machine Learning
Information Retrieval
Use of a Weighted Topic Hierarchy for Document Classification
TSD '99 Proceedings of the Second International Workshop on Text, Speech and Dialogue
Semantic refinement and error correction in large terminological knowledge bases
Data & Knowledge Engineering
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
On the evaluation and comparison of taggers: the effect of noise in testing corpora
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Co-active intelligence for image retrieval
Proceedings of the 13th annual ACM international conference on Multimedia
Semantic indexing using WordNet senses
RANLPIR '00 Proceedings of the ACL-2000 workshop on Recent advances in natural language processing and information retrieval: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 11
Differentiating homonymy and polysemy in information retrieval
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Context representation using word sequences extracted from a news corpus
International Journal of Approximate Reasoning
On content-driven search-keyword suggesters for literature digital libraries
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries
Semantically driven snippet selection for supporting focused web searches
Data & Knowledge Engineering
An Approach to Web-Scale Named-Entity Disambiguation
MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
Robust and efficient page rank for word sense disambiguation
TextGraphs-5 Proceedings of the 2010 Workshop on Graph-based Methods for Natural Language Processing
A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques
Information Processing and Management: an International Journal
Word sense disambiguation for spam filtering
Electronic Commerce Research and Applications
Artificial Intelligence in Medicine
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This paper discusses research on distinguishing word meanings in the context of information retrieval systems. We conducted experiments with three sources of evidence for making these distinctions: morphology, part-of-speech, and phrases. We have focused on the distinction between homonymy and polysemy (unrelated vs. related meanings). Our results support the need to distinguish homonymy and polysemy. We found: 1) grouping morphological variants makes a significant improvement in retrieval performance, 2) that more than half of all words in a dictionary that differ in part-of-speech are related in meaning, and 3) that it is crucial to assign credit to the component words of a phrase. These experiments provide better understanding of word-based methods, and suggest where natural language processing can provide further improvements in retrieval performance.