Modern Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Noun-phrase co-occurrence statistics for semiautomatic semantic lexicon construction
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Monolingual and bilingual concept visualization from corpora
NAACL-Demonstrations '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Demonstrations - Volume 4
Semantic Vector Combinations and the Synoptic Gospels
QI '09 Proceedings of the 3rd International Symposium on Quantum Interaction
Enterprise people and skill discovery using tolerant retrieval and visualization
ECIR'07 Proceedings of the 29th European conference on IR research
LKR'08 Proceedings of the 3rd international conference on Large-scale knowledge resources: construction and application
Word space modeling for measuring semantic specificity in Chinese
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Corpus clouds - facilitating text analysis by means of visualizations
LTC'09 Proceedings of the 4th conference on Human language technology: challenges for computer science and linguistics
Automatically structuring domain knowledge from text: An overview of current research
Information Processing and Management: an International Journal
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Many ways of dealing with large collections of linguistic information involve the general principle of mapping words, larger terms and documents into some sort of abstract space. Considerable effort has been devoted to applying such techniques for practical tasks such as information retrieval and word-sense disambiguation. However, the inherent structure of these spaces is often less well-understood.Visualisation tools can help to uncover the relationships between meanings in this space, giving a clearer picture of the natural structure of linguistic information. We present a variety of tools for visualising word-meanings in vector spaces and graph models, derived from co-occurrence information and local syntactic analysis. Our techniques suggest new solutions to standard problems such as automatic management of lexical resources, which perform well under evaluation.The tools presented in this paper are all available for public use on our website.