Disambiguating prepositional phrase attachments by using on-line dictionary definitions
Computational Linguistics - Special issue of the lexicon
Word sense disambiguation using machine-readable dictionaries
SIGIR '89 Proceedings of the 12th annual international ACM SIGIR conference on Research and development in information retrieval
Progress in the application of natural language processing to information retrieval tasks
The Computer Journal - Special issue on information retrieval
Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
The structure of the merriam-webster pocket dictionary
The structure of the merriam-webster pocket dictionary
Building a large thesaurus for information retrieval
ANLC '88 Proceedings of the second conference on Applied natural language processing
A practical part-of-speech tagger
ANLC '92 Proceedings of the third conference on Applied natural language processing
Extracting semantic hierarchies from a large on-line dictionary
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Structural patterns vs. string patterns for extracting semantic information from dictionaries
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
NetSerf: using semantic knowledge to find Internet information archives
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
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Information retrieval systems can be made more effective by providing more expressive query languages for users to specify their information need. This paper argues that this can be achieved through the use of semantic relations as query primitives, and describes a new technique for extracting semantic relations from an online dictionary. In contrast to existing research, this technique involves the composition of basic semantic relations, a process akin to constrained spreading activation in semantic networks. The proposed technique is evaluated in the context of extracting semantic relations that are relevant for retrieval from a corpus of pictures.