Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Lexical ambiguity and information retrieval
ACM Transactions on Information Systems (TOIS)
Information storage and retrieval
Information storage and retrieval
Towards building contextual representations of word senses using statistical models
Corpus processing for lexical acquisition
Use of Dependency Microcontexts in Information Retrieval
SOFSEM '00 Proceedings of the 27th Conference on Current Trends in Theory and Practice of Informatics
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Disambiguating highly ambiguous words
Computational Linguistics - Special issue on word sense disambiguation
A statistical parser for Czech
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
HLT '93 Proceedings of the workshop on Human Language Technology
Use of Dependency Microcontexts in Information Retrieval
SOFSEM '00 Proceedings of the 27th Conference on Current Trends in Theory and Practice of Informatics
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In several recent years, natural language processing (NLP) has brought some very interesting and promising outcomes. In the field of information retrieval (IR), however, these significant advances have not been applied in an optimal way yet.Author argues that traditional IR methods, i.e. methods based on dealing with individual terms without considering their relations, can be overcome using NLP procedures. The reason for this expectation is the fact that NLP methods are able to detect the relations among terms in sentences and that the information obtained can be stored and used for searching. Features of word senses and the significance of word contexts are analysed and possibility of searching based on word senses instead of mere words is examined.The core part of the paper focuses on analysing Czech sentences and extracting the context relations among words from them. In order to make use of lemmatisation and morphological and syntactic tagging of Czech texts, author proposes a method for construction of dependency word microcontexts fully automatically extracted from texts, and several ways how to exploit the microcontexts for the sake of increasing retrieval performance.