Abstract
This paper focuses especially on two problems that are crucial for retrieval performance in information retrieval (IR) systems: the lack of information caused by document pre-processing and the difficulty caused by homonymous and synonymous words in natural language. Author argues that traditional IR methods, i. e. methods based on dealing with individual terms without considering their relations, can be overcome using natural language processing (NLP). In order to detect the relations among terms in sentences and 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.
This study has been supported by MŠMT (the FRVŠ grant no 1909).
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Holub, M. (2000). Use of Dependency Microcontexts in Information Retrieval. In: Hlaváč, V., Jeffery, K.G., Wiedermann, J. (eds) SOFSEM 2000: Theory and Practice of Informatics. SOFSEM 2000. Lecture Notes in Computer Science, vol 1963. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44411-4_23
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DOI: https://doi.org/10.1007/3-540-44411-4_23
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