Fuzzy Pseudo-Thesaurus Based Clustering of a Folkloristic Corpus

Automatic thesaurus extraction is essential for modern information retrieval. We develop a method for fuzzy pseudo-thesaurus based on word pair co-occurrence in documents. In this study it is presented, that considering the word frequency degree counted on the whole corpus makes the obtained pseudo-thesaurus usable. Such parameters were found with which most of the obtained pairs of words were validated to be related by human expert. Among the extracted pairs and groups of words the relationship is often looser than synonymy, but they identify the frequently repeated topics of the corpus. We suggest the use of groups of closely related words for the definition of different topics and based on this clustering of the documents were performed (Chakrabarty, et al. (1999))