Summary
Clustering enables more effective information retrieval. In practice, similar approaches are used for ranking and clustering. This paper presents a practical evaluation of a method for clustering of documents which is based on certain textual fuzzy similarity measure. The similarity measure was originally introduced in [12.] — cf. also [13.], and later used in internet-related applications [14., 15., 18.]. Two textual databases [21., 22.] of predefined clusters and of diverse level of freedom in the contents of documents were used for experiments that employed some variants of the basic clustering method [19.].
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Szczepaniak, P.S. (2006). Clustering and Classification of Textual Documents Based on Fuzzy Quantitative Similarity Measure — a Practical Evaluation. In: Last, M., Szczepaniak, P.S., Volkovich, Z., Kandel, A. (eds) Advances in Web Intelligence and Data Mining. Studies in Computational Intelligence, vol 23. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33880-2_31
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DOI: https://doi.org/10.1007/3-540-33880-2_31
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