Advertisement
Published in:
2006 | OriginalPaper | Chapter
Clustering and Classification of Textual Documents Based on Fuzzy Quantitative Similarity Measure — a Practical Evaluation
Author : Piotr S. Szczepaniak
Published in: Advances in Web Intelligence and Data Mining
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.
].