Preprocessing Method And Similarity Measures In Clustering-based
Text Mining: A Preliminary Study
Author(s)
S. Iiritano, M. Ruffolo & P. Rullo
Abstract
Preprocessing method and similarity measures
in clustering-based text mining: a preliminary
study
S. 1iritano1t2, M. ~ u f f o l o l > ~ & P. ~ u l l o l l ~
Exeura s.i-.l.
2 ~ ~ ~ ~ - ~ i p a r t i m e n t o di Elettronica, lnformatica e Sistemistica
3 ~ ~ ~ ~ - ~ ~ ~ - - l s t i t u t o di CAlcolo e Reti ad alte prestazioni del Consiglio
Nazionale delle Ricerche
4 Dipartimento di Matematica
Universitd della Calabria, 87036 Rende (CS), Italy
Abstract
Knowledge Discovery in Text (KDT) has emerged as a challenging application due
to the large amount of textual documents available from heterogeneous sources. An
approach to knowledge discovery in text is based on clustering techniques in which
the quality of results strongly depends on features extracted from documents and
on similarity coefficients defined on them. In this work we present a framework
for textual document preprocessing useful for the extraction of relevant features
(i.e. lemma and word). Moreover, we define two similarity coeffi
Keywords
Related Book
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