Szczegóły publikacji

Opis bibliograficzny

Text mining with hybrid biclustering algorithms / Patryk ORZECHOWSKI, Krzysztof BORYCZKO // W: Artificial intelligence and soft computing : 15th international conference, ICAISC 2016 : Zakopane, Poland, June 12–16, 2016 : proceedings, Pt. 2 / eds. Leszek Rutkowski, [et al.]. — Switzerland : Springer International Publishing, cop. 2016. — (Lecture Notes in Artificial Intelligence ; ISSN 0302-9743 ; 9693). — ISBN: 978-3-319-39383-4; e-ISBN: 978-3-319-39384-1. — S. 102–113. — Bibliogr. s. 111–113, Abstr. — Toż na Dysku Flash


Autorzy (2)


Dane bibliometryczne

ID BaDAP98335
Data dodania do BaDAP2016-06-21
DOI10.1007/978-3-319-39384-1_9
Rok publikacji2016
Typ publikacjimateriały konferencyjne (aut.)
Otwarty dostęptak
Konferencja15th International Conference on Artificial Intelligence and Soft Computing
Czasopismo/seriaLecture Notes in Computer Science

Abstract

Text data mining is the process of extracting valuable information from a dataset consisting of text documents. Popular clustering algorithms do not allow detection of the same words appearing in multiple documents. Instead, they discover general similarity of such documents. This article presents the application of a hybrid biclustering algorithm for text mining documents collected from Twitter and symbolic analysis of knowledge spreadsheets. The proposed method automatically reveals words appearing together in multiple texts. The proposed approach is compared to some of the most recognized clustering algorithms and shows the advantage of biclustering over clustering in text mining. Finally, the method is confronted with other biclustering methods in the task of classification. © Springer International Publishing Switzerland 2016.

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