Self–Organizing Map representation for clustering Wikipedia search results

Julian Szymański

doi:10.1007/978-3-642-20042-7_15

Self–Organizing Map representation for clustering Wikipedia search results

Abstract

The article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal Component Analysis. We introduce hierarchical organization of the categorized articles changing the granularity of SOM network. The categorization method has been used in implementation of the system that clusters results of keyword-based search in Polish Wikipedia.

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Julian Szymański dr hab. inż.

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Category:: Conference activity
Type:: materiały konferencyjne indeksowane w Web of Science
Title of issue:: INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2011, PT II strony 140 - 149
ISSN:: 0302-9743
Language:: English
Publication year:: 2011
Bibliographic description:: Szymański J..: Self–Organizing Map representation for clustering Wikipedia search results , W: INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2011, PT II, 2011, Springer-Verlag Berlin Heidelberg,.
DOI:: Digital Object Identifier (open in new tab) 10.1007/978-3-642-20042-7_15
Verified by:: Gdańsk University of Technology