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Review of data, text and web mining software

Qingyu Zhang (Department of Computer and Information Technology, College of Business, Arkansas State University, Jonesboro, Arkansas, USA)
Richard S. Segall (Department of Computer and Information Technology, College of Business, Arkansas State University, Jonesboro, Arkansas, USA)

Kybernetes

ISSN: 0368-492X

Article publication date: 4 May 2010

2929

Abstract

Purpose

The purpose of this paper is to review and compare selected software for data mining, text mining (TM), and web mining that are not available as free open‐source software.

Design/methodology/approach

Selected softwares are compared with their common and unique features. The software for data mining are SAS® Enterprise Miner™, Megaputer PolyAnalyst® 5.0, NeuralWare Predict®, and BioDiscovery GeneSight®. The software for TM are CompareSuite, SAS® Text Miner, TextAnalyst, VisualText, Megaputer PolyAnalyst® 5.0, and WordStat. The software for web mining are Megaputer PolyAnalyst®, SPSS Clementine®, ClickTracks, and QL2.

Findings

This paper discusses and compares the existing features, characteristics, and algorithms of selected software for data mining, TM, and web mining, respectively. These softwares are also applied to available data sets.

Research limitations/implications

The limitations are the inclusion of selected software and datasets rather than considering the entire realm of these. This review could be used as a framework for comparing other data, text, and web mining software.

Practical implications

This paper can be helpful for an organization or individual when choosing proper software to meet their mining needs.

Originality/value

Each of the software selected for this research has its own unique characteristics, properties, and algorithms. No other paper compares these selected softwares both visually and descriptively for all the three types of data, text, and web mining.

Keywords

Citation

Zhang, Q. and Segall, R.S. (2010), "Review of data, text and web mining software", Kybernetes, Vol. 39 No. 4, pp. 625-655. https://doi.org/10.1108/03684921011036835

Publisher

:

Emerald Group Publishing Limited

Copyright © 2010, Emerald Group Publishing Limited

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