This work shows the use of WEKA, a tool that implements the most common machine learning algorithms, to perform a Text Mining analysis on a set of documents. Applying these methods requires initial steps where the text is converted into a structured format. Both the processing phase and the analysis of the transformed dataset, using classification and clustering algorithms, can be carried out entirely with this tool, in a rigorous and simple way. The work describes the construction of two classification models starting from two different sets of documents. These models are not meant to be good or realistic, but just illustrate how WEKA can be used for a Text Mining analysis.

Text categorization with WEKA: A survey / D. Merlini, M. Rossini. - In: MACHINE LEARNING WITH APPLICATIONS. - ISSN 2666-8270. - ELETTRONICO. - 4:(2021), pp. 1-20. [10.1016/j.mlwa.2021.100033]

Text categorization with WEKA: A survey

D. Merlini
;
2021

Abstract

This work shows the use of WEKA, a tool that implements the most common machine learning algorithms, to perform a Text Mining analysis on a set of documents. Applying these methods requires initial steps where the text is converted into a structured format. Both the processing phase and the analysis of the transformed dataset, using classification and clustering algorithms, can be carried out entirely with this tool, in a rigorous and simple way. The work describes the construction of two classification models starting from two different sets of documents. These models are not meant to be good or realistic, but just illustrate how WEKA can be used for a Text Mining analysis.
2021
4
1
20
D. Merlini, M. Rossini
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1234958
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