Text categorization with WEKA: A survey
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...
Main Authors: | Donatella Merlini, Martina Rossini |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2021-06-01
|
Series: | Machine Learning with Applications |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827021000141 |
Similar Items
-
Text Classification Algorithms: A Survey
by: Kamran Kowsari, et al.
Published: (2019-04-01) -
Using Statistical Properties to Enhance Text Categorization
by: Rached Zantout, et al.
Published: (2015-06-01) -
WekaPyScript: Classification, Regression, and Filter Schemes for WEKA Implemented in Python
by: Christopher Beckham, et al.
Published: (2016-08-01) -
The textcat Package for n -Gram Based Text Categorization in R
by: Kurt Hornik, et al.
Published: (2013-01-01) -
A Customizable Text Classifier for Text Mining
by: Yun-liang Zhang, et al.
Published: (2007-12-01)