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Automated Text Binary Classification Using Machine Learning Approach

Authors: Alberto Holts; Claudio Riquelme; Rodrigo Alfaro;

Automated Text Binary Classification Using Machine Learning Approach

Abstract

The increased number of documents in digital format available on the Web and its useful information for different purposes entail an essential need to organize them. However, this task must be automated in order to save costs and manpower. In the community research, the main approach to face this problem is based on the application of machine learning techniques. This article studies the main machine learning approaches to reach an automated text classification.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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