Text Mining Algorithms

Authors

  • Adebola K. Ojo Department of Computer Science, University of Ibadan, Ibadan, Nigeria.

DOI:

https://doi.org/10.9734/bpi/mono/978-81-972870-5-3/CH9

Keywords:

Text Mining Algorithms, Latent Dirichlet Allocation, K-Means Clustering, Naïve Bayes Classifier, Support Vector Machines

Abstract

This unit emphasizes exploring various text mining algorithms that are used to extract valuable insights from a large corpus of text data. The algorithms discussed in this unit include Latent Dirichlet Allocation, K-Means Clustering, Genetic Algorithm, Naïve Bayes Classifier, Association Rules, K-Nearest Neighbor, Support Vector Machines, Neural Networks, Decision Trees and Generalized Linear Models. Additionally, this unit also covers some popular text mining classification algorithms and data mining algorithms, along with relevant examples to help you understand the practical applications of these algorithms.

Published

2024-08-02

How to Cite

Adebola K. Ojo. (2024). Text Mining Algorithms. Text Mining Techniques With Applications, Edition 1, 96–103. https://doi.org/10.9734/bpi/mono/978-81-972870-5-3/CH9