Text Mining Algorithms | Chapter 8 | Text Mining Techniques with Applications, Edition 1

 

 

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.

 

Author(s) Details

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

 

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-81-972870-5-3/CH9

Text Analysis Extraction and Text Representation | Chapter 4 | Text Mining Techniques with Applications, Edition 1

 

We will discuss the categories of how texts are extracted and how to represent these unstructured text documents with appropriate format and structure to support later automated text mining algorithms.

 

Author(s) Details

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

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-81-972870-5-3/CH5