Automated Document Classification

The development of information technology has increased the availability of electronic documents. Meanwhile machine learning techniques for automated text classification are being developed. These techniques can be applied to domains such as document organization, information retrieval, spam filtering, automated cataloging, word sense disambiguation, and automated survey coding. While achievements in text classification have been reported, it is rare to find a book that systematically unveils issues in this field. It is therefore in such context, this book presents methods and algorithms for automated document classification. It provides materials on conventional and current techniques. In addition, it discusses how someone can statistically make analysis to find out the significance of choosing a method or an algorithm. This book is appropriate for practitioners, researchers, professionals, senior university students or graduate students, and others who are interested in the fields such as Information Retrieval, Text Mining, Natural Language Processing, Library Science and Automation.

Autorentext

Lazaro S.P. Busagala received his PhD in Information Systems Engineering from Mie University. He is currently the Deputy Director of the Computer Centre of Sokoine University of Agriculture. He is the author of various scientific articles. Dr. Busagala is also a university academic librarian involved in teaching, research and consultancy.