ISBN-13: 9781420059403 / Angielski / Twarda / 2009 / 328 str.
Featuring contributions from leading researchers in the field, this book provides a detailed overview of text mining theory, applications, and visualization. The theory section discusses text mining, information retrieval, latent semantic analysis, pagerank, latent Dirichlet allocation, and probabilistic relational models. In the section on text mining applications, the book explores web-based information, system and safety issues, spam filtering, information extraction, link mining, question answering, determining trends, and news reports. The final section of the book covers text visualization and examines how text mining techniques can be used to map information through visualizing databases.
An extension of data mining, text mining involves the extraction of information and knowledge from unstructured text. This constantly evolving field is increasingly used by major corporations, such as Google, Yahoo, and Microsoft. Featuring contributions from leading researchers in the field, this book provides a detailed overview of text mining theory, applications, and visualization. The theory section discusses text mining, information retrieval, latent semantic analysis, pagerank, latent Dirichlet allocation, and probabilistic relational models. In the section on text mining applications, the book explores web-based information, system and safety issues, spam filtering, information extraction, link mining, question answering, determining trends, and news reports. The final section of the book covers text visualization and examines how text mining techniques can be used to map information through visualizing databases.