Following the success of the first edition of this book published two years ago, this New Edition, now in paperback format, has been updated and includes new data on the main market players (28 companies are described) to reflect the latest changes and developments within the text mining sector.Text Mining is an interdisciplinary field bringing together techniques from data mining, linguistics, information retrieval, and visualization to address the issue of quickly extracting information from large databases with different applicative objectives. This book is directed towards graduate students in business, and undergraduate students in computer science, and to practitioners in law enforcement, security, intelligence, marketing and IT departments; it assumes readers have little or no previous knowledge about mathematics or linguistics. It has been structured as a self-teaching guide and has been written as a result of the authors’ experiences in participating in several large-scale text mining projects. It can be used as a guide for system integrators, and designers of text mining systems, but especially for business analysts and consultants who wish to apply the powerful tools of this technology to real situations.CONTENTS:THEORETICAL OVERVIEW: Text Processing and Information Retrieval; Information Extraction; Text Clustering; Text Categorization; Summarization and Visualization; Application Integration; ROI in Text Mining Projects.APPLICATIONS: Open Sources Analysis for Corporate and Government Intelligence; A Critical Appraisal of Text Mining in an Intelligence Environment; How to Forecast Telecommunications Competitive Landscape; Competitive Intelligence for SMEs: An Application to the Italian Building Sector; Virtual Communities: Human Capital and other Personal Characteristics Extraction; Customer Feedbacks and Opinion Surveys Analysis in the Automotive industry; Email Management System; TV Channel Provider: Mining the User Feedback; Text Mining in Banking; Text Mining in Life Sciences; Information Search and Classification to Foster Innovation in SMEs; Media Industry: How to Improve Documentalists Efficiency; Link Analysisin Crime Pattern Detection; SOFTWARE AND SERVICES: Text Mining Resources. ABOUT THE EDITOR:Alessandro Zanasi is a security research advisor and professor at Bologna University, Italy. Before he served asCarabinieri officer in Rome Scientific Investigations Center; IBM executive in Italy, Paris and San Jose (USA); METAGroup analyst; cofounder of Temis SA.As an intelligence specialist, he has been advising governments and corporations in security, intelligence and detectiontechnologies for more than twenty years. Among the others: European Commission through his membership, since 2005,to ESRAB-European Security Research Advisory Board and, since 2007, to ESRIF-European Security Research andInnovation Forum. AMONG THE 28 AUTHORS:Milic (Microsoft, UK), Pazienza (Univ.Roma,IT), Tiberio (Univ.Modena,IT), Sebastiani (Univ.Padova,IT),Mladenic, Grobelnik (Stefan Institute, SL), Sullivan (Ballston, USA), Politi (Analyst, IT), de’ Rossi (Telecom Italia,IT), Grivel (CNRS, F), Wives, Loh (Univ.Rio Grande, BR), Lebeth (Dresdner Bank, D), Fluck, Gieger (FraunhoferInstitute, D), Peters (Gruner+Jahr, D), Ananyan (Megaputer, USA).Abstract Previex and other info: 1313textminingv207.pdf

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