Text Mining and Its Applications to Intelligence, CRM and Knowledge Management
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Text Mining and Its Applications to Intelligence, CRM and Knowledge Management: (No. 7 Advances in Management Information)

Text Mining and Its Applications to Intelligence, CRM and Knowledge Management: (No. 7 Advances in Management Information)


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About the Book

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. ABOUT THE EDITOR: Alessandro Zanasi is a security research advisor and professor at Bologna University, Italy. Before he served as Carabinieri officer in Rome Scientific Investigations Center; IBM executive in Italy, Paris and San Jose (USA); META Group analyst; cofounder of Temis SA. As an intelligence specialist, he has been advising governments and corporations in security, intelligence and detection technologies 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 and Innovation Forum.

Table of Contents:
Part 1: THEORETICAL OVERVIEW Chapter 1: Text processing and information retrieval Introduction; Data gathering and extraction of text; Text processing; Information retrieval; Concluding remarks Chapter 2: Information extraction and - Surroundings Introduction; Information extraction historical flash-back; IE systems architecture; Features of an IE system; Adaptive IE systems; IE systems: a few European applications Chapter 3: Text clustering as a mining task Introduction; Overview on data clustering analysis; Problems and solutions in the text clustering field; Conclusions Chapter 4: Text categorization Introduction; The basic picture; Techniques; Applications; Conclusion; Notes Chapter 5: Summarization and visualization Introduction; Text summarization; Text visualization; Example of summarization of a document set; Future directions of research and applications Part 2: APPLICATIONS Chapter 6: Application integration in applied text mining Introduction; Business drivers and application types; Application elements; Conclusions Chapter 7: ROI in text mining projects Introduction; The evaluation of a text mining solution; The evaluation of the tangible components; The evaluation of the intangible components; Conclusions a) INTELLIGENCE Chapter 8: Open sources automatic analysis for corporate and government intelligence Introduction; New government intelligence role; Corporate intelligence; Open sources; Terrorism and other challenges to government intelligence; Practical examples of text mining applied to the intelligence process; Business cases Chapter 9: A critical appraisal of text mining in an intelligence environment Introduction; 11 Sept., intelligence and information explosion; Data mining: some world relevant examples; Data mining, the intelligence cycle and decision Chapter 10: Marketing intelligence system to forecast telecommunications competitive landscape Introduction; Italian mobile market overview; TIM positioning; From competitive to market intelligence; Our needs Chapter 11: Competitive intelligence for SMEs: An application to the Italian building sector What was the problem; Edilintelligence: what is it?; The text mining bricks of the solution: Theory and practice; Conclusions b) CRM Chapter 12: Virtual communities: human capital and other personal characteristics extraction The emergence of neo-renaissance paradigm; Intellectual and human capital; Virtual communities: where text mining is applied; Human capital in customer communities; Human capital in employee community; Human capital in social contexts; Social network links detection Chapter 13: Customer feedbacks and opinion surveys analysis in the automotive industry Introduction; Customer feedback analysis in Renault; Opinion surveys for automotive manufacturers; Conclusions Chapter 14: The Responsio email management system Introduction; Email answering by semi-supervised text classification; Responsio email management system; Case study; Discussion Chapter 15: TV channel provider: mining the user feedback Introduction; The case; The process; Conclusion c) KNOWLEDGE MANAGEMENT Chapter 16: Text mining based knowledge management in banking Introduction; The document as a primary source; Knowledge based search; Building up a knowledge management infrastructure; Integrating principles; Modules; Conclusion and future work Chapter 17: Text mining in life sciences Introduction; Text mining - current state; Ontology development; Conclusion Chapter 18: Information search and classification to foster innovation in SMEs The AREA Science Park experience The AREA Science Park and its technology transfer division; TEMIS online miner light, the TTD search engine for patents (TTDSE); TTD results Chapter 19: Media industry: how to improve documentalists efficiency Introduction; Text data production in media; Indexing textual data; Archive solutions: data bases and automatic procedures; Text mining experience in Gruner + Jahr; Conclusion Chapter 20: Link analysis in crime pattern detection Introduction; Case overview; Implementation approach; Data preprocessing; Structured data analysis; Concept extraction; Pattern analysis; Drill-down and reporting; Drill-down and reporting; Automation; Conclusion Part 3: SOFTWARE and SERVICES Chapter 21: Text mining resources Introduction A: SOFTWARE B: SERVICES


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Product Details
  • ISBN-13: 9781845642969
  • Publisher: WIT Press
  • Publisher Imprint: WIT Press
  • Series Title: No. 7 Advances in Management Information
  • ISBN-10: 1845642961
  • Publisher Date: 30 Aug 2007
  • Binding: Digital (delivered electronically)


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