Text Mining and its Applications to Intelligence, CRM and Knowledge Management

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
Chapter 21	Text mining tools
	Megaputer intelligence; SAS; SPSS; Synthema; TEMIS; Others