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