Cover Image

Handbook of research on text and Web mining technologies

"This handbook presents recent advances and surveys of applications in text and web mining of interests to researchers and end-users "--Provided by publisher.

Bibliographic Details
Corporate Author: IGI Global.
Other Authors: Song, Min, 1969-, Wu, Yi-Fang, 1970-
Format: Electronic
Language:English
Published: Hershey, Pa. : IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA), c2009.
Subjects:
Data mining > Handbooks, manuals, etc.
Web databases > Handbooks, manuals, etc.
Core text mining operations
Data mining techniques in text mining
Data preprocessing techniques
Emerging directions of text mining
Evaluation techniques of text mining
Information extraction
Information retrieval
Link analysis
Natural language processing (NLP)
Taxonomy of text mining
Text categorization
Text clustering
Text mining applications
Text mining case studies
Visualization approaches
Online Access:View fulltext via EzAccess
Table of Contents:
  • Vol. 1. Section 1. Document Preprocessing
  • 1. On Document Representation and Term Weights in Text Classification
  • 2. Deriving Document Keyphrases for Text Mining
  • 3. Intelligent Text Mining: Putting Evolutionary Methods and Language Technologies Together
  • Section 2. Classification and Clustering
  • 4. Automatic Syllabus Classification Using Support Vector Machines
  • 5. Partially Supervised Text Categorization
  • 6. Image Classification and Retrieval with Mining Technologies
  • 7. Improving Techniques for Naïve Bayes Text Classifiers
  • 8. Using the Text Categorization Framework for Protein Classification
  • 9. Featureless Data Clustering
  • 10. Swarm Intelligence in Text Document Clustering
  • 11. Some Efficient and Fast Approaches to Document Clustering
  • 12. SOM-Based Clustering of Textual Documents Using WordNet
  • 13. A Multi-Agent Neural Network System for Web Text Mining
  • Section 3. Database, Ontology, and the Web
  • 14. Frequent Mining on XML Documents
  • 15. The Process and Application of XML Data Mining
  • 16. Approximate Range Querying over Sliding Windows
  • 17. Slicing and Dicing a Linguistic Data Cube
  • 18. Discovering Personalized Novel Knowledge from Text
  • 19. Untangling BioOntologies for Mining Biomedical Information
  • 20. Thesaurus-Based Automatic Indexing
  • 21. Concept-Based Text Mining
  • 22. Statistical Methods for User Profiling in Web Usage Mining
  • 23. Web Mining to Identify People of Similar Background
  • 24. Hyperlink Structure Inspired by Web Usage
  • 25. Designing and Mining Web Applications: A Conceptual Modeling Approach
  • Vol. 2.
  • 26. Web Usage Mining for Ontology Management
  • 27. A Lattice-Based Framework for Interactively and Incrementally Mining Web Traversal Patterns
  • 28. Privacy-Preserving Data Mining on the Web: Foundations and Techniques
  • Section 4. Information Retrieval and Extraction
  • 29. Automatic Reference Tracking
  • 30. Determination of Unithood and Termhood for Term Recognition
  • 31. Retrieving Non-Latin Information in a Latin Web: The Case of Greek
  • 32. Latent Semantic Analysis and Beyond
  • 33. Question Answering Using Word Associations
  • 34. The Scent of a Newsgroup: Providing Personalized Access to Usenet Sites through Web Mining
  • Section 5. Application and Survey
  • 35. Text Mining in Program Code
  • 36. A Study of Friendship Networks and Blogosphere
  • 37. An HL7-Aware Decision Support System for E-Health
  • 38. Multitarget Classifiers for Mining in Bioinformatics
  • 39. Current Issues and Future Analysis in Text Mining for Information Security Applications
  • 40. Collaborative Filtering Based Recommendation Systems
  • 41. Performance Evaluation Measures for Text Mining
  • 42. Text Mining in Bioinformatics: Research and Application
  • 43. Literature Review in Computational Linguistics Issues in the Developing Field of Consumer Informatics: Finding the Right Information for Consumer's Health Information Need
  • 44. A Survey of Selected Software Technologies for Text Mining
  • 45. Application of Text Mining Methodologies to Health Insurance Schedules
  • 46. Web Mining System for Mobile-Phone Marketing
  • 47. Web Service Architectures for Text Mining: An Exploration of the Issues via an E-Science Demonstrator.

Similar Items