Kaynakça var.

Preface I. Introduction to Text Mining I.1 Defining Text Mining I.2 General Architecture of Text Mining Systems II. Core Text Mining Operations II.1 Core Text Mining Operations II.2 Using Background Knowledge for Text Mining II.3 Text Mining Query Languages III. Text Mining Preprocessing Techniques III.1 Task-Oriented Approaches III.2 Further Reading IV. Categorization IV.1 Applications of Text Categorization V. Clustering V.1 Clustering Tasks in Text Analysis VI. Information Extraction VI.1 Introduction to Information Extraction VI.2 Historical Evolution of IE: the Message Understanding Conferences and Tipster VI.3 IE Examples VI.4 Architecture of IE Systems VI.5 Anaphora Resolution VI.6 Inductive Algorithm for IE VI.7 Structured IE VI.8 Further Reading VII. Probabilistic Models for Information Extraction VII.1 Hidden Markov Models VII.2 Stochastic Context-Free Grammars VII.3 Maximal Entropy Modeling VII.4 Maximal Entropy Markov Models VII.5 Conditional Random Fields VII.6 Further Reading VIII Preprocessing Applications Using Probabilistic and Hybrid Ap proaches VIII.1 Applications of HMM to Textual Analysis VIII.2 Using MEMM for Information Extraction VIII.3 Applications of CRFs to Textual Analysis VIII.4 TEG: Using SCFG Rules for Hybrid Statistical/ Knowledge-Based IE VIII.5 Bootstrapping VIII.6 Further Reading IX Presentation-Layer Considerations for Browsing and Query Re finement IX.1 Browsing IX.2 Assessing Constraints and Simple Specification Filters at the Presentation Layer IX.3 Assessing the Underlying Query Language X Visualization Approaches X.1 Introduction X.2 Architectural Considerations X.3 Common Visualization Approaches for Text Mining X.4 Visualization Technique in Link Analysis X.5 Real World Example: The Document Explorer System XI Link Analysis XI.1 Preliminaries XI.2 Automatic Layout of Networks XI.3 Paths and Cycles in Graphs XI.4 Centrality XI.5 Partitioning of Networks XI.6 Pattern Matching in Networks XI.7 Software Packages for Link Analysis XII Text Mining Applications XII.1 General Considerations XII.2 Corporate Finance: Mining Industry Literature for Busi- ness Intelligence XII.3 A "Horizontal" Text Mining Application: Patent Analysis Solution Leveraging a Commercial Text Analytics Platform XII.4 Life Sciences Research: Mining Biological Pathway In- formation with Geneways Appendix: Dial: A Dedicated Information Extraction Language for Text Mining 1. Introduction to DIAN 2. Information Extraction in the DIAL Environment 3. Text Tokenization 4. Concepts and Rule Structure 5. Pattern Matching 6. Rule Constraints 7. Concept Guards 8. Actions 9. Inheritance 10. Complete Examples Bibliography