Contents:
Chapter 1 Probabilistic types for info Retrieval pages 1— Chapter 2 Learnable score versions for automated textual content Summarization and data Retrieval pages 33— Chapter three Logistic Regression and textual content category pages 59— Chapter four Kernel tools for Textual info entry pages 85— Chapter 6 Conditional Random Fields for info Extraction pages — Chapter 7 Statistical equipment for laptop Translation pages — Chapter eight info Mining pages — Chapter nine Opinion Detection as an issue class challenge pages — Mit kreativer Software zum kommerziellen Erfolg.
Bibliography Chapter 6. Information extraction 6.
Description This book presents statistical models that have recently been developed within several research communities to access information contained in text collections. General problems with kernel choices kernel engineering 95 4. Chapter 1 Probabilistic types for info Retrieval pages 1— This book presents statistical models that have recently been developed within several research communities to access information contained in text collections. Bibliography PART 4:
Machine learning for information extraction 6. Introduction to conditional random fields 6. Conditional random fields 6. Conditional random fields and their applications 6.
Bibliography PART 3: Phrase-based models 7. Modeling reorderings 7. Evaluating machine translation 7. State-of-the-art and recent developments 7.
Useful resources 7. Bibliography PART 4: The multidimensional visualization of information 8. Domain mapping via social networks 8. Analyzing the variability of searches and data merging 8. The seven types of evaluation measures used in IR 8.
Bibliography Chapter 9. Cosine weights - a second glance 9. General principles of kernel methods 88 4. General problems with kernel choices kernel engineering 95 4. Kernel versions of standard algorithms: Kernels for text entities 4. Bibliography Chapter 5.
Topic-based models 5. Topic models 5. Term models 5. Similarity measures between documents 5.
Bibliography Chapter 6. Information extraction 6. Machine learning for information extraction 6. Introduction to conditional random fields 6. Conditional random fields 6.
Conditional random fields and their applications 6. Bibliography PART 3: Phrase-based models 7. Modeling reorderings 7. Evaluating machine translation 7.