Text analytics -- Natural-language processing -- Information extraction -- Document representation -- Association rules mining -- Corpus-based semantic analysis -- Document clustering -- Topic modeling -- Document categorization. "Text Analytics: An Introduction to the Science …
"Text Analytics: An Introduction to the Science and Applications of Unstructured Information Analysis is a concise and accessible introduction to the science and applications of text analytics (or text mining), which enables automatic knowledge discovery from unstructured inform…
This book proposes an approach to the analysis of information using a neural network based on neural-like elements and temporal summation of signals, which makes it possible to implement a structural approach to the analysis of information streams. Together with associative acce…
" The genesis of this volume was a workshop at the Societas Linguistica Europaea conference in Vilnius in 2010, organised by Hollmann and Gisborne, on the ques-tion of what specific contribution cognitive linguistics has made to the gathering and analysis of linguistic data. " -…
How do people describe events they have witnessed? What role does linguistic aspect play in this process? To provide answers to these questions, we conducted an experiment on aspectual framing. In our task, people were asked to view videotaped vehicular accidents and to describe…
Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for …
1. Introduction to Text Mining with Machine Learning -- 2. Introduction to R -- 3. Structured Text Representations -- 4. Classification -- 5. Bayes Classifier -- 6. Nearest Neighbors -- 7. Decision Trees -- 8. Random Forest -- 9. Adaboost -- 10. Support Vector Machines -- 11. De…
1. Introduction to Text Mining with Machine Learning -- 2. Introduction to R -- 3. Structured Text Representations -- 4. Classification -- 5. Bayes Classifier -- 6. Nearest Neighbors -- 7. Decision Trees -- 8. Random Forest -- 9. Adaboost -- 10. Support Vector Machines -- 11. De…
1. Introduction to Text Mining with Machine Learning -- 2. Introduction to R -- 3. Structured Text Representations -- 4. Classification -- 5. Bayes Classifier -- 6. Nearest Neighbors -- 7. Decision Trees -- 8. Random Forest -- 9. Adaboost -- 10. Support Vector Machines -- 11. De…
