
- 350 pages
- English
- PDF
- Available on iOS & Android
Functional Applications of Text Analytics Systems
About this book
Text analytics consist of the statistics about a text element, which includes the word count, the word histogram, and the word frequency histogram. Most text documents of value are related to otherāsometimes many otherādocuments, and so analytics describing the relative frequency of terms in a document compared to its peers are important for defining key words (tagging, labeling, indexing), search-responsive terms (query terms), and compressed versions of the documents (key words, summary, etc.).This clearly written text explains the functional applications of search, translation, optimization, and learning with regard to text analytics. Generation of analytics is aided by a hybrid, ensemble, or other combinatorial approach in which two or more effective analytic processes are used simultaneously, and their outputs combined to form a better "consensus". Additional value to the preservation of the information is provided through these methods. Also, since they encompass capabilities of two or more knowledge-generating systems, they can create a "superset" of access points to the data generated. The book also describes the role of functional approaches in the testing and configuration of these systems.
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Information
Table of contents
- Front Cover
- Functional Applications of Text Analytics Systems
- Contents
- Preface
- Acknowledgement
- List of Figures
- List of Tables
- List of Abbreviations
- 1 Linguistics and NLP
- 2 Summarization
- 3 Clustering, Classification, and Categorization
- 4 Translation
- 5 Optimization
- 6 Learning
- 7 Testing and Configuration
- Index
- About the Author
- Back Cover