Text Analytics

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A01=John Atkinson-Abutridy
advanced text data analysis applications
Age Group_Uncategorized
Age Group_Uncategorized
Apple Ceo
artifiical intelligence
Association Rules
Author_John Atkinson-Abutridy
automatic-update
Bayesian classification
Categorization
Category1=Non-Fiction
Category=UNF
Clustering
computational linguistics
COP=United Kingdom
Corpus-based Semantic Analysis
Delivery_Pre-order
Dirichlet Distribution
Document Categorization
Document Clustering
Document Vectors
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Frequent Itemsets
Information Extraction
Language_English
LDA
lexical analysis
Mining
MLE Estimator
Natural-Language Processing
NLP
PA=Temporarily unavailable
Part-of Speech Tagging
POS
POS Tag
Price_€100 and above
PS=Active
Query Vector
regular expressions
Roc Curve
Rule Extraction Method
semantic parsing
softlaunch
Supervised Machine Learning
Text Analytics
Text Analytics Tasks
Text Mining
Textual Analysis Applications
Topic Modeling
unsupervised algorithms
Unsupervised Machine Learning
Vice Versa
Word Embeddings

Product details

  • ISBN 9781032249797
  • Weight: 520g
  • Dimensions: 156 x 234mm
  • Publication Date: 06 May 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
  • Language: English
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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 information sources, for both industrial and academic purposes. The book introduces the main concepts, models, and computational techniques that enable the reader to solve real decision-making problems arising from textual and/or documentary sources.

Features:

  • Easy-to-follow step-by-step concepts and methods
  • Every chapter is introduced in a very gentle and intuitive way so students can understand the WHYs, WHAT-IFs, WHAT-IS-THIS-FORs, HOWs, etc. by themselves
  • Practical programming exercises in Python for each chapter
  • Includes theory and practice for every chapter, summaries, practical coding exercises for target problems, QA, and sample code and data available for download at https://www.routledge.com/Atkinson-Abutridy/p/book/9781032249797

John Atkinson-Abutridy has been a university professor and researcher over the last 25 years. He received a PhD in Artificial Intelligence (AI) from the University of Edinburgh (UK), and has led scientific and technological projects both at national and international levels on several AI topics including Natural-Language Processing, Machine Learning, Evolutionary Computation, and Text Mining, and has published almost 100 peer review scientific articles in journals and conferences. Furthermore, he has been AI consultant and transferred some intelligent system technologies into the industry. Dr. Atkinson-Abutridy has been a visiting researcher/professor in several universities and research centers worldwide such as the University of Cambridge (UK), MIT (USA), IBM T.J. Watson Labs (USA), and INRIA (France). He is also a professional member of the AAAI and a senior member of the ACM.

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