Machine Learning for Text

Text analytics is a field that lies on the interface of information retrieval, machine learning, and natural language processing. This book carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this book span three broad categories: 1. Basic algorith...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Aggarwal, Charu C. (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
Έκδοση:1st ed. 2018.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 1 An Introduction to Text Analytics
  • 2 Text Preparation and Similarity Computation
  • 3 Matrix Factorization and Topic Modeling
  • 4 Text Clustering
  • 5 Text Classification: Basic Models
  • 6 Linear Models for Classification and Regression
  • 7 Classifier Performance and Evaluation
  • 8 Joint Text Mining with Heterogeneous Data
  • 9 Information Retrieval and Search Engines
  • 10 Text Sequence Modeling and Deep Learning
  • 11 Text Summarization
  • 12 Information Extraction
  • 13 Opinion Mining and Sentiment Analysis
  • 14 Text Segmentation and Event Detection.