Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies, and Applications
eBook - ePub

Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies, and Applications

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies, and Applications

About this book

Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications captures the state of the art in usage of artificial intelligence in different types of recommendation systems and predictive analysis. The book provides guidelines and case studies for application of artificial intelligence in recommendation from expert researchers and practitioners. A detailed analysis of the relevant theoretical and practical aspects, current trends and future directions is presented. The book highlights many use cases for recommendation systems: · Basic application of machine learning and deep learning in recommendation process and the evaluation metrics · Machine learning techniques for text mining and spam email filtering considering the perspective of Industry 4.0 · Tensor factorization in different types of recommendation system · Ranking framework and topic modeling to recommend author specialization based on content. · Movie recommendation systems · Point of interest recommendations · Mobile tourism recommendation systems for visually disabled persons · Automation of fashion retail outlets · Human resource management (employee assessment and interview screening) This reference is essential reading for students, faculty members, researchers and industry professionals seeking insight into the working and design of recommendation systems.

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Yes, you can access Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies, and Applications by Abhishek Majumder,Joy Lal Sarkar,Arindam Majumder, Abhishek Majumder, Joy Lal Sarkar, Arindam Majumder in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Welcome
  2. Table of Content
  3. Title
  4. BENTHAM SCIENCE PUBLISHERS LTD.
  5. FOREWORD
  6. PREFACE
  7. List of Contributors
  8. Study of Machine Learning for Recommendation Systems
  9. Machine Learning Approaches for Text Mining and Spam E-mail Filtering: Industry 4.0 Perspective
  10. An Overview of Deep Learning-Based Recommendation Systems and Evaluation Metrics
  11. Towards Recommender Systems Integrating Contextual Information from Multiple Domains through Tensor Factorization
  12. Developing a Content-based Recommender System for Author Specialization using Topic Modelling and Ranking Framework
  13. Movie Recommendations
  14. Sentiment Analysis for Movie Reviews
  15. A Movie Recommender System with Collaborative and Content Filtering
  16. An Introduction to Various Parameters of the Point of Interest
  17. Mobile Tourism Recommendation System for Visually Disabled
  18. Point of Interest Recommendation via Tensor Factorization
  19. Exploring the Usage of Data Science Techniques for Assessment and Prediction of Fashion Retail - A Case Study Approach
  20. Data Analytics in Human Resource Recruitment and Selection
  21. A Personalized Artificial Neural Network for Rice Crop Yield Prediction