Includes bibliographic references and index.

An introduction to basic concepts on recommender systems / Pooja Rana, Nishi Jain and Usha Mittal -- A brief model overview of personalized recommendation to citizens in the health-care industry / Subhasish Mohapatra and Kunal Anand -- 2Es of TIS : a review of information exchange and extraction in tourism information systems / Malik M. Saad Missen, Mickaël Coustaty, Hina Asmat, Amnah Firdous, Nadeem Akhtar, Muhammad Akram and V.B. Surya Prasath -- Concepts of recommendation system from the perspective of machine learning / Sumanta Chandra Mishra Sharma, Adway Mitra and Deepayan Chakraborty -- A machine learning approach to recommend suitable crops and fertilizers for agriculture / Govind Kumar Jha, Preetish Ranjan and Manish Gaur -- Accuracy-assured privacy-preserving recommender system using hybrid-based deep learning method / Abhaya Kumar Sahoo and Chittaranjan Pradhan -- Machine learning-based recommender system for breast cancer prognosis / G. Kanimozhi, P. Shanmugavadivu and M. Mary Shanthi Rani -- A recommended system for crop disease detection and yield prediction using machine learning approach / Pooja Akulwar -- Content-based recommender systems / Poonam Bhatia Anand and Rajender Nath -- Content (item)-based recommendation system / R. Balamurali -- Content-based health recommender systems / Soumya Prakash Rana, Maitreyee Dey, Javier Prieto and Sandra Dudley -- Context-based social media recommendation system / R. Sujithra Kanmani and B. Surendiran -- Netflix challenge : improving movie recommendations / Vasu Goel -- Product or item-based recommender system / Jyoti Rani, Usha Mittal and Geetika Gupta -- A trust-based recommender system built on IoT blockchain network with cognitive framework / S. Porkodi and D. Kesavaraja -- Development of a recommender system HealthMudra using blockchain for prevention of diabetes / Rashmi Bhardwaj and Debabrata Datta -- Case study 1 : health care recommender systems / Usha Mittal, Nancy Singla and Geetika Gupta -- Temporal change analysis-based recommender system for Alzheimer Disease classification / S. Naganandhini, P. Shanmugavadivu and M. Mary Shanthi Rani -- Regularization of graphs : sentiment classification / R.S.M. Lakshmi Patibandla -- TSARS : a tree-similarity algorithm-based agricultural recommender system / Madhusree Kuanr, Puspanjali Mohapatra and Sasmita Subhadarsinee Choudhury -- Influenceable targets recommendation analyzing social activities in egocentric online social networks / Soumyadeep Debnath, Dhrubasish Sarkar and Dipankar Das.

"The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven to be a valuable way for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed. During the last decade, many of them have also been successfully deployed in commercial environments"-- Provided by publisher.

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John Wiley and Sons Wiley Frontlist Obook All English 2020