Description
McGraw Hill Recommender Systms In E-Com by Bhasker and Bharat
The proliferation of Internet technologies and e-commerce has made the webspace an exciting and interactive business platform for producers, marketers and consumers. At the same time, web itself has become complex and difficult to navigate, overwhelming users with innumerable choices of products, services, and/or information. But, help is at hand with recommender systems which can overcome the information overload problem by retrieving appropriate information based on a user's past purchases, tastes and preferences and those of similar users. Written by seasoned IT experts with extensive research and industry experience, Recommender Systems in e-Commerce deals with recommendation systems, process and techniques in detail. Enriched with illustrative diagrams and examples, the book covers: Processes, characteristics and classification of recommendation systems, Basic techniques used in recommendation systems: Collaborative Filtering, Data Mining, Information Retrieval/Content Filtering, Design, development and evaluation of recommendation system for low-involvement and high-involvement products, Applications of recommendation systems. The book will be useful for professionals working in e-commerce industry, management students, faculty and researchers.