By Charu C. Aggarwal
This ebook comprehensively covers the subject of recommender platforms, which supply custom-made suggestions of goods or prone to clients in accordance with their earlier searches or purchases. Recommender method tools were tailored to various functions together with question log mining, social networking, information techniques, and computational ads. This booklet synthesizes either basic and complex issues of a learn region that has now reached maturity. The chapters of this publication are equipped into 3 categories:
Algorithms and evaluation: those chapters talk about the elemental algorithms in recommender structures, together with collaborative filtering equipment, content-based equipment, knowledge-based equipment, ensemble-based equipment, and evaluation.
Recommendations in particular domain names and contexts: the context of a advice could be seen as very important part info that is affecting the advice targets. varieties of context resembling temporal information, spatial info, social information, tagging facts, and trustworthiness are explored.
Advanced issues and applications: a number of robustness points of recommender platforms, resembling shilling structures, assault types, and their defenses are discussed.
In addition, fresh themes, resembling studying to rank, multi-armed bandits, crew platforms, multi-criteria platforms, and energetic studying platforms, are brought including applications.
Although this booklet essentially serves as a textbook, it is going to additionally attract commercial practitioners and researchers because of its concentrate on functions and references. a variety of examples and routines were supplied, and an answer guide is obtainable for instructors.