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OverviewThis monograph provides an overview of bandit algorithms inspired by various aspects of Information Retrieval (IR), such as click models, online ranker evaluation, personalization or the cold-start problem. Using a survey style, each chapter focuses on a specific IR problem and explains how it was addressed with various bandit approaches. Within each section, all the algorithms are presented in chronological order. The monograph shows how specific concepts related to bandit algorithms. This comprehensive, chronological approach enables the author to explain the impact of IR on the development of new bandit algorithms as well as the impact of bandit algorithms on the development of new methods in IR.The survey is primarily intended for two groups of readers: researchers in Information Retrieval or Machine Learning and practicing data scientists. It is accessible to anyone who has completed introductory to intermediate level courses in machine learning and/or statistics. Full Product DetailsAuthor: Dorota GłowackaPublisher: now publishers Inc Imprint: now publishers Inc Weight: 0.205kg ISBN: 9781680835748ISBN 10: 1680835742 Pages: 138 Publication Date: 23 May 2019 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1. Introduction 2. Reinforcement Learning and Bandit Algorithms 3. Click Models and Bandit Algorithms 4. Ranking and Optimization 5. Ranker Evaluation 6. Recommendation 7. Conclusions and Research Trends 8. Conclusions and Future Directions Acknowledgements ReferencesReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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