Review and Implementation of Common Statistical Methods for Recommender Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Review and Implementation of Common Statistical Methods for Recommender Systems write by Candace Jennifer McKeag. This book was released on 2021. Review and Implementation of Common Statistical Methods for Recommender Systems available in PDF, EPUB and Kindle. As a result of today's massive information overload, the exploration and development of recommender systems is burgeoning. This paper consists of a comprehensive literature review in which the current knowledge surrounding statistical methods for recommender systems is outlined and evaluated. For each method, the theoretical premise and application-related aspects such as optimal use cases and common research problems are described. To round out the literature review, an implementation of several collaborative filtering techniques is conducted in order to apply the discussed theory and identify some advantages and disadvantages of the methods.
Statistical Methods for Recommender Systems
Statistical Methods for Recommender Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Methods for Recommender Systems write by Deepak K. Agarwal. This book was released on 2016-02-24. Statistical Methods for Recommender Systems available in PDF, EPUB and Kindle. Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues that arise in recommender systems includes detailed, in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods), bilinear random-effects models (matrix factorization) and scalable model fitting using modern computing paradigms like MapReduce. The authors draw upon their vast experience working with such large-scale systems at Yahoo! and LinkedIn, and bridge the gap between theory and practice by illustrating complex concepts with examples from applications they are directly involved with.
Common Statistical Methods for Clinical Research with SAS Examples, Third Edition
Common Statistical Methods for Clinical Research with SAS Examples, Third Edition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Common Statistical Methods for Clinical Research with SAS Examples, Third Edition write by Glenn Walker. This book was released on 2010-02-15. Common Statistical Methods for Clinical Research with SAS Examples, Third Edition available in PDF, EPUB and Kindle. Glenn Walker and Jack Shostak's Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is a thoroughly updated edition of the popular introductory statistics book for clinical researchers. This new edition has been extensively updated to include the use of ODS graphics in numerous examples as well as a new emphasis on PROC MIXED. Straightforward and easy to use as either a text or a reference, the book is full of practical examples from clinical research to illustrate both statistical and SAS methodology. Each example is worked out completely, step by step, from the raw data. Common Statistical Methods for Clinical Research with SAS Examples, Third Edition, is an applications book with minimal theory. Each section begins with an overview helpful to nonstatisticians and then drills down into details that will be valuable to statistical analysts and programmers. Further details, as well as bonus information and a guide to further reading, are presented in the extensive appendices. This text is a one-source guide for statisticians that documents the use of the tests used most often in clinical research, with assumptions, details, and some tricks--all in one place. This book is part of the SAS Press program.
Recommender Systems for Information Providers
Recommender Systems for Information Providers - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Recommender Systems for Information Providers write by Andreas W. Neumann. This book was released on 2009-03-03. Recommender Systems for Information Providers available in PDF, EPUB and Kindle. Information providers are a very promising application area of recommender systems due to the general problem of assessing the quality of information products prior to the purchase. Recommender systems automatically generate product recommendations: customers profit from a faster finding of relevant products, stores profit from rising sales. All aspects of recommender systems are covered: the economic background, mechanism design, a survey of systems in the Internet, statistical methods and algorithms, service oriented architectures, user interfaces, as well as experiences and data from real-world applications. Specific solutions for areas with strong privacy concerns, scalability issues for large collections of products, as well as algorithms to lessen the cold-start problem for a faster return on investment of recommender projects are addressed. This book describes all steps it takes to design, implement, and successfully operate a recommender system for a specific information platform.
Recommender Systems Handbook
Recommender Systems Handbook - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Recommender Systems Handbook write by Francesco Ricci. This book was released on 2015-11-17. Recommender Systems Handbook available in PDF, EPUB and Kindle. This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, and challenges. A variety of real-world applications and detailed case studies are included. In addition to wholesale revision of the existing chapters, this edition includes new topics including: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems.
