Statistical Methods for Recommender Systems

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

?There is an increasing demand for recommender systems due to the information overload users are facing on the Web. The goal of a recommender system is to provide personalized recommendations of produ

This book presents a collection of statistical methods and procedures to assess data coming from educational systems. The topics examined include: statistical methods for constructing composite indica

In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations. This book offers an overview of approaches to developing state-of-the-art recommender systems. The authors present current algorithmic approaches for generating personalized buying proposals, such as collaborative and content-based filtering, as well as more interactive and knowledge-based approaches. They also discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies. The final chapters cover emerging topics such as recommender systems in the social web and consumer buying behavior theory. Suitable for computer science researchers and students interested in getting an overview of the field, this book will also be useful for profes

Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between

《統計推薦系統》由LinkedIn公司的技術專家撰寫，著眼於推薦系統的核心—統計方法，不僅講解理論知識，而且分享了作者在LinkedIn和Yahoo！的實踐經驗。 《統計推薦系統》分為三部分：第一部分介紹推薦系統的組成、經典推薦方法及評估方法，並引出了探索與利用問題；第二部分圍繞點擊通過率（CTR）預估這一重要問題，重點介紹快速線上雙線性因數模型和面向回歸的隱因數模型，為熱門推薦和個性化推薦

This book presents group recommender systems, which focus on the determination of recommendations for groups of users. The authors summarize different technologies and applications of group recommende

This book presents the algorithms used to provide recommendations by exploiting matrix factorization and tensor decomposition techniques. It highlights well-known decomposition methods for recommender

This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender

"This book aims to provide a comprehensive review of state-of-the-art practices for educational recommender systems, as well as the challenges to achieve their actual deployment"--Provided by publishe

As recommender systems (RS) allow means of guiding consumers through the overloaded choices of products available, the recommendation problem has always been of great interest for both academic and in

This book comprehensively covers the topic of recommender systems, which provide personalized recommendations of products or services to users based on their previous searches or purchases. Recommende

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

In this resource for researchers, practitioners, and advanced students in tourism informatics, contributors from around the world focus on travel recommender systems (TRS), travel-related online socia

Part of Tsinghua University Texts, "Statistical Properties of Deterministic Systems" discusses the fundamental theory and computational methods of the statistical properties of deterministic discrete

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 system

For courses in Statistical Methods for the Social Sciences . Statistical methods applied to social sciences, made accessible to all through an emphasis on concepts Statistical Methods for t

Bioterrorism is not a new threat, but in an increasingly interconnected world, the potential for catastrophic outcomes is greater today than ever. The medical and public health communities are establishing biosurveillance systems designed to proactively monitor populations for possible disease outbreaks as a first line of defense. The ideal biosurveillance system should identify trends not visible to individual physicians and clinicians in near-real time. Many of these systems use statistical algorithms to look for anomalies and to trigger epidemiologic investigation, quantification, localization and outbreak management. This book discusses the design and evaluation of statistical methods for effective biosurveillance for readers with minimal statistical training. Weaving public health and statistics together, it presents basic and more advanced methods, with a focus on empirically demonstrating added value. Although the emphasis is on epidemiologic and syndromic surveillance, the stat

The book aims to investigate methods and techniques for spatial statistical analysis suitable to model spatial information in support of decision systems. Over the last few years there has been a cons

This book introduces a number of cutting edge statistical methods which can be used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, res

Statistical methods applied to social sciences, made accessible to all through an emphasis on concepts Statistical Methods for the Social Sciences introduces statistical methods to students majoring i

The book is devoted to the study of the correlation effects in many-particle systems. It presents the advanced methods of quantum statistical mechanics (equilibrium and nonequilibrium), and shows thei

The book is devoted to the study of the correlation effects in many-particle systems. It presents the advanced methods of quantum statistical mechanics (equilibrium and nonequilibrium), and shows thei

Ott and Longnecker's AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Seventh Edition, provides a broad overview of statistical methods for advanced undergraduate and graduate students from a

Although there are countless books on statistics, few are dedicated to the application of statistical methods to software engineering.Simple Statistical Methods for Software Engineering: Data and Patt

Advances in social science research methodologies and data analytic methods are changing the way research in information systems is conducted. New developments in statistical software technologies for

Concepts and Methods in Modern Theoretical Chemistry: Statistical Mechanics, the second book in a two-volume set, focuses on the dynamics of systems and phenomena. A new addition to the series Atoms,

The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic diffe

Practical Statistical Methods: A SAS Programming Approach presents a broad spectrum of statistical methods useful for researchers without an extensive statistical background. In addition to nonparamet

Presenting an extensive set of tools and methods for data analysis, Robust Nonparametric Statistical Methods, Second Edition covers univariate tests and estimates with extensions to linear models, mul

STATISTICAL METHODS FOR ENGINEERS offers a balanced, streamlined one-semester introduction to Engineering Statistics that emphasizes the statistical tools most needed by practicing engineers. Using re

Wong (earth systems and geo-information sciences, George Mason U.) and Lee (geography, Kent State U.) developed this text for quantitative methods classes introducing both statistical concepts and spa

Statistical Methods for Communication Science is the only statistical methods volume currently available that focuses exclusively on statistics in communication research. Writing in a straightforward,

This 1998 book describes the sampling and statistical methods used most often by behavioral ecologists and field biologists. Written by a biologist and two statisticians, it provides a rigorous discussion together with worked examples of statistical concepts and methods that are generally not covered in introductory courses, and which are consequently poorly understood and applied by field biologists. The first section reviews important issues such as defining the statistical population and the sampling plan when using non-random methods for sample selection, bias, interpretation of statistical tests, confidence intervals and multiple comparisons. After a detailed discussion of sampling methods and multiple regression, subsequent chapters discuss specialized problems such as pseudoreplication, and their solutions. It will quickly become the statistical handbook for all field biologists.

This 1998 book describes the sampling and statistical methods used most often by behavioral ecologists and field biologists. Written by a biologist and two statisticians, it provides a rigorous discussion together with worked examples of statistical concepts and methods that are generally not covered in introductory courses, and which are consequently poorly understood and applied by field biologists. The first section reviews important issues such as defining the statistical population and the sampling plan when using non-random methods for sample selection, bias, interpretation of statistical tests, confidence intervals and multiple comparisons. After a detailed discussion of sampling methods and multiple regression, subsequent chapters discuss specialized problems such as pseudoreplication, and their solutions. It will quickly become the statistical handbook for all field biologists.

Multiple comparisons are the comparisons of two or more treatments. These may be treatments of a disease, groups of subjects, or computer systems, for example. Statistical multiple comparison methods

A textbook for advanced undergraduate/first year graduate level courses in statistical methods in geography. Presents methods useful in research design, hypothesis testing, and analyzing spatial and f

Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book’s website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook.The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about

Handbook of Statistical Methods for Randomized Controlled Trials

Statistical Methods for Overdispersed Count Data provides a review of the most recent methods and models for such data, including a description of R functions and packages that allow their implementat