عنوان

Recommender systems :

شابک

3319296590

شابک

9783319296593

شابک اشتباه

3319296574

شابک اشتباه

9783319296579

کد کشور

bnb

شماره

b623949

عنوان اصلي

Recommender systems :

نام عام مواد

[Book]

ساير اطلاعات عنواني

the textbook /

نام نخستين پديدآور

Charu C. Aggarwal.

نام خاص و کميت اثر

1 online resource (xxi, 498 pages) :

ساير جزييات

illustrations (some color)

متن يادداشت

Includes bibliographical references and index.

متن يادداشت

An Introduction to Recommender Systems -- Neighborhood-Based Collaborative Filtering -- Model-Based Collaborative Filtering -- Content-Based Recommender Systems -- Knowledge-Based Recommender Systems -- Ensemble-Based and Hybrid Recommender Systems -- Evaluating Recommender Systems -- Context-Sensitive Recommender Systems -- Time- and Location-Sensitive Recommender Systems -- Structural Recommendations in Networks -- Social and Trust-Centric Recommender Systems -- Attack-Resistant Recommender Systems -- Advanced Topics in Recommender Systems.

بدون عنوان

0

متن يادداشت

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. Recommender system methods have been adapted to diverse applications including query log mining, social networking, news recommendations, and computational advertising. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three categories: - Algorithms and evaluation: These chapters discuss the fundamental algorithms in recommender systems, including collaborative filtering methods, content-based methods, knowledge-based methods, ensemble-based methods, and evaluation. - Recommendations in specific domains and contexts: the context of a recommendation can be viewed as important side information that affects the recommendation goals. Different types of context such as temporal data, spatial data, social data, tagging data, and trustworthiness are explored. - Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defenses are discussed. In addition, recent topics, such as learning to rank, multi-armed bandits, group systems, multi-criteria systems, and active learning systems, are introduced together with applications. Although this book primarily serves as a textbook, it will also appeal to industrial practitioners and researchers due to its focus on applications and references. Numerous examples and exercises have been provided, and a solution manual is available for instructors. About the Author: Charu C. Aggarwal is a Distinguished Research Staff Member (DRSM) at the IBM T.J. Watson Research Center in Yorktown Heights, New York. He completed his B.S. from IIT Kanpur in 1993 and his Ph. D. from the Massachusetts Institute of Technology in 1996. He has published more than 300 papers in refereed conferences and journals, and has applied for or been granted more than 80 patents. He is author or editor of 15 books, including a textbook on data mining and a comprehensive book on outlier analysis. Because of the commercial value of his patents, he has thrice been designated a Master Inventor at IBM. He has received several internal and external awards, including the EDBT Test-of-Time Award (2014) and the IEEE ICDM Research Contributions Award (2015). He has also served as program or general chair of many major conferences in data mining. He is a fellow of the SIAM, ACM, and the IEEE, for ℓ́ℓcontributions to knowledge discovery and data mining algorithms.ℓ́ℓ.

منبع سفارش / آدرس اشتراک

OverDrive, Inc.

شماره انبار

8A97FEEB-0425-492D-805E-80DBFF3D5B75

عنوان

Recommender systems.

شماره استاندارد بين المللي کتاب و موسيقي

9783319296579

موضوع مستند نشده

Recommender systems (Information filtering)

موضوع مستند نشده

Artificial intelligence.

موضوع مستند نشده

Computers-- Database Management-- Data Mining.

موضوع مستند نشده

Computers-- Intelligence (AI) & Semantics.

موضوع مستند نشده

Data mining.

موضوع مستند نشده

Recommender systems (Information filtering)

موضوع مستند نشده

COM021030

موضوع مستند نشده

UNF

موضوع مستند نشده

UYQE

شماره

ويراست

شماره رده

مستند نام اشخاص تاييد نشده

Aggarwal, Charu C.

تاريخ عمليات

20201221083051.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

کد کاربرگه

270410

تكميل شده

Y