Leveraging Transitive Trust Relations to Improve Cross-Domain Recommendation

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Leveraging Position Bias to Improve Peer Recommendation

With the advent of social media and peer production, the amount of new online content has grown dramatically. To identify interesting items in the vast stream of new content, providers must rely on peer recommendation to aggregate opinions of their many users. Due to human cognitive biases, the presentation order strongly affects how people allocate attention to the available content. Moreover,...

متن کامل

A Novel Trust Computation Method Based on User Ratings to Improve the Recommendation

Today, the trust has turned into one of the most beneficial solutions to improve recommender systems, especially in the collaborative filtering method. However, trust statements suffer from a number of shortcomings, including the trust statements sparsity, users' inability to express explicit trust for other users in most of the existing applications, etc. Thus to overcome these problems, this ...

متن کامل

Leveraging Missing Ratings to Improve Online Recommendation Systems

Vol. XLIII (August 2006), 355–365 355 © 2006, American Marketing Association ISSN: 0022-2437 (print), 1547-7193 (electronic) *Yuanping Ying is Assistant Professor of Marketing, School of Management, University of Texas, Dallas (e-mail: [email protected]). Fred Feinberg is Hallman Fellow and Bank One Corporation Associate Professor of Marketing, Stephen M. Ross School of Business, University o...

متن کامل

Recommendation System Leveraging Heterogeneity of Trust in Social Networks

Recommendation systems are an integral part of many online services ranging from content streaming websites like Netflix to online shopping websites like Amazon. They improve the online experience by suggesting new products that match users’ interests and preferences. Collaborative filtering [4] methods are the most commonly used techniques in recommendation systems which rely on collection and...

متن کامل

Leveraging Decomposed Trust in Probabilistic Matrix Factorization for Effective Recommendation

Trust has been used to replace or complement ratingbased similarity in recommender systems, to improve the accuracy of rating prediction. However, people trusting each other may not always share similar preferences. In this paper, we try to fill in this gap by decomposing the original single-aspect trust information into four general trust aspects, i.e. benevolence, integrity, competence, and p...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IEEE Access

سال: 2018

ISSN: 2169-3536

DOI: 10.1109/access.2018.2850706