Coupled Low Rank Approximation for Collaborative Filtering in Social Networks

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

Mixture-Rank Matrix Approximation for Collaborative Filtering

Low-rank matrix approximation (LRMA) methods have achieved excellent accuracy among today’s collaborative filtering (CF) methods. In existing LRMA methods, the rank of user/item feature matrices is typically fixed, i.e., the same rank is adopted to describe all users/items. However, our studies show that submatrices with different ranks could coexist in the same user-item rating matrix, so that...

متن کامل

Low Rank Matrix Approximation for Geometry Filtering

Wepropose a robust, anisotropic normal estimationmethod for both point clouds and meshes using a low rank matrix approximation algorithm. First, we compute a local feature descriptor for each point and find similar, non-local neighbors that we organize into a matrix. We then show that a low rank matrix approximation algorithm can robustly estimate normals for both point clouds and meshes. Furth...

متن کامل

Collaborative Filtering Approach For Big Data Applications in Social Networks

In this paper Collaborative Filtering approach (Club CF) is planned recruiting similar services in the same clusters to recommend services collaboratively (Recommender Service System).Technically this approach is enacted around two stages: In first stage, the available services are divided into small-scale clusters in logic for further processing. In second stage, a collaborative filtering algo...

متن کامل

Collaborative Filtering for People to People Recommendation in Social Networks

Predicting people other people may like has recently become an important task in many online social networks. Traditional collaborative filtering approaches are popular in recommender systems to effectively predict user preferences for items. However, in online social networks people have a dual role as both “users” and “items”, e.g., both initiating and receiving contacts. Here the assumption ...

متن کامل

Information Filtering on Coupled Social Networks

In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybri...

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.2018.2806488