Recently, recommender systems have played an increasingly important role in a wide
variety of commercial applications to help users find favourite products. Research in the …

China has experienced an outstanding economic expansion during the past decades,
however, literature on non-monetary metrics that reveal the status of China's regional …

In recommender systems, many efforts have been made on utilizing textual information in
matrix factorization to alleviate the problem of data sparsity. Recently, some of the works …

Abstract In Recommendation Systems (RS) and Collaborative Filtering (CF), the similarity
measures have been the operating component upon which CF performance is essentially …

In recent years, application of recommendation algorithm in real life such as Amazon,
Taobao is getting universal, but it is not perfect yet. A few problems need to be solved such …

With the unprecedented development in the internet technology, the information overload
issues have become more and more complex, resulting in users being unable to obtain the …

Abstract Personalized Recommender Systems (RS) are used to help people reduce the
amount of time they spend to find items they are interested in. Collaborative Filtering (CF) is …

Recommender systems have a wide range of applications in the age suffering information
overload. A promising way to design better recommender systems in the presence of …

Reputation is a valuable asset in online social lives and it has drawn increased attention.
Due to the existence of noisy ratings and spamming attacks, how to evaluate user reputation …

A variety of rating-based recommendation methods have been extensively studied including
the well-known collaborative filtering approaches and some network diffusion-based …