Add to ORKGIn traditional recommendation systems, the challenging issues in adopting similarity-based approaches are sparsity, cold-start users and trustworthiness. We present a new paradigm of recommendation system which can utilize information from social networks ..
Information overload is a new challenge in e-commerce sites. The problem refers to the fast growing ...
Recommender systems help users faced with the problem of information overflow and provide personaliz...
Recommender systems have been strongly researched within the last decade. With the emergence and pop...
Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is w...
A review of existing approaches to recommendation in e-commerce systems is provided. A recommendatio...
The vision for Web 3.0 (also known as Semantic Web) is the ability to create meaning out of huge qua...
Abstract: Automated recommender systems have played a more and more im-portant role in marketing and...
These days, Emergence of e-commerce web sites is one of the important consequences of the Internet i...
Traditional collaborative filtering (CF) based recommender systems on the basis of user similarity o...
Similarity-based recommender systems suffer from significant limitations, such as data sparseness an...
In recent years, there is a dramatic growth in number and popularity of online social networks. Ther...
In order to alleviate the pressure of information overload and enhance consumer satisfaction, person...
In collaborative filtering recommender systems, users cannot get involved in the choice of their pee...
A network of people having established trust relations and a model for propagation of related trust ...
In this paper, we build a recommender system for a new study area: social commerce, which combines r...
Information overload is a new challenge in e-commerce sites. The problem refers to the fast growing ...
Recommender systems help users faced with the problem of information overflow and provide personaliz...
Recommender systems have been strongly researched within the last decade. With the emergence and pop...
Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is w...
A review of existing approaches to recommendation in e-commerce systems is provided. A recommendatio...
The vision for Web 3.0 (also known as Semantic Web) is the ability to create meaning out of huge qua...
Abstract: Automated recommender systems have played a more and more im-portant role in marketing and...
These days, Emergence of e-commerce web sites is one of the important consequences of the Internet i...
Traditional collaborative filtering (CF) based recommender systems on the basis of user similarity o...
Similarity-based recommender systems suffer from significant limitations, such as data sparseness an...
In recent years, there is a dramatic growth in number and popularity of online social networks. Ther...
In order to alleviate the pressure of information overload and enhance consumer satisfaction, person...
In collaborative filtering recommender systems, users cannot get involved in the choice of their pee...
A network of people having established trust relations and a model for propagation of related trust ...
In this paper, we build a recommender system for a new study area: social commerce, which combines r...
Information overload is a new challenge in e-commerce sites. The problem refers to the fast growing ...
Recommender systems help users faced with the problem of information overflow and provide personaliz...
Recommender systems have been strongly researched within the last decade. With the emergence and pop...