Add to ORKGThis PhD thesis addresses the following problem: exploiting of trust information in order to enhance the accuracy and the user acceptance of current Recommender Systems (RS). RSs suggest to users items they will probably like. Up to now, current RSs mainly generate recommendations based on users' opinions on items. Nowadays, with the growth of online communities, emarketplaces, weblogs and peer-to-peer networks, a new kind of information is available: rating expressed by an user on another user (trust). We analyze current RS weaknesses and show how use of trust can overcome them. We proposed a solution about exploiting of trust into RSs and underline what experiments we will run in order to test our solution
Similarity-based recommender systems suffer from significant limitations, such as data sparseness an...
Recommender systems are one of the recent inventions to deal with ever growing information overload ...
Recommender Systems (RS) have emerged as an important response to the so-called information overload...
This PhD thesis addresses the following problem: exploiting of trust information in order to enhance...
information online, which results into an exponential growth of world wide web data. This leads to t...
Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is w...
Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is w...
Recommender Systems allow people to find the resources they need by making use of the experiences a...
The incorporation of a trust network among the users of a recommender system (RS) proves beneficial ...
The incorporation of a trust network among the users of a recommender system (RS) proves beneficial ...
Trust networks among users of a recommender system (RS) prove beneficial to the quality and amount o...
Abstract. Recommender Systems (RS) suggest to users items they might like such as movies or songs. H...
Information overload is a new challenge in e-commerce sites. The problem refers to the fast growing ...
Recommender Systems (RS) suggest to users items they might like such as movies or songs. However th...
A significant remaining challenge for existing recommender systems is that users may not trust recom...
Similarity-based recommender systems suffer from significant limitations, such as data sparseness an...
Recommender systems are one of the recent inventions to deal with ever growing information overload ...
Recommender Systems (RS) have emerged as an important response to the so-called information overload...
This PhD thesis addresses the following problem: exploiting of trust information in order to enhance...
information online, which results into an exponential growth of world wide web data. This leads to t...
Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is w...
Recommendation systems or recommender system (RSs) is one of the hottest topics nowadays, which is w...
Recommender Systems allow people to find the resources they need by making use of the experiences a...
The incorporation of a trust network among the users of a recommender system (RS) proves beneficial ...
The incorporation of a trust network among the users of a recommender system (RS) proves beneficial ...
Trust networks among users of a recommender system (RS) prove beneficial to the quality and amount o...
Abstract. Recommender Systems (RS) suggest to users items they might like such as movies or songs. H...
Information overload is a new challenge in e-commerce sites. The problem refers to the fast growing ...
Recommender Systems (RS) suggest to users items they might like such as movies or songs. However th...
A significant remaining challenge for existing recommender systems is that users may not trust recom...
Similarity-based recommender systems suffer from significant limitations, such as data sparseness an...
Recommender systems are one of the recent inventions to deal with ever growing information overload ...
Recommender Systems (RS) have emerged as an important response to the so-called information overload...