Add to ORKGThis paper presents a stochastic model based on Monte Carlo simulation techniques for measuring the performance of recommenders. A general procedure to assess the accuracy of recommendation predictions is presented and implemented in a typical case study where input parameters are treated as random values and recommender errors are estimated using sensitive analysis. The results obtained are presented and a new perspective to the evaluation and assessment of recommender systems is discussed
Many trust-aware recommendation systems have emerged to overcome the problem of data sparsity, which...
Recommender systems have been strongly researched within the last decade. With the arising and popul...
In this paper we introduce the idea of using a reliability measure associated to the predic- tions m...
There have been various definitions, representations and derivations of trust in the context of reco...
Trust networks among users of a recommender system (RS) prove beneficial to the quality and amount o...
As an indispensable technique in the field of Information Filtering, Recommender System has been wel...
Recommender systems are powerful tools that filter and recommend content relevant to a user. One of ...
As the use of recommender systems becomes more consolidated on the Net, an increasing need arises to...
Relationships between users in social networks have been widely used to improve recommender systems....
Increasing availability of information has furthered the need for recommender systems across a varie...
Recommender systems are one of the recent inventions to deal with ever growing information overload ...
Recommender systems help Internet users quickly find information they may be interested in from an e...
In this paper, we present a model of a trust-based recommendation system on a social network. The id...
Recommender Systems (RS) have emerged as an important response to the so-called information overload...
In this paper, we present a model of a trust-based recommendation system on a social network. The id...
Many trust-aware recommendation systems have emerged to overcome the problem of data sparsity, which...
Recommender systems have been strongly researched within the last decade. With the arising and popul...
In this paper we introduce the idea of using a reliability measure associated to the predic- tions m...
There have been various definitions, representations and derivations of trust in the context of reco...
Trust networks among users of a recommender system (RS) prove beneficial to the quality and amount o...
As an indispensable technique in the field of Information Filtering, Recommender System has been wel...
Recommender systems are powerful tools that filter and recommend content relevant to a user. One of ...
As the use of recommender systems becomes more consolidated on the Net, an increasing need arises to...
Relationships between users in social networks have been widely used to improve recommender systems....
Increasing availability of information has furthered the need for recommender systems across a varie...
Recommender systems are one of the recent inventions to deal with ever growing information overload ...
Recommender systems help Internet users quickly find information they may be interested in from an e...
In this paper, we present a model of a trust-based recommendation system on a social network. The id...
Recommender Systems (RS) have emerged as an important response to the so-called information overload...
In this paper, we present a model of a trust-based recommendation system on a social network. The id...
Many trust-aware recommendation systems have emerged to overcome the problem of data sparsity, which...
Recommender systems have been strongly researched within the last decade. With the arising and popul...
In this paper we introduce the idea of using a reliability measure associated to the predic- tions m...