“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

In this age of information overload, people use a variety of strategies to make choices about
what to buy, how to spend their leisure time, and even whom to date. Recommender …

Recommender systems are now popular both commercially and in the research community,
where many approaches have been suggested for providing recommendations. In many …

Recommender systems are now popular both commercially and in the research community,
where many approaches have been suggested for providing recommendations. In many …

Despite the rapid growth in social network sites and in data mining for emotion (sentiment
analysis), little research has tied the two together, and none has had social science goals …

There is an increasing consensus in the Recommender Systems community that the
dominant error-based evaluation metrics are insufficient, and mostly inadequate, to properly …

Promoting recommender systems in real-world applications requires deep investigations
with emphasis on their next generation. This survey offers a comprehensive and systematic …

While recommender systems can greatly enhance the user experience, the entry barriers in
terms of data acquisition are very high, making it hard for new service providers to compete …

Collaborative filtering (CF) recommenders based on User-Item rating matrix as explicitly
obtained from end users have recently appeared promising in recommender systems …

The evaluation of collaborative filtering shares a number of similarities with that of
classification. This similarity is due to the fact that collaborative filtering can be viewed as a …