Recommender systems aim at predicting users' preferences based on abundant information,
such as user ratings, demographics, and reviews. Although reviews are sparser than ratings …

Social media has gained huge importance in our lives wherein there is an enormous
demand of getting high social popularity. With the emergence of many social media …

This paper proposes a new measure for recommendation through integrating Triangle and
Jaccard similarities. The Triangle similarity considers both the length and the angle of rating …

A classical problem that frequently compromises Recommender System (RS) accuracy is
the sparsity of the data about the interactions of the users with the items to be recommended …

A tag-aware recommender system (TRS) presents the challenge of tag sparsity in a user
profile. Previous work focuses on expanding similar tags and does not link the tags with …

Web 2.0 or social web applications such as online discussion forums, blogs and Wikipedia
have improved knowledge sharing by providing an environment in which users can …

The social web interactions have extended the sharing and the growth of web resources on
the web. The collaborative web services (folksonomies) enable users to assign their freely …

Recommendation systems have been well established to reduce the problem of information
overload and have become one of the most valuable tools applicable to different domains …

Social annotations are valuable resources generated by users on the Web, which encode
abundant information on user preferences for certain documents. Social annotation-based …

In this paper we propose a method that can enhance the social popularity of a post (ie, the
number of views or likes) by recommending appropriate hash tags considering both content …