This paper describes a technique for making personalized recommendations from any type of database to a user based on similarities between the interest pro le of that user and tho...
With hundreds of millions of participants, social media services have become commonplace. Unlike a traditional social network service, a microblogging network like Twitter is a hy...
In this paper we propose a novel recommender system which enhances user-based collaborative filtering by using a trust-based social network. Our main idea is to use infinitesimal ...
Many software projects fail because they overlook stakeholders or involve the wrong representatives of significant groups. Unfortunately, existing methods in stakeholder analysis...
Soo Ling Lim, Daniele Quercia, Anthony Finkelstein
Collaborative filtering requires a centralized rating database. However, within a peer-to-peer network such a centralized database is not readily available. In this paper, we pro...
Jun Wang, Johan A. Pouwelse, Reginald L. Lagendijk...