2nd International ICST Workshop on the Value of Security through Collaboration

Research Article

Reputation-based Trust-Aware Recommender System

  • @INPROCEEDINGS{10.1109/SECCOMW.2006.359555,
        author={Sukumal  Kitisin and Clifford  Neuman},
        title={Reputation-based Trust-Aware Recommender System},
        proceedings={2nd International ICST Workshop on the Value of Security through Collaboration},
        publisher={IEEE},
        proceedings_a={SECOVAL},
        year={2007},
        month={5},
        keywords={Recommender Systems Trust Reputation Credit Model Expertise Measure},
        doi={10.1109/SECCOMW.2006.359555}
    }
    
  • Sukumal Kitisin
    Clifford Neuman
    Year: 2007
    Reputation-based Trust-Aware Recommender System
    SECOVAL
    IEEE
    DOI: 10.1109/SECCOMW.2006.359555
Sukumal Kitisin1,*, Clifford Neuman2,*
  • 1: Department of Computer Science, Kasetsart Univeristy, Bangkok, Thailand
  • 2: USC/Information Sciences Institute, Marina del Rey, CA, USA
*Contact email: sukumal.i@ku.ac.th, bcn@isi.edu

Abstract

The volume of information available grows so large that it is time-consuming for people to find relevant reliable quality information. With the growth of online communities like Web boards and e-commerce communities, a new kind of information is made available - rating given by one user to another user. However, conventional recommender systems compute their recommendations regardless of the recommenders' past behaviors and reputation. They omit these significant social elements commonly done in decision making and advice seeking process in the real world. We propose an approach to include the social factors e.g. user's past behaviors and reputation together as an element of trust that can be incorporated into the current recommender system framework and show our experiments in order to test our solution