6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing

Research Article

A recommender system based on the collaborative behavior of bird flocks

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  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2010.11,
        author={Esin Saka and Olfa Nasraoui},
        title={A recommender system based on the collaborative behavior of bird flocks},
        proceedings={6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing},
        publisher={IEEE},
        proceedings_a={COLLABORATECOM},
        year={2011},
        month={5},
        keywords={Swarm intelligence recommender system collaborative filtering flocks of agents bird flocks},
        doi={10.4108/icst.collaboratecom.2010.11}
    }
    
  • Esin Saka
    Olfa Nasraoui
    Year: 2011
    A recommender system based on the collaborative behavior of bird flocks
    COLLABORATECOM
    ICST
    DOI: 10.4108/icst.collaboratecom.2010.11
Esin Saka1,*, Olfa Nasraoui1,*
  • 1: Knowledge Discovery and Web Mining Lab, University of Louisville, Louisville, KY, USA
*Contact email: esin.saka@louisville.edu, olfa.nasraoui@louisville.edu

Abstract

This paper proposes a swarm intelligence based recommender system (FlockRecom) based on the collaborative behavior of bird flocks for generating Top-N recommendations. The flock-based recommender algorithm (FlockRecom) iteratively adjusts the position and speed of dynamic flocks of agents on a visualization panel. By using the neighboring agents on the visualization panel, top-n recommendations are generated. The performance of FlockRecom is evaluated using the Jester Dataset-2 and is compared with a traditional collaborative filtering based recommender system. Experiments on real data illustrate the workings of the recommender system and its advantages over its CF baseline.