Title :
A recommender system based on the collaborative behavior of bird flocks
Author :
Saka, Esin ; Nasraoui, Olfa
Author_Institution :
Knowledge Discovery & Web Min. Lab., Univ. of Louisville, Louisville, KY, USA
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.
Keywords :
data visualisation; recommender systems; CF baseline; FlockRecom; Jester Dataset-2; collaborative bird flock behavior; flock based recommender algorithm; swarm intelligence based recommender system; top-n recommendations; visualization panel; Artificial intelligence; Awards activities; Measurement; Variable speed drives; Visualization; Swarm intelligence; bird flocks; collaborative filtering; flocks of agents; recommender system;
Conference_Titel :
Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2010 6th International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
978-963-9995-24-6