A New Glowworm Swarm Optimization Based Clustering Algorithm for Multimedia Documents

Abstract

Due to the explosion of multimedia data, the demand for the sophisticated multimedia knowledge discovery systems has been increased. The multimodal nature of multimedia data is the big barrier for knowledge extraction. The representation of multimodal data in a unimodal space will be more advantageous for any mining task. We initially represent the multimodal multimedia documents in a unimodal space by converting the multimedia objects into signal objects. The dynamic nature of the glowworms motivated us to propose the Glowworm Swarm Optimization based Multimedia Document Clustering (GSOMDC) algorithm to group the multimedia documents into topics. The better purity and entropy values indicates that the GSOMDC algorithm successfully clusters the multimedia documents into topics. The goodness of the clustering is evaluated by performing the cluster based retrieval of multimedia documents with better precision values.