Targeted Product Promotion Using Firefly Algorithm On Social Networks
نویسنده
چکیده
Diverse demands and dynamic environment of e-market makes market segmentation imperative for decision makers to devise strategies to woo varied groups. Market Segmentation is a process to segment the large and dynamic markets into separate sub markets where customers in the same group are similar with respect to a given set of characteristics. The most prevalent technique that is used for market segmentation is clustering. Clustering refers to the partitioning of unlabeled data objects into certain number of clusters with the objective of maximum homogeneity within cluster and heterogeneity between the clusters. This chapter studies the viability of nature inspired firefly algorithm for clustering approach. It incorporates the flashing behavior of fireflies to attain the optimal solution. Experimental evaluations substantiate the effectiveness of firefly as compared to Particle Swarm Optimization (PSO), Differential Evolutionary (DE) algorithms based clustering approaches with respect to varied statistical criteria over artificial and benchmark datasets.
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