A Newton's Universal Gravitation Inspired Firefly Algorithm for Document Clustering

摘要

The divisive clustering has the advantage to build a hierarchical structure that is more efficient to represent documents in search engines. Its operation employs one of the partition clustering algorithms that leads to being trapped in a local optima. This paper proposes a Firefly algorithm that is based on Newton's law of universal gravitation, known as Gravitation Firefly Algorithm (GFA), for document clustering. GFA is used to find centers of clusters based on objective function that maximizes the force between each document and an initial center. Upon identification of a center, the algorithm then locates documents that are similar to the center using cosine similarity function. The process of finding centers for new clusters continues by sorting the light intensity values of the balance documents. Experimental results on Reuters datasets showed that the proposed Newton inspired Firefly algorithm is suitable to be used for document clustering in text mining.