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Document clustering for knowledge discovery using nature-inspired algorithm


Mohammed, Athraa Jasim and Yusof, Yuhanis and Husni, Husniza (2014) Document clustering for knowledge discovery using nature-inspired algorithm. In: Knowledge Management International Conference 2014 (KMICe2014), 12-15 August 2014, Langkawi, Malaysia.

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Abstract

As the internet is overload with information, various knowledge based systems are now equipped with data analytics features that facilitate knowledge discovery.This includes the utilization of optimization algorithms that mimics the behavior of insects or animals.This paper presents an experiment on document clustering utilizing the Gravitation Firefly algorithm (GFA).The advantage of GFA is that clustering can be performed without a pre-defined value of k clusters.GFA determines the center of clusters by identifying documents with high force.Upon identification of the centers, clusters are created based on cosine similarity measurement.Experimental results demonstrated that GFA utilizing a random positioning of documents outperforms existing clustering algorithm such as Particles Swarm Optimization (PSO) and K-means.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Organized by: School of Computing, UUM CAS, Universiti Utara Malaysia
Uncontrolled Keywords: Firefly Algorithm, Data Mining, Text clustering, Knowledge Discovery.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Computing
Depositing User: Dr. Yuhanis Yusof
Date Deposited: 20 Nov 2014 04:03
Last Modified: 22 May 2016 07:44
URI: http://repo.uum.edu.my/id/eprint/12731

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