Literature ReviewOpen accessEvery word in the titleAdvances in Document Clustering with Evolutionary-Based AlgorithmsSarmad Makki, Razali Yaakob, Norwati Mustapha, Hamidah IbrahimDocument clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of … …American Journal of Applied Sciences, Vol. 12, Issue 10 · 20 Oct 2015 · 7,186 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDocument Clustering Based on Firefly AlgorithmAthraa Jasim Mohammed, Yuhanis Yusof, Husniza HusniDocument clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters. Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization. This study explores the adaptation of another swarm algorithm which … …Journal of Computer Science, Vol. 11, Issue 3 · 26 Mar 2015 · 7,510 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCLUSTERING TWEETS USING CELLULAR GENETIC ALGORITHMAmr Adel, Essam ElFakharany, Amr BadrAs the popularity of Twitter continues to increase rapidly, it is extremely necessary to analyze the huge amount of data that Twitter users generate. A popular method of tweet analysis is clustering. Because most tweets are textual, this study focuses on clustering tweets based on their textual content similarity. This study presents tweet clustering using cellular genetic algorithm cGA. The … …Journal of Computer Science, Vol. 10, Issue 7 · 16 Jun 2014 · 7,915 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleArtificial Bee Colony Algorithm Integrated with Fuzzy C-mean Operator for Data ClusteringM. Krishnamoorthi, A. M. NatarajanClustering task aims at the unsupervised classification of patterns in different groups. To enhance the quality of results, the emerging swarm-based algorithms now-a-days become an alternative to the conventional clustering methods. In this study, an optimization method based on the swarm intelligence algorithm is proposed for the purpose of clustering. The significance of the proposed algorithm is that it uses … …Journal of Computer Science, Vol. 9, Issue 4 · 6 May 2013 · 6,299 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA New Cooperative Algorithm Based on PSO and K-Means for Data ClusteringMehdi Neshat, Shima Farshchian Yazdi, Daneyal Yazdani, Mehdi SargolzaeiProblem statement: Data clustering has been applied in multiple fields such as machine learning, data mining, wireless sensor networks and pattern recognition. One of the most famous clustering approaches is K-means which effectively has been used in many clustering problems, but this algorithm has some drawbacks such as local optimal convergence and sensitivity to initial points. Approach: Particle Swarm Optimization … …Journal of Computer Science, Vol. 8, Issue 2 · 19 Nov 2011 · 7,967 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Improved Clustering Based Genetic Algorithm for Solving Complex NP ProblemsR. Sivaraj, T. RavichandranProblem statement: The selection process is a major factor in genetic algorithm which determines the optimality of solution for a complex problem. The selection pressure is the critical step which finds out the best individuals in the entire population for further genetic operators. The proposed algorithm tries to find out the best individuals with reduced selection pressure than standard genetic … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,928 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEnhanced Clustering Techniques for Hyper Network Planning using Minimum Spanning Trees and Ant-Colony AlgorithmLamiaa Fattouh IbrahimProblem statement: The process of network planning is divided into two sub steps. The first step is determining the location of the Multi Service Access Node (MSAN). The second step is the construction of subscriber network lines from MSAN to subscribers to satisfy optimization criteria and design constraints. Due to the complexity of this process artificial intelligence and clustering techniques … …Journal of Computer Science, Vol. 7, Issue 3 · 9 Mar 2011 · 6,813 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSummarizing Relational Data Using Semi-Supervised Genetic Algorithm-Based Clustering TechniquesRayner AlfredProblem statement: In solving a classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets stored in multiple tables into a single table. Unfortunately, we may loss some information when we join tables with a high degree of one-to-many association. Therefore, data transformation becomes a tedious trial-and-error work and … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,585 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleThe Parallel Maximal Cliques Algorithm for Protein Sequence ClusteringKhalid Jaber, Nur’Aini Abdul Rashid, Rosni AbdullahProblem statement: Protein sequence clustering is a method used to discover relations between proteins. This method groups the proteins based on their common features. It is a core process in protein sequence classification. Graph theory has been used in protein sequence clustering as a means of partitioning the data into groups, where each group constitutes a cluster. Mohseni-Zadeh introduced a … …American Journal of Applied Sciences, Vol. 6, Issue 7 · 31 Jul 2009 · 7,100 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimized Wireless Sensor Network Clustering Using a Hybrid Firefly–Bat Algorithm (HFBA)J. Jegan, Senthil kumar P, S. Saravanakumar et al.Wireless Sensor Networks (WSNs) are composed of numerous sensor nodes that collaborate to observe and evaluate various environmental parameters, transmitting the data to a central base station. Each node is equipped with a unique transmitter, receiver, and processor to facilitate sensing, processing, and communication. These networks are often installed in extremely remote and inaccessible areas. A significant challenge arises from … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,431 accessesView PDFCite