Research ArticleOpen accessIn the abstractFractional Lion Algorithm-An Optimization Algorithm for Data ClusteringSatish Chander, P. Vijaya, Praveen DhyaniClustering divides the data available as bulk into meaningful, useful groups (Clusters) without any prior knowledge about the data. Cluster analysis provides an abstraction from individual data objects to the clusters in which those objects reside. It is a key technique in the data mining and has become an important issue in many fields. This paper presents a novel Fractional … …Journal of Computer Science, Vol. 12, Issue 7 · 12 Aug 2016 · 7,673 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Acceptance Criterion (AAC) Algorithm for Optimization ProblemsAnmar AbuhamdahOptimization methods commonly are designed for solving the optimization problems. Local search algorithms are optimization method, which are good candidate in exploiting the search space. However, most of them need parameter tuning and incapable of escaping from local optima. This work proposes non-parametric Acceptance Criterion (AC) that not relies on user-defined, which motivate to propose an Adaptive Acceptance Criterion (AAC). … …Journal of Computer Science, Vol. 11, Issue 4 · 23 Jul 2015 · 6,969 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrating Correlation Clustering and Agglomerative Hierarchical Clustering for Holistic Schema MatchingBasel Alshaikhdeeb, Kamsuriah AhmadHolistic schema matching is the process of carrying off several number of schemas as an input and outputs the correspondences among them. Treating large number of schemas may consume longer time with poor quality. Therefore, several clustering approaches have been proposed in order to reduce the search space by partitioning the data into smaller portions which can facilitate the matching … …Journal of Computer Science, Vol. 11, Issue 3 · 3 Apr 2015 · 6,389 accessesView PDFCite
Research ArticleOpen accessIn the abstractDocument 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
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractCOMBINATION OF DIFFERENCE SUBSPACE AND OPPURTUNISTIC CLUSTERING ON HIGH DIMENSIONAL DATAM. Ravichandran, A. ShanmugamClustering is recognized as sigificant technique for analysing data and concentric effort has been taken in different domains comprises of recognition of pattern, statistical analysis and data mining for decades. Subspace clustering is developed from the group of cluster objects from all subspaces of a dataset. During clustering of objects involing higher dimension, the accuracy and effectiveness of traditional clustering … …Journal of Computer Science, Vol. 10, Issue 8 · 11 Mar 2014 · 6,355 accessesView PDFCite
Research ArticleOpen accessIn the abstractCLUSTER BASED DUPLICATE DETECTIONA. Venkatesh Kumar, S. VengataasalamWe propose a clustering technique for entropy based text dis-similarity calculation of de-duplication system. Improve the quality of grouping; in this study we propose a Multi-Level Group Detection (MLGD) algorithm which produces a most accurate group with most closely related object using Alternative Decision Tree (ADT) technique. Our propose a two new algorithm; first one is Multi-Level Group Detection (MLGD) … …Journal of Computer Science, Vol. 9, Issue 11 · 28 Sep 2013 · 7,035 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial 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 accessIn the abstractAn Efficient Unified K-Means Clustering Technique for Microarray Gene Expression DataP. Valarmathie, K. Dinakaran, T. RavichandranProblem statement: Using microarray techniques one could monitor the expressions levels of thousands of genes simultaneously. One challenge was how to derive meaningful insights into expressed data. This might be carried out by clustering techniques such as hierarchical and k-means, but most of the clustering techniques were largely heuristic in nature and are associated with some unresolved issues like how … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,912 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach to Medical Image SegmentationNandagopalan Shanmugam, Adiga B. Suryanarayana, Sudarshan TSB et al.Problem statement: Segmentation is a vital aspect of medical imaging. It aids in the visualization of medical data and diagnostics of various diseases. Ultrasound image segmentation, in particular echocardiographic image segmentation, is required to identify the regions of interest such as Left Ventricle (LV) and other cardiac cavities. Existing methods do not address the drawbacks of speed and quality of … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,214 accessesView PDFCite