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150 results for “Clustering Algorithm”
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Research ArticleOpen accessPhrase in the titleCOMPARATIVE STUDY OF K-MEANS AND K-MEANS++ CLUSTERING ALGORITHMS ON CRIME DOMAINBashar Aubaidan, Masnizah Mohd, Mohammed AlbaredThis study presents the results of an experimental study of two document clustering techniques which are k-means and k-means++. In particular, we compare the two main approaches in crime document clustering. The drawback of k-means is that the user needs to define the centroid point. This becomes more critical when dealing with document clustering because each center point represented by … …Journal of Computer Science, Vol. 10, Issue 7 · 19 Feb 2014 · 7,762 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleContent Based Medical Image Retrieval with Texture Content Using Gray Level Co-occurrence Matrix and K-Means Clustering AlgorithmsB. Ramamurthy, K. R. ChandranProblem statement: Recently, there has been a huge progress in collection of varied image databases in the form of digital. Most of the users found it difficult to search and retrieve required images in large collections. In order to provide an effective and efficient search engine tool, the system has been implemented. In image retrieval system, there is no methodologies … …Journal of Computer Science, Vol. 8, Issue 7 · 24 May 2012 · 7,448 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleUsing Hyper Clustering Algorithms in Mobile Network PlanningLamiaa Fattouh Ibrahim, Hesham A. SalmanProblem statement: As a large amount of data stored in spatial databases, people may like to find groups of data which share similar features. Thus cluster analysis becomes an important area of research in data mining. Applications of clustering analysis have been utilized in many fields, such as when we search to construct a cluster served by base station in … …American Journal of Applied Sciences, Vol. 8, Issue 10 · 30 Aug 2011 · 7,504 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Rough Set based Gene Expression Clustering AlgorithmJ. Jeba Emilyn, K. RamarProblem statement: Microarray technology helps in monitoring the expression levels of thousands of genes across collections of related samples. Approach: The main goal in the analysis of large and heterogeneous gene expression datasets was to identify groups of genes that get expressed in a set of experimental conditions. Results: Several clustering techniques have been proposed for identifying gene signatures and … …Journal of Computer Science, Vol. 7, Issue 7 · 28 Jun 2011 · 6,830 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleImproving the Performance of Multivariate Bernoulli Model based Documents Clustering Algorithms using Transformation TechniquesPerumal Pitchandi, Nedunchezhian RajuProblem statement: Document clustering is the most important areas of data mining since they are very much and currently the subject of significant global research since such areas strengthen the enterprises of web intelligence, web mining, web search engine design and so forth. Generative models based on the multivariate Bernoulli and multinomial distributions have been widely used for text classification. … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,281 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleNew Efficient Strategy to Accelerate k-Means Clustering AlgorithmMoh’d Belal Al- Zoubi, Amjad Hudaib, Ammar Huneiti, Bassam HammoOne of the most popular clustering techniques is the k-means clustering algorithm. However, the utilization of the k-means is severely limited by its high computational complexity. In this study, we propose a new strategy to accelerate the k-means clustering algorithm through the Partial Distance (PD) logic. The proposed strategy avoids many unnecessary distance calculations by applying efficient PD strategy. Experiments … …American Journal of Applied Sciences, Vol. 5, Issue 9 · 30 Sep 2008 · 7,437 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Novel Distributed Clustering Algorithm for Mobile Ad-hoc NetworksSahar Adabi, Sam Jabbehdari, Amirmasoud Rahmani, Sepideh AdabiThis paper proposed a new Distributed Score Based Clustering Algorithm (DSBCA) for Mobile Ad-hoc Networks (MANETs).In MANETs, select suitable nodes in clusters as cluster heads are so important. The proposed Clustering Algorithm considers the Battery Remaining, Number of Neighbors, Number of Members, and Stability in order to calculate the node's score with a linear algorithm. After each node calculates its … …Journal of Computer Science, Vol. 4, Issue 2 · 28 Feb 2008 · 7,114 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleReal-Time Simulation Method Using Monte Carlo and Clustering Algorithms: A Case Study Covering Drill Bit WearRodolfo Wilvert Reitz, Paulo José de Freitas FilhoMinimization of the cost of drilling an oil well is primarily achieved by reducing the operation completion time, which in turn can be achieved by increasing the Rate of Penetration (ROP). The ROP is the result of a combination of factors, such as lithological formation, operational parameters and bit wear. This paper addresses bit wear during drilling, using a method … …Journal of Computer Science, Vol. 14, Issue 2 · 27 Feb 2018 · 8,210 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDetecting Anomalies in IoT Using Intuitionistic Fuzzy Clustering AlgorithmsVijo Arul Selvi M., Fehmin Nadira Laskar, Fokrul Alom Mazarbhuiya et al.Intuitionistic Fuzzy Sets (IFS) are convenient ways to represent the vagueness and uncertainty inherent in any dataset. There are many uses of these. One such use is the Fuzzy C-Means (FCM) algorithm, which clusters the data objects into a pre-assigned (c) number of fuzzy clusters, which has been adopted in many fields, namely, pattern classification, anomaly detection, fraud identification, etc. … …Journal of Computer Science, Vol. 22, Issue 2 · 2 Mar 2026 · 1,600 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleGeometrical Approach to a New Hybrid Grid-Based Gravitational Clustering AlgorithmFaisal Bin Al Abid, A.N.M. Rezaul Karim, Golam Rahman ChowdhuryIn the past years, several clustering algorithms have been developed, for example, K-means, K-medoid. Most of these algorithms have the common problem of selecting the appropriate number of clusters and these algorithms are sensitive to noisy data and would cause less accurate clustering of the data set. Therefore, this paper introduces a new Hybrid Grid-based Gravitational Clustering Algorithm (HGGCA) geometrically, … …Journal of Computer Science, Vol. 17, Issue 3 · 9 Mar 2021 · 6,783 accessesView PDFCite