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262 results for “Clustering”
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Research ArticleOpen accessEvery word 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
Research ArticleOpen accessEvery word in the titleNewcastle Traffic Classification Using Clustering AlgorithmsHamad B Matar, Talal Almutairi, Nayef Z Al-MutairiThe urban road traffic network evolution is complex and varies depend on road type, zoning types and social activities. Typical traffic pattern variation of road network could be examined by considering the daily human travel activities. Thus, factor and cluster analysis is carried out. This paper is a comparative analysis of various Data Mining clustering methods for the grouping of … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 2 · 4 Apr 2020 · 7,214 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Hierarchical Clustering Approach for DBpedia based Contextual Information of TweetsVenkatesha Maravanthe, Prasanth Ganesh Rao, Anita Kanavalli et al.The past decade has seen a tremendous increase in the adoption of Social Web leading to the generation of enormous amount of user data every day. The constant stream of tweets with an innate complex sentimental and contextual nature makes searching for relevant information a herculean task. Multiple applications use Twitter for various domain sensitive and analytical use-cases. This paper … …Journal of Computer Science, Vol. 16, Issue 3 · 25 Mar 2020 · 7,246 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleModified ACS Centroid Memory for Data ClusteringAyad Mohammed Jabbar, Ku Ruhana Ku-Mahamud, Rafid SagbanAnt Colony Optimization (ACO) is a generic algorithm, which has been widely used in different application domains due to its simplicity and adaptiveness to different optimization problems. The key component that governs the search process in this algorithm is the management of its memory model. In contrast to other algorithms, ACO explicitly utilizes an adaptive memory, which is important to … …Journal of Computer Science, Vol. 15, Issue 10 · 11 Oct 2019 · 7,641 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Clustering based Approach for Contextual Anomaly Detection in Internet of ThingsDina ElMenshawy, Waleed Helmy, Neamat El-TaziInternet of Things (IoT) is a network which connects different communication devices with the internet to attain quick, robust and real-time information transfer and communication, achieving intelligent management. IoT is still in its infancy so it faces numerous challenges varying from data management to security concerns. Sensors generate enormous quantities of data that need to be handled efficiently to have … …Journal of Computer Science, Vol. 15, Issue 8 · 24 Aug 2019 · 7,582 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAutomatic Counting for Live and Dead Cells from Trypan Blue-Stained Images by Image Analysis Based on Adaptive K-Means ClusteringSu Mon Aung, Kanyanatt Kanokwiroon, Tonghathai Phairatana, Surapong ChatpunComputer-assisted image analysis can be employed to reduce the time consumed in the routine task such as cell counting. This study aimed to establish a method to perform this routine task based on an image analysis to automatically count live and dead cells after staining with trypan blue dye. Gray scale conversion and morphological operation were applied to the input … …Journal of Computer Science, Vol. 15, Issue 2 · 1 Mar 2019 · 8,566 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDirect Sequence and Frequency Hopping Signals Classification Based on Co-Occurrence Matrix and Clustering TechniquesHaidy S. Fouad, Hend A. Elsayed, Shawkat K. GirgisSpread Spectrum techniques (SS) were first developed for military applications, but currently, they have commercial applications. SS provides secure communication and allows multiple accesses for same radio spectrum. So, most Wireless Local Area Network (WLAN) systems use it, as do Cognitive Radios (CR), space systems and Global Positioning Systems (GPS). Direct Sequence Spread Spectrum (DSSS) and frequency hopped spread spectrum … …Journal of Computer Science, Vol. 15, Issue 1 · 10 Jan 2019 · 8,203 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Selection-based MCL Clustering Algorithm for Motif DiscoveryChunxiao Sun, Zhiyong Zhang, Jinglei Tang, Shuai LiuAs motif discovery plays an important role in the understanding of the relationship of gene regulation, this paper puts forward a selection-based MCL clustering refinement algorithm (SMCLR) aiming at solving the planted (l, d) motif search (PMS) problem. Firstly, we divide the DNA dataset into different subsets through selection of reference sequence and screen parts of eligible subsets by setting … …American Journal of Biochemistry and Biotechnology, Vol. 14, Issue 4 · 1 Jan 2019 · 8,827 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Better Approach to Ontology Integration using Clustering Through Global Similarity MeasureAshwin Makwana, Amit GanatraKnowledge representation is a crucial area of work in the intelligent system, especially in query answering system development. Ontology is used to represent shared knowledge of a particular domain for query answering system. Domain-specific ontology can be designed and developed by many groups and researchers, because of which there is heterogeneity in the knowledgebase. Ontology integration or merging is necessary … …Journal of Computer Science, Vol. 14, Issue 6 · 25 Jun 2018 · 8,227 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Elite Pool-Based Big Bang-Big Crunch Metaheuristic for Data ClusteringIbrahim Al-Marashdeh, Ghaith M. Jaradat, Masri Ayob et al.This paper delves into the capacity of enhanced Big Bang-Big Crunch (EBB-BC) metaheuristic to handle data clustering problems. BB-BC is a product of an evolution theory of the universe in physics and astronomy. Two main phases of BB-BC are big bang and big crunch. The big bang phase involves a creation of a population of random initial solutions, while in … …Journal of Computer Science, Vol. 14, Issue 12 · 19 Jun 2018 · 7,879 accessesView PDFCite