Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

156 results for “Data Clustering”
Set a search alert
Research ArticleOpen accessIn the abstractUtility Independent Privacy Preserving Data Mining on Vertically Partitioned DataE. Poovammal, M. PonnavaikkoProblem statement: Driven by mutual benefits, or by regulations that require certain data to be published, there has been a demand for the exchange and publication of data among various parties. Data publishing has been ubiquitous in many domains such as medical, business and education. Detailed person-specific data, present in the centralized server or in the distributed environment, in its … …Journal of Computer Science, Vol. 5, Issue 9 · 30 Sep 2009 · 6,841 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiscretization Numerical Data for Relational Data with One-to-Many RelationsRayner AlfredProblem statement: Handling numerical data stored in a relational database has been performed differently from handling those numerical data stored in a single table due to the multiple occurrences (one-to-many association) of an individual record in the non-target table and non-determinate relations between tables. Numbers in Multi-Relational Data Mining (MRDM) were often discretized, after considering the schema of the relational … …Journal of Computer Science, Vol. 5, Issue 7 · 31 Jul 2009 · 7,031 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe 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 · 7,103 accessesView PDFCite
Research ArticleOpen accessIn the abstractNew 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 · 7,440 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn Studying Spatial Patterns and Association Between these Patterns of Mortality and Prosperity in MalaysiaFaisal G. Khamis, Abdul Aziz Jemain, Kamarulzaman IbrahimIn this study, we examined the geographical distribution (the spatial structure) of mortality and prosperity in Malaysia. In addition we proposed an approach to investigate the association between clustering patterns of mortality and prosperity across different areas of the country. To characterize the geographic pattern of mortality and prosperity, three indicators (infant, neonatal, and stillbirth) were proposed for mortality and … …American Journal of Applied Sciences, Vol. 5, Issue 7 · 31 Jul 2008 · 6,936 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving Quality of Clustering using Cellular Automata for Information retrievalP. K. Sree, G. V.S. Raju, I. R. Babu, S. V. RajuClustering has been widely applied to Information Retrieval (IR) on the grounds of its potential improved effectiveness over inverted file search. Clustering is a mostly unsupervised procedure and the majority of the clustering algorithms depend on certain assumptions in order to define the subgroups present in a data set .A clustering quality measure is a function that, given a data … …Journal of Computer Science, Vol. 4, Issue 2 · 28 Feb 2008 · 7,038 accessesView PDFCite
Research ArticleOpen accessIn the abstractFeature Selection in Data-Mining for Genetics Using Genetic AlgorithmV. N. Rajavarman, S. P. RajagopalanWe discovered genetic features and environmental factors which were involved in multifactorial diseases. To exploit the massive data obtained from the experiments conducted at the General Hospital, Chennai, data mining tools were required and we proposed a 2-Phase approach using a specific genetic algorithm. This heuristic approach had been chosen as the number of features to consider was large (upto … …Journal of Computer Science, Vol. 3, Issue 9 · 30 Sep 2007 · 6,630 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Physical Organization of R-Trees Using Node ClusteringF. Sagayaraj Francis, P. ThambiduraiR-Tree is a multidimensional indexing structure that forms basis for all the multidimensional indexing structures based on data partitioning. A number of attempts have been made in the past to improve the performance of R-Tree by manipulating the tree parameters and the data parameters. But hardly any attempt had been made to use external parameters such as disk parameters to … …Journal of Computer Science, Vol. 3, Issue 7 · 31 Jul 2007 · 6,628 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Classification Method Based on Data DecompositionAyman E. Khedr, Amira M. Idrees, Ahmed I. El SeddawyKnowledge discovery is one of the vital fields which strongly supports decision making by applying different techniques based on the targeted field and the required information. Focusing on clustering and classification techniques, this paper presents an approach for adapting one of the classification algorithms for supporting decision making procedure in radiology data analysis field. The proposed adaptation is based on … …Journal of Computer Science, Vol. 12, Issue 1 · 20 Feb 2016 · 7,426 accessesView PDFCite
Research ArticleOpen accessIn the abstractObservation Modeling for Continuous Predicting Global and Diffuse Solar Radiation on Horizontal SurfaceSomporn Hongkong, Singthong PattanasethanonMathematical modeling for continuous prediction of solar energy is inevitable for energy systems. General, existing models are mostly empirical and data dependent. This article has to present a variable model for predicting global and diffuse solar radiation on the horizontal plane. The model considered in this study has applied Hidden Markov Model (HMM) with two observations. The databases were measured … …American Journal of Environmental Sciences, Vol. 9, Issue 3 · 23 May 2013 · 6,799 accessesView PDFCite