Search Results - (( java implementation clustering algorithm ) OR ( based information data algorithm ))
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Thesis -
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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4
A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Final Year Project / Dissertation / Thesis -
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Conference or Workshop Item -
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MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data
Published 2014“…This research proposes mean gain ratio (MGR), a new information theory based hierarchical divisive clustering algorithm for categorical data. …”
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An adaptive density-based method for clustering evolving data streams / Amineh Amini
Published 2014“…This study proposes a density-based algorithm for clustering evolving data streams. …”
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11
An intelligent data mapping for hydrological information system (his) cube data base to cater from various data types
Published 2004“…In this research, ontology based information extraction used hydrological data from Jabatan Pengairan dan Saliran (JPS) as the case study. …”
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Monograph -
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HAPTIC VISUALIZATION USING VISUAL TEXTURE INFORMATION
Published 2011“…Wavelet decomposition is utilized to extract data information from texture data. In searching process, the data are retrieved based on data distribution. …”
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13
DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Final Year Project -
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A buffer-based online clustering for evolving data stream
Published 2019“…In this study, we present a fully online density-based clustering algorithm called buffer-based online clustering for evolving data stream (BOCEDS). …”
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Pengekstrakan data berasaskan pendekatan ontologi: kes data jujukan hidrologi
Published 2005“…In this research, ontology based information extraction used hydrological data from Jabatan Pengairan dan Saliran (JPS) as the case study. …”
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Propositional satisfiability algorithm to find minimal reducts for data mining
Published 2002“…An algorithm in finding minimal reducts based on Prepositional Satisfiability (SAT) algorithm is proposed. …”
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A Data Mining Approach to Construct Graduates Employability Model in Malaysia
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A Multi-Criteria Recommendation Technique for Personalized Tourism Experiences
Published 2025“…Recommendation systems use algorithms to analyze user data and provide personalized recommendations based on their past behaviour and preferences. …”
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20
Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Classification is a process of grouping or placing data into appropriate categories or classes based on specificattributes or features to predict labels or classes of new data based on patternsobserved from previously trained data. …”
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