Search Results - (( based streaming mining algorithm ) OR ( java implication based algorithm ))
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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction
Published 2024“…Lately, a fully online buffer-based clustering algorithm for handling evolving data streams (BOCEDS) was developed. …”
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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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Dominance analyses reduction in skyline query processing over data stream with data mining technique
Published 2025“…DAR employs the Apriori algorithm, one of the most prevalent data mining algorithms, to identify the frequently occurring dominance analyses. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…Data stream clustering plays an important role in data stream mining for knowledge extraction. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…In the online phase, the stream clustering algorithm for trajectories based on the lifespan of the cluster is proposed (CC_TRS) to overcome the limitations of the time window technique. …”
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A review on data stream classification
Published 2018“…This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.…”
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A Review on Data Stream Classification
Published 2018“…This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.…”
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets
Published 2021“…Therefore, this research proposed an improved pheromone- based PKSOM algorithm known as iPKSOM to solve the mentioned problem. …”
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Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining
Published 2023“…Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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Efficient and effective automated surveillance agents using kernel tricks
Published 2012“…Kernel machines provide a powerful data mining technique that may be used for pattern matching in the presence of complex data. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis
