Search Results - (( knowledge extraction clustering algorithm ) OR ( java application optimisation algorithm ))
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1
A buffer-based online clustering for evolving data stream
Published 2019“…Data stream clustering plays an important role in data stream mining for knowledge extraction. …”
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2
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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3
An efficient fuzzy C-least median clustering algorithm
Published 2021“…In this paper we are discussing our new procedure for clustering called Fuzzy C-least median of squares algorithm which is an improvement to Fuzzy C-means (FCM) algorithm. …”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase
Published 2004“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering
Published 2021“…In the field of computer science, data mining facilitates the extraction of useful knowledge and patterns from a huge amount of data. …”
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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction
Published 2024“…In a world of connectivity empowered by the advancement of the Internet of Things (IoT), an infinite number of data streams have emerged. Thus, data stream clustering is crucial for extracting hidden knowledge and data mining. …”
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Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan
Published 2019“…Even though, there is a tool for clustering, some of this tool required an expert knowledge in clustering in order to understand the results. …”
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10
Clustering Student Performance Data Using k-Means Algorithms
Published 2023“…The research approach known as educational data mining (EDM) focuses on using data mining techniques to extract massive data from the educational context and transform it into knowledge that can improve educational systems and decisions. …”
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Big Data Mining Using K-Means and DBSCAN Clustering Techniques
Published 2022“…The density-based spatial clustering of applications with noise (DBSCAN) and the K-means algorithm were used to develop clustering algorithms. …”
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Data stream clustering by divide and conquer approach based on vector model
Published 2016“…The continuous effort on data stream clustering method has one common goal which is to achieve an accurate clustering algorithm. …”
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Constrained clustering approach to aid in remodularisation of object-oriented software systems / Chong Chun Yong
Published 2016“…These practical concerns have led the researcher to propose the idea of integrating domain knowledge into traditional unsupervised clustering algorithms, herewith referred as constrained clustering, a semi-supervised clustering technique where domain experts can explicitly exert their opinions in the form of explicit clustering constraints to restrict whether a pair of software components should or should not be clustered into the same subsystem. …”
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14
Fruity vegetable recognition system using Color Histogram and BRISK features extraction / Siti Hajar Mohd Nasri
Published 2016“…This project proposed to use Color Histogram as color feature and Binary Robust Invariant Scalable Keypoints (BRISK) features extraction as one of ways to overcome the problem. In process to extract the two main features, K-means clustering algorithm is used as background subtraction method with combination of Canny’s Edge Detection and Mathematical Morphology Operation for shape extraction. …”
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15
Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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16
Out-of-core simplification with appearance preservation for computer game applications
Published 2006“…Unlike any other vertex clustering methods, the knowledge of neighbourhood between nodes is unnecessary and the node simplification is performed independently. …”
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17
Out-of-core simplification with appearance preservation for computer game applications
Published 2006“…Unlike any other vertex clustering methods, the knowledge of neighbourhood between nodes is unnecessary and the node simplification is performed independently. …”
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The development of level of detail (LOD) technique in 3D computer graphics application
Published 2009“…Unlike any other vertex clustering methods, the knowledge of neighbourhood between nodes is unnecessary and the node simplification is performed independently. …”
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Monograph -
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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20
Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…In response to the current issues of poor real-time performance, high computational costs, and excessive memory usage of object detection algorithms based on deep convolutional neural networks in embedded devices, a method for improving deep convolutional neural networks based on model compression and knowledge distillation is proposed. …”
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