Search Results - (( java implication drops algorithm ) OR ( knowledge extraction clustering algorithm ))

A buffer-based online clustering for evolving data stream by Islam, Md. Kamrul, Ahmed, Md. Manjur, Kamal Z., Zamli

“…Data stream clustering plays an important role in data stream mining for knowledge extraction. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning by Islam, Md Kamrul

“…Data stream clustering plays an important role in data stream mining for knowledge extraction. …”
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An efficient fuzzy C-least median clustering algorithm by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Aboosalih, K C

“…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 by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

“…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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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering by Rahmah, Mokhtar, Raza, Muhammad Ahsan, Fauziah, Zainuddin, Nor Azhar, Ahmad, Raza, Muhammad Fahad, Raza, Binish

“…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 by Alkawsi G., Al-amri R., Baashar Y., Ghorashi S., Alabdulkreem E., Kiong Tiong S.

“…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. …”

Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan by Aznan, Muhammad Nur Syazwanie Aznan

“…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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Clustering Student Performance Data Using k-Means Algorithms by Sultan Alalawi, Sultan Juma, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

“…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 by Fawzia Omer, A., Mohammed, H.A., Awadallah, M.A., Khan, Z., Abrar, S.U., Shah, M.D.

“…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 by Khalilian, Madjid, Mustapha, Norwati, Sulaiman, Nasir

“…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 by Chong, Chun Yong

“…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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Fruity vegetable recognition system using Color Histogram and BRISK features extraction / Siti Hajar Mohd Nasri by Mohd Nasri, Siti Hajar

“…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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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…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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Out-of-core simplification with appearance preservation for computer game applications by Tan, Kim Heok

“…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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Out-of-core simplification with appearance preservation for computer game applications by Bade, Abdullah, Daman, Daut, Sunar, Mohd. Shahrizal, Tan , Kim Heok

“…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 by Ismail, Nor Anita Fairos, Daman, Daut, Mohd. Rahim, Mohd. Shafry

“…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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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

“…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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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems by Franco, Daniel Jose Da Graca Peceguina

“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…Data mining is known as the process of detection concerning patterns from essential amounts of data. As a process of knowledge discovery. Classification is a data analysis that extracts a model which describes an important data classes. …”
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