Search Results - (( developing learning graph algorithm ) OR ( java implementation mining algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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2
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Scalable approach for mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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4
Mining association rules from structured XML data
Published 2009“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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5
A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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The application of suitable sports games for junior high school students based on deep learning and artificial intelligence
Published 2025“…This study intends to develop a Spatial Temporal-Graph Convolutional Network (ST-GCN) action detection algorithm based on the MediaPipe framework. …”
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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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Optimizing kindergarten schedule using : graph coloring / Nur Nabilah Salleh Muner
Published 2019“…It provides platform for developing early childhood education that combines learning with play. …”
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10
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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11
An improved directed random walk framework for cancer classification using gene expression data
Published 2020“…From the perspective of computing, an algorithm is developed to ease the diagnosis process, but the feasibility is not reliable. …”
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Industry 5.0 and Education 5.0: Transforming Vocational Education through Intelligent Technology
Published 2024“…By analyzing the research gaps in personalized learning paths, emotion-driven learning, crossdisciplinary integration, and long-term learning behavior analysis, the paper proposes four improved algorithms: the adaptive learning path generation algorithm, the emotion-driven personalized learning algorithm, the cross-disciplinary knowledge graph algorithm, and the long-term learning behavior prediction algorithm. …”
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A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition
Published 2010“…Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. …”
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Bipartite graph approach to course timetabling problems / Hafizah A Razak
Published 2009“…The prototype is design using constructive heuristic algorithm and colouring the edge of two bipartite graphs. …”
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Interactive learning package for artificial neural network (Demonstration Module) / Camellia Mohd Kamal
Published 2004“…Interactive Learning Package for Artificial Neural Network (Demonstration Module) is a learning package that allow the users to learn and enhance the understanding of the ANN subject in more detailed way and apply in the demonstration parts. …”
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Development of deep reinforcement learning based resource allocation techniques in cloud radio access network
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CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning
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Prediction of customer churn for ABC Multistate Bank using machine learning algorithms / Hui Shan Hon ... [et al.]
Published 2023“…The purpose of this study is to apply machine learning algorithms to develop the most effective model for predicting bank customer churn. …”
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