Search Results - (( model validation learning algorithm ) OR ( based information clustering algorithm ))*
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
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A hybrid approach for personalized news recommendation with ordered clustering algorithm, rich user and news metadata
Published 2019“…A new model in news selection is proposed based on sub-modularity model. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi
Published 2019“…Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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Time series modeling of water level at Sulaiman Station, Klang River, Malaysia
Published 2010“…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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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“…A new multi density-based clustering method forms final clusters using both summarized synopsis information and statistical information. …”
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Adaptive firefly algorithm for hierarchical text clustering
Published 2016“…In this research, an adaptive hierarchical text clustering algorithm is proposed based on Firefly Algorithm. …”
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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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USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING
Published 2010“…Therefore, the document clustering based on the same category is important to help users to retrieve information they need. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…In this study, a fully online density-based clustering algorithm called Buffer-based Online Clustering for Evolving Data Stream (BOCEDS) is presented. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
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MuDi-Stream: A multi density clustering algorithm for evolving data stream
Published 2016“…The offline phase generates the final clusters using an adapted density-based clustering algorithm. …”
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Document clustering based on firefly algorithm
Published 2015“…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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Energy Efficient Technique for Cluster Head Selection and Data gathering in Wireless Sensor Network
Published 2008“…Cluster head send the energy level and distance information of each node to base station (BS).Base station selects the cluster-head dynamically on the basis of energy level and distance. …”
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Conference or Workshop Item -
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An Improved Genetic Clustering Algorithm for Categorical Data
Published 2013“….: G-ANMI: A mutual information based genetic clustering algorithm for categorical data, Knowledge-Based Systems 23, 144–149(2010)] proposed a mutual information based genetic clustering algorithm named G-ANMI for categorical data. …”
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