Search Results - (( java application optimisation algorithm ) OR ( based representation clustering algorithm ))
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USING LATENT SEMANTIC INDEXING FOR DOCUMENT CLUSTERING
Published 2010“…Based on the new representation, the documents are then subjected to the clustering algorithm itself, which is Fuzzy c-Means algorithm. …”
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Evaluation of Visual Network Algorithms on Historical Documents
Published 2020“…The evaluation found that FA2 algorithm when combined with MC algorithm produce the best network representation for SAGA. …”
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A Comparative Study Of Fuzzy C-Means And K-Means Clustering Techniques
Published 2014“…First we present an overview of both methods with emphasis on the implementation of the algorithm. Then, we apply six datasets to measure the quality of clustering result based on the similarity measure used in the algorithm and its representation of clustering result. …”
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Development of a parallel clustering of bilingual corpora based on reduced terms
Published 2015“…Document clustering is a process that groups a set of documents based on their similarities. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…Nature-inspired optimization-based clustering techniques are powerful, robust and more sophisticated than the conventional clustering methods due to their stochastic and heuristic characteristics. …”
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High performance in minimizing of term-document matrix representation for document clustering
Published 2009“…By using various numbers of patterns (rank) of SVD, the proposed method is applied to cluster documents using the Fuzzy C-Means algorithm. …”
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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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Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing
Published 2017“…Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. …”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
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Depth Image Layers Separation (DILS) algorithm of image view synthesis based on stereo vision
Published 2013“…A new Depth Image Layers Separation (DILS) algorithm for synthesizing inter-view images based on disparity depth map layers representation is presented. …”
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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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Optimized feature construction methods for data summarizations of relational data
Published 2014“…DARA transforms the data relational representation into a vector space representation and a clustering process is applied to group the data based on their characteristics similarity. …”
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A deep autoencoder-based representation for Arabic text categorization
Published 2020“…To overcome these shortcomings, we proposed a deep Autoencoder based representation for Arabic text categorization. …”
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k-nearest neighbour using ensemble clustering based on feature selection approach to learning relational data
Published 2016“…However, DARA suffers a major drawback when the cardinalities of attributes are very high because the size of the vector space representation depends on the number of unique values that exist for all attributes in the dataset.A feature selection process can be introduced to overcome this problem.These selected features can be further optimized to achieve a good classification result.Several clustering runs can be performed for different values of k to yield an ensemble of clustering results. …”
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…First, this study combines SPM with Sentence Scoring method as feature-based approach and Bellman-Ford algorithm as graph-based to validate the performance of SPM. …”
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A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization
Published 2017“…The thesis main objective is to develop a new framework for social- and knowledge-based coalition formation (SKCF). The related sub-objectives are: 1) to define coalition and social factors to form a coalition formation model, 2) to develop a knowledge representation scheme to store knowledge of formed coalitions, and 3) to develop an effective algorithm to optimize the coalition which can also be treated as a clustering problem. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…In order to establish an efficient mapping between the particle’s position in the continuous MOPSO and the scheduling solution in the JSP, this research proposes the JSP to be adopted within a discrete MOPSO through a modified solution representation using the permutation-based representation and a modified setup of the particle’s position and velocity. …”
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