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Parallel scatter search algorithms for exam timetabling. (c2009)
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…Additionally, it was able to identify several differentiable regions in the real data set and on different chromosomes. However, we noticed that chromosomes 1, 3 and 6 had the highest occurrence rate of differentiable motifs (9, 8 and 6 motifs respectively). …”
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Efficient Approximate Conformance Checking Using Trie Data Structures
Published 2021“…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities
Published 2021“…The results indicate that KNSGA-II is superior to other algorithms. Also, a case study in Iran is implemented and the related results are analyzed.…”
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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…The proposed algorithm has successfully maintained homogeneity to the original data set, reduced the execution time and occupied storage space, and led to decent monitoring performance.…”
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On the complexity of multi-parameterized cluster editing
Published 2017“…In other words, Cluster Editing can be solved efficiently when the number of false positives/negatives per single data element is expected to be small compared to the minimum cluster size. …”
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A TABU SEARCH APPROACH TO THE CLUSTERING PROBLEM
Published 2020“…The problem is a nonconvex program that has many local minima. It has been studied by many researchers and the most well-known algorithm for solving it is the k-means algorithm. …”
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Auto-indexing Arabic texts based on association rule data mining. (c2015)
Published 2015“…Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. The model uses the Apriori Algorithm - an association rule algorithm for extracting frequent sets containing related items - to extract relations between words in the texts to be indexed with words from texts that belong to the same category. …”
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Three-phase approach for curriculum-based course timetabling problem. (c2012)
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Scalable parallel algorithms for dynamic programming on tree decomposition. (c2017)
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Methodology for Analyzing the Traditional Algorithms Performance of User Reviews Using Machine Learning Techniques
Published 2020“…This conclusion was achieved after preprocessing a number of data values from these data sets.</p><h2>Other Information</h2><p dir="ltr">Published in: Algorithms<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/a13080202" target="_blank">https://dx.doi.org/10.3390/a13080202</a></p>…”
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Clustering records in information retrieval systems. (c1995)
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Improving Rule Set Based Software Quality Prediction
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A decentralized load balancing strategy for parallel search-three optimization. (c2010)
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masterThesis -
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Topics in graph algorithms
Published 2003“…This is achieved by implementing some algorithms for the vertex cover problem, and conducting experiments on real data sets. …”
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