How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation حسب Joni Salminen (7434770)

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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering حسب Abu Zitar, Raed

"…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …"

K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation حسب Ashhadul Islam (16869981)

"…This paper introduces K Nearest Neighbor OveRsampling (KNNOR) Algorithm — a novel data augmentation technique that considers the distribution of data and takes into account the k nearest neighbors while generating artificial data points. …"

Oversampling techniques for imbalanced data in regression حسب Samir Brahim Belhaouari (9427347)

"…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …"

Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units حسب Shanableh, Tamer

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A Tabu Search algorithm for mapping data to multicomputers. (c1997) حسب Diab, Kamal M.

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A genetic algorithm for testable data path synthesis حسب Harmanani, H.

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A neural networks algorithm for data path synthesis حسب Harmanani, Haidar M.

"…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …"
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Allocating data to distributed-memory multiprocessors by genetic algorithms حسب Mansour, Nashat

"…We present three genetic algorithms (GAs) for allocating irregular data sets to multiprocessors. …"
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Distributed dimension reduction algorithms for widely dispersed data حسب Abu-Khzam, F.N.

"…It runs in linear time and requires very little data transmission. A series of experiments is conducted to gauge how the algorithm’s emphasis on minimal data transmission affects solution quality. …"
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Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem حسب Assaker, Guy

"…The research note is presented in two parts: Part A presents an overview of REBUS, including its development, algorithm, and its primary functions. …"
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Data damage assessment and recovery algorithm from malicious attacks in healthcare data sharing systems حسب Haraty, Ramzi A.

"…In this paper, we present an efficient data damage assessment and recovery algorithm to delete malicious transactions and recover affected transactions in a data source in a health care system based on the concept of the matrix. …"
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Public health utility of cause of death data: applying empirical algorithms to improve data quality حسب Sarah Charlotte Johnson (9715415)

Physical optimization algorithms for mapping data to distributed-memory multiprocessors حسب Mansour, Nashat

"…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …"
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Parallel physical optimization algorithms for allocating data to multicomputer nodes حسب Mansour, Nashat

"…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …"
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Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994) حسب Kawash, Jalal Y.

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An enhanced k-means clustering algorithm for pattern discovery in healthcare data حسب Haraty, Ramzi A.

"…This paper studies data mining applications in healthcare. Mainly, we study k-means clustering algorithms on large datasets and present an enhancement to k-means clustering, which requires k or a lesser number of passes to a dataset. …"
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data حسب Assaf, Ali

"…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …"
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KNNOR: An oversampling technique for imbalanced datasets حسب Ashhadul Islam (16869981)

"…The proposed technique called K-Nearest Neighbor OveRsampling approach (KNNOR) performs a three step process to identify the critical and safe areas for augmentation and generate synthetic data points of the minority class. …"

On the steiner walk problem. (c2009) حسب Maarouf, Amina

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