Modeling and Computing Probabilistic Skyline on Incomplete Data

2020 ◽  
Vol 32 (7) ◽  
pp. 1405-1418 ◽  
Author(s):  
Kaiqi Zhang ◽  
Hong Gao ◽  
Xixian Han ◽  
Zhipeng Cai ◽  
Jianzhong Li
Keyword(s):  
Incomplete Data ◽  
Probabilistic Skyline

Corrigendum to “Bayesian test for asymmetry and nonstationarity in MTAR model with possibly incomplete data”

2006 ◽  
Vol 50 (2) ◽  
pp. 584
Author(s):  
Soo Jung Park ◽  
Dong Wan Shin ◽  
Byeong Uk Park ◽  
Woo Chul Kim ◽  
Man-Suk Oh
Keyword(s):  
Incomplete Data ◽  
Bayesian Test

Continuous Probabilistic Skyline Query for Secure Worker Selection in Mobile Crowdsensing

2021 ◽  
pp. 1-1
Author(s):  
Xichen Zhang ◽  
Rongxing Lu ◽  
Jun Shao ◽  
Hui Zhu ◽  
Ali A. Ghorbani
Keyword(s):  
Skyline Query ◽  
Mobile Crowdsensing ◽  
Worker Selection ◽  
Probabilistic Skyline

scholarly journals A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 786
Author(s):  
Yenny Villuendas-Rey ◽  
Eley Barroso-Cubas ◽  
Oscar Camacho-Nieto ◽  
Cornelio Yáñez-Márquez
Keyword(s):  
Swarm Intelligence ◽  
Data Clustering ◽  
Incomplete Data ◽  
Missing Values ◽  
Clustering Algorithms ◽  
Bat Algorithm ◽  
Hybrid Features ◽  
Bee Colony ◽  
Learning Tasks ◽  
Clustering Data

Swarm intelligence has appeared as an active field for solving numerous machine-learning tasks. In this paper, we address the problem of clustering data with missing values, where the patterns are described by mixed (or hybrid) features. We introduce a generic modification to three swarm intelligence algorithms (Artificial Bee Colony, Firefly Algorithm, and Novel Bat Algorithm). We experimentally obtain the adequate values of the parameters for these three modified algorithms, with the purpose of applying them in the clustering task. We also provide an unbiased comparison among several metaheuristics based clustering algorithms, concluding that the clusters obtained by our proposals are highly representative of the “natural structure” of data.

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