scholarly journals The Multi-Relational Skyline Operator

2007 ◽  
Author(s):  
Wen Jin ◽  
Martin Ester ◽  
Zengjian Hu ◽  
Jiawei Han
Keyword(s):  
Skyline Operator

scholarly journals The Skyline Operator for Selection of Virtual Machines in Mobile Computing

2018 ◽  
Vol 10 (11) ◽  
pp. 1-10
Author(s):  
Rasim M. Alguliyev ◽  
◽  
Ramiz M. Aliguliyev ◽  
Rashid G. Alakbarov ◽  
Oqtay R. Alakbarov
Keyword(s):  
Mobile Computing ◽  
Virtual Machines ◽  
Skyline Operator ◽  
Selection Of

An extended artificial bee colony with local search for solving the Skyline-based web services composition under interval QoS properties

2021 ◽  
pp. 1-16
Author(s):  
Ghizlane Khababa ◽  
Fateh Seghir ◽  
Sadik Bessou
Keyword(s):  
Web Services ◽  
Local Search ◽  
Artificial Bee Colony ◽  
Search Space ◽  
Evolutionary Strategy ◽  
Extended Version ◽  
The Public ◽  
Bee Colony ◽  
Skyline Operator ◽  
Experimental Comparisons

 In this paper, we introduce an extended version of artificial bee colony with a local search method (EABC) for solving the QoS uncertainty-aware web service composition (IQSC) problem, where the ambiguity of the QoS properties are represented using the interval-number model. At first, we formulate the addressed problem as an interval constrained single-objective optimization model. Then, we use the skyline operator to prune the redundant and dominated web services from their sets of functionally equivalent ones. Whereas, EABC is employed to solve the IQSC problem in a reduced search space more effectively and more efficiently. For the purpose of validation of the performance and the efficiency of the proposed approach, we present the experimental comparisons to an existing skyline-based PSO, an efficient discrete gbest-guided artificial bee colony and a recently provided Harris Hawks optimization with an elite evolutionary strategy algorithms on an interval extended version of the public QWS dataset.

A New Progressive Method for Computing Skyline Queries

2017 ◽  
Vol 10 (3) ◽  
pp. 1-21
Author(s):  
Zekri Lougmiri
Keyword(s):  
Decision Making ◽  
Divide And Conquer ◽  
Progressive Method ◽  
Skyline Queries ◽  
Numerical Attributes ◽  
Divide And Conquer Algorithm ◽  
Skyline Operator ◽  
Synthetic Datasets

Skyline queries are important in many fields, especially for decision making. In this context, objects or tuples of databases are defined according to some numerical and non numerical attributes. The skyline operator acts on the numerical ones. The algorithms that implements this skyline operator are genrally of progressive or non progressive. The progressive ones return the skyline operator during its execution while non preogressive alogrithms return the result at the end of its execution. This paper presents a new progressive algorithm for computing the skyline points. This algorithm is based on sorting as a preprocessing of the input. The authors present new theorems for deducing promptly the first skyline points and reducing the candidate space. A new version of Divide-and-Conquer algorithm is used for computing the final skyline. Intensive experimentations on both real and synthetic datasets show that our algorithm presents best performance comparatively to other methods.

scholarly journals General Spatial Skyline Operator

2012 ◽  
pp. 494-508 ◽  
Author(s):  
Qianlu Lin ◽  
Ying Zhang ◽  
Wenjie Zhang ◽  
Aiping Li
Keyword(s):  
Skyline Operator ◽  
Spatial Skyline

SkySlide: A Hybrid Method for Landslide Susceptibility Assessment based on Landslide-Occurring Data Only

2020 ◽  
Author(s):  
Alev Mutlu ◽  
Furkan Goz
Keyword(s):  
Hybrid Method ◽  
Landslide Susceptibility ◽  
Performance Metrics ◽  
Geometric Mean ◽  
Imbalanced Data ◽  
Majority Voting ◽  
Support Vector ◽  
Susceptibility Assessment ◽  
Landslide Susceptibility Assessment ◽  
Skyline Operator

Abstract Landslide susceptibility assessment is the problem of determining the likelihood of a landslide occurrence in a particular area with respect to the geographical and morphological properties of the area. This paper presents a hybrid method, namely SkySlide, that incorporates clustering, skyline operator, classification and majority voting principle for region-scale landslide susceptibility assessment. Clustering and skyline operator are utilized to model landslides while classification and majority voting principle are utilized to assess landslide susceptibility. The contribution of the study is 2-fold. First, the proposed method requires properties of landslide-occurring data only to model landslides. Second, the proposed method is evaluated on imbalanced data and experimental results include performance metrics of imbalanced data. Experiments conducted on two real-life datasets show that clustering greatly improves performance of SkySlide. Experiments further demonstrate that SkySlide achieves higher class balance accuracy, Matthews correlation coefficient, geometric mean and bookmaker informedness scores compared with the most commonly used methods for landslide susceptibility assessment such as support vector machines, logistic regression and decision trees.

Skyline Operator over Tripadvisor Reviews Within the Belief Functions Framework

2017 ◽  
pp. 186-197 ◽  
Author(s):  
Fatma Ezzahra Bousnina ◽  
Sayda Elmi ◽  
Mouna Chebbah ◽  
Mohamed Anis Bach Tobji ◽  
Allel HadjAli ◽  
...  
Keyword(s):  
Belief Functions ◽  
Skyline Operator

Probabilistic skyline operator over sliding windows

2013 ◽  
Vol 38 (8) ◽  
pp. 1212-1233 ◽  
Author(s):  
Wenjie Zhang ◽  
Xuemin Lin ◽  
Ying Zhang ◽  
Wei Wang ◽  
Gaoping Zhu ◽  
...  
Keyword(s):  
Sliding Windows ◽  
Skyline Operator ◽  
Probabilistic Skyline
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