Spatial skyline queries over incomplete data for smart cities

2018 ◽  
Vol 90 ◽  
pp. 1-14 ◽  
Author(s):  
Sayda Elmi ◽  
Jun-Ki Min
Keyword(s):  
Incomplete Data ◽  
Smart Cities ◽  
Skyline Queries ◽  
Spatial Skyline

scholarly journals SCSA: Evaluating skyline queries in incomplete data

2018 ◽  
Vol 49 (5) ◽  
pp. 1636-1657 ◽  
Author(s):  
Yonis Gulzar ◽  
Ali A. Alwan ◽  
Radhwan Mohamed Abdullah ◽  
Qin Xin ◽  
Marwa B. Swidan
Keyword(s):  
Incomplete Data ◽  
Skyline Queries

Answering Skyline Queries over Incomplete Data with Crowdsourcing

2019 ◽  
pp. 1-1
Author(s):  
Xiaoye Miao ◽  
Yunjun Gao ◽  
Su Guo ◽  
Lu Chen ◽  
Jianwei Yin ◽  
...  
Keyword(s):  
Incomplete Data ◽  
Skyline Queries

Nearest and farthest spatial skyline queries under multiplicative weighted Euclidean distances

2020 ◽  
Vol 192 ◽  
pp. 105299 ◽  
Author(s):  
Marta Fort ◽  
J. Antoni Sellarès ◽  
Nacho Valladares
Keyword(s):  
Skyline Queries ◽  
Euclidean Distances ◽  
Spatial Skyline

k -dominant skyline queries on incomplete data

2016 ◽  
Vol 367-368 ◽  
pp. 990-1011 ◽  
Author(s):  
Xiaoye Miao ◽  
Yunjun Gao ◽  
Gang Chen ◽  
Tianyi Zhang
Keyword(s):  
Incomplete Data ◽  
Skyline Queries

C2S

2015 ◽  
pp. 294-324
Author(s):  
Marlene Goncalves ◽  
Fabiola Di Bartolo
Keyword(s):  
Experimental Study ◽  
State Of The Art ◽  
Skyline Query ◽  
Skyline Queries ◽  
Multiple User ◽  
Data Points ◽  
Special Case ◽  
Spatial Skyline

Skyline queries may be used to filter interesting data from a broad range of data. A Skyline query selects those data that are the best according to multiple user-defined criteria. A special case of Skyline queries are the Spatial Skyline Queries (SSQ). SSQ allow users to express preferences on the closeness between a set of data points and a set of query points. We study the problem of answering SSQ in presence of changing data, i.e., data whose values regularly change over a period of time. In this chapter, it is proposed an algorithm to evaluate SSQ on changing data. The proposed algorithm is able to avoid recomputation of the whole Skyline with each update on the data. Also, the performance of the proposed algorithm against state-of-the-art algorithms was empirically studied. The experimental study shows that the proposed algorithm may become 3 times faster than state-of-the-art algorithms.

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