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

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

scholarly journals A Model for Processing Skyline Queries in Crowd-sourced Databases

2018 ◽  
Vol 10 (2) ◽  
pp. 798 ◽  
Author(s):  
Marwa B. Swidan ◽  
Ali A. Alwan ◽  
Sherzod Turaev ◽  
Yonis Gulzar
Keyword(s):  
Cognitive Abilities ◽  
Incomplete Data ◽  
Missing Values ◽  
Main Idea ◽  
Crowd Sourcing ◽  
New Paradigm ◽  
Skyline Queries ◽  
Proposed Model ◽  
Worker Selection ◽  
High Quality Result

Nowadays, in most of the modern database applications, lots of critical queries and tasks cannot be completely addressed by machine. Crowd-sourcing database has become a new paradigm for harness human cognitive abilities to process these computer hard tasks. In particular, those problems  that are difficult for machines but easier for humans can be solved better than ever, such as entity resolution, fuzzy matching for predicates and joins, and image recognition. Additionally, crowd-sourcing database allows performing database operators on incomplete data as human workers can be involved to provide estimated values during run-time. Skyline queries which received formidable attention by database community in the last decade, and exploited in a variety of applications such as multi-criteria decision making and decision support systems. Various works have been accomplished address the issues of skyline query in crowd-sourcing database. This includes a database with full and partial complete data. However, we argue that processing skyline queries with partial incomplete data in crowd-sourcing database has not received an appropriate attention. Therefore, an efficient approach processing skyline queries with partial incomplete data in crowd-sourcing database is needed. This paper attempts to present an efficient model tackling the issue of processing skyline queries in incomplete crowd-sourcing database. The main idea of the proposed model is exploiting the available data in the database to estimate the missing values. Besides, the model tries to explore the crowd-sourced database in order to provide more accurate results, when local database failed to provide precise values. In order to ensure high quality result could be obtained, certain factors should be considered for worker selection to carry out the task such as workers quality and the monetary cost. Other critical factors should be considered such as time latency to generate the results.

Processing k-skyband, constrained skyline, and group-by skyline queries on incomplete data

2014 ◽  
Vol 41 (10) ◽  
pp. 4959-4974 ◽  
Author(s):  
Yunjun Gao ◽  
Xiaoye Miao ◽  
Huiyong Cui ◽  
Gang Chen ◽  
Qing Li
Keyword(s):  
Incomplete Data ◽  
Skyline Queries

scholarly journals IDENTIFYING SKYLINES IN CLOUD DATABASES WITH INCOMPLETE DATA

2018 ◽  
Author(s):  
Yonis Gulzar ◽  
Ali Amer Alwan Aljuboori ◽  
Norsaremah Salleh ◽  
Imad Fakhri Al Shaikhli
Keyword(s):  
Incomplete Data ◽  
Data Transfer ◽  
Real Life ◽  
Database Systems ◽  
Personalized Recommendation ◽  
Skyline Queries ◽  
Sorting Technique ◽  
Cloud Databases ◽  
Filtering Technique ◽  
Prohibitive Cost

Skyline queries is a rich area of research in the database community. Due to its great benefits, it has been integrated into many database applications including but not limited to personalized recommendation, multi-objective, decision support and decision-making systems. Many variations of skyline technique have been proposed in the literature addressing the issue of handling skyline queries in incomplete database. Nevertheless, these solutions are designed to fit with centralized incomplete database single access. However, in many real-world database systems, this might not be the case, particularly for a database witha large amount of incomplete data distributed over various remote locations such as cloud databases. It is inadequate to directly apply skyline solutions designed for the centralized incomplete database to work on cloud due to the prohibitive cost. Thus, this paper introduces a new approach called Incomplete-data Cloud Skylines (ICS) aiming at processing skyline queries in cloud databases with incomplete data. This approach emphasizes on reducing the amount of data transfer and domination tests during skyline process. It incorporates sorting technique that assists in arranging the data items in a way where dominating data items will be placed at the top of the list helping in eliminate dominated data items. Besides, ICS also employs a filtering technique to prune the dominated data items before applying skyline technique. It comprises a technique named local skyline joiner that helps in reducing the amount of data transfer between datacenters when deriving the final skylines. It limit the amount of data items to be transferred to only those local skylines of each relation. A comprehensive experiment have been performed on both synthetic and real-life datasets, which demonstrate the effectiveness and versatility of our approach in comparison to the current existing approaches. We argue that our approach is practical and can be adopted in many contemporary cloud database systems with incomplete data to process skyline queries.  

Answering Skyline Queries over Incomplete Data with Crowdsourcing(Extended Abstract)

2020 ◽  
Author(s):  
Xiaoye Miao ◽  
Yunjun Gao ◽  
Su Guo ◽  
Lu Chen ◽  
Jianwei Yin ◽  
...  
Keyword(s):  
Incomplete Data ◽  
Skyline Queries

Skyline queries over incomplete data streams

2019 ◽  
Vol 28 (6) ◽  
pp. 961-985 ◽  
Author(s):  
Weilong Ren ◽  
Xiang Lian ◽  
Kambiz Ghazinour
Keyword(s):  
Data Streams ◽  
Incomplete Data ◽  
Skyline Queries

scholarly journals ANSWERING WHY-NOT QUESTIONS ON REVERSE SKYLINE QUERIES OVER INCOMPLETE DATA

2019 ◽  
Vol 17 (1) ◽  
pp. 84
Author(s):  
Bagus Jati Santoso ◽  
Tosca Yoel Connery
Keyword(s):  
Incomplete Data ◽  
Skyline Queries ◽  
Reverse Skyline
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