Search Results - real ((((((query processing) OR (data processing))) OR (rice processing))) OR (_ processing))
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Optimizing skyline query processing in incomplete data
Published 2019“…Hence, missing data pose new challenges if the processing skyline queries cannot easily apply those methods that are designed for complete data. …”
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2
Processing skyline queries in incomplete database: issues, challenges and future trends
Published 2017“…In many contemporary database applications such as multi-criteria decision-making and real-time decision-support applications, data mining, ecommerce and recommendation systems, users need query operators to process the data aiming at finding the results that best fit with their preferences. …”
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A systematic literature review of skyline query processing over data stream
Published 2023“…Although an abundance of skyline query processing techniques have been proposed, there is a lack of a Systematic Literature Review (SLR) on current research works pertinent to skyline query processing over data stream. …”
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4
D-SKY: a framework for processing skyline queries in a dynamic and incomplete database
Published 2018“…Processing skyline queries in incomplete data is challenging, particularly, for a database with dynamic contents in which the database is frequently updated. …”
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Proceeding Paper -
5
A systematic literature review of skyline query processing over data stream
Published 2023“…Although an abundance of skyline query processing techniques have been proposed, there is a lack of a Systematic Literature Review (SLR) on current research works pertinent to skyline query processing over data stream. …”
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GNN-based skyline query processing for large-scale and incomplete graphs
Published 2026“…This research demonstrates the potential to improve query processing efficiency and to support applications in e-commerce, finance, and smart data systems…”
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Processing skyline queries in centralised and distributed incomplete databases
Published 2013“…Several experiments on synthetic and real datasets have been conducted. The results showed that our proposed approach for processing skyline queries in incomplete database has reduced the number of pairwise comparisons in the range of 75%-93% and the processing time in the range of 50%-89% compared to the previous approach. …”
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8
Efficient skyline query processing in incomplete graph databases using machine learning techniques
Published 2025“…Processing skyline queries in such massive, incomplete graphs is computationally intensive due to missing values and high-dimensional data. …”
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9
Analyzing Power Consumption in Query Processing for Centralized Database System
Published 2012“…In supporting to green computing, this project is being carried out with the main purpose to analyze the efficient performance of query processing activity in consuming power from a centralized database by implementing different query strategies in data grouping. …”
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Final Year Project -
10
Efficient management of Top-k queries over Uncertain Data Streams with dynamic Sliding Window Model
Published 2024“…The Uncertain Data Stream (UDS) utilized for query processing can provide challenges in many technical contexts owing to its inherent inconsistency, ambiguity, and time delay in interpreting information. …”
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11
Skyline query processing for incomplete data in cloud environment
Published 2017“…An approach is needed taking into considera-tion the unique features of cloud environment when processing skyline que-ries on a database with incomplete data. …”
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Proceeding Paper -
12
Skyline queries computation on crowdsourced- enabled incomplete database
Published 2020“…Processing skyline queries over incomplete databases impose a number of challenges that negatively influence processing the skyline queries. …”
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13
Enhancing skyline query processing on large and incomplete graphs with graph neural networks: a hybrid machine learning approach
Published 2025“…This work demonstrates the potential of creating a more efficient query processing, supporting applications in e-commerce, finance, and smart data systems, while aligning with the 9th Sustainable Development Goal on industry, innovation, and infrastructure.…”
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14
Optimizing B-tree search performance of big data sets / Mohsen Marjani
Published 2017“…This research contributes in optimizing data retrieval for big data sets and gives direction to researchers towards a novel approach of indexing and searching big data in order to improve query processing and search performance.…”
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15
Skyline queries computation on crowdsourced- enabled incomplete database
Published 2020“…Processing skyline queries over incomplete databases impose a number of challenges that negatively influence processing the skyline queries. …”
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IDSA: an efficient algorithm for skyline queries computation on dynamic and incomplete data with changing states
Published 2021“…Data incompleteness causes several challenges on skyline queries such as losing the transitivity property of the skyline technique and the test dominance process between tuples being cyclic. …”
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IDSA: an efficient algorithm for skyline queries computation on dynamic and incomplete data with changing states
Published 2021“…Data incompleteness causes several challenges on skyline queries such as losing the transitivity property of the skyline technique and the test dominance process between tuples being cyclic. …”
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18
CSQUiD: an index and non-probability framework for constrained skyline query processing over uncertain data
Published 2024“…Therefore, this work introduces an index, non-probability framework named Constrained Skyline Query processing on Uncertain Data (CSQUiD) aiming at reducing the computational time in processing constrained skyline queries over uncertain high-dimensional data. …”
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Identifying skylines in cloud databases with incomplete data
Published 2019“…Thus, this paper introduces a new approach called Incomplete-data Cloud Skylines (ICS) aiming at processing skyline queries in cloud databases with incomplete data. …”
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Building textual OLAP cubes using real-time intelligent heterogeneous approach
Published 2018“…In this context, the approach (a) exploits the GPU along with the CPU in order to process textual data. (b) Stores the queries aggregations’ hash table in the global memory such that the higher aggregations levels are being answered in a shorter time (c) Introduces an intelligent self-evaluating mechanism (ISEM), that evaluates the resource efficiency on query-basis by deciding which resource (CPU or GPU+CPU) is more reliable to process each query. …”
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