research-article

Balanced Dominating Top-k Queries over Uncertain Data

Authors:

Ping LiAuthors Info & Claims

CCIOT '20: Proceedings of the 2020 5th International Conference on Cloud Computing and Internet of Things

Pages 69 - 76

https://doi.org/10.1145/3429523.3429533

Published: 09 November 2020 Publication History

Abstract

Uncertainty of data is inherent in many important applications. Effectively extracting valuable information to enable better decisions is important but not a trivial task over uncertain data. We have witnessed a great deal of significant researches for this purpose, such as top-k queries, skyline queries and dominated top-k queries. As for uncertainty, the common challenge that those researches face is to answer the ranking methods in consideration of user's function score and probability. In this paper, we propose a novel ranking method to select reliable and worthy results. In our method the coordinated and balanced degree of score and probability is also an evaluation target. After constructing of balance degree, we design the balanced dominating top-k query semantic and effective algorithms to identify the top-k answers. Comprehensive experiments with both real and synthetic data sets demonstrate the effectiveness and efficiency of our proposed approach.

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Cited By

Hossen FAzharul Hasan K(2024)Dominance by Stability: A Framework for Top k Dominating Query on Incomplete DataProceedings of the 2nd International Conference on Big Data, IoT and Machine Learning10.1007/978-981-99-8937-9_2(19-32)Online publication date: 30-Mar-2024
https://doi.org/10.1007/978-981-99-8937-9_2
Hossen FAzharul Hasan KAbdul Fattah HTsuji T(2023)Partial Dominance: A New Framework for Top-k Dominating Queries on Highly Incomplete Data2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT56998.2023.10306585(1-6)Online publication date: 6-Jul-2023
https://doi.org/10.1109/ICCCNT56998.2023.10306585
Fattah HHasan KTsuji T(2022)Weighted top-k dominating queries on highly incomplete dataInformation Systems10.1016/j.is.2022.102008107:COnline publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1016/j.is.2022.102008
Show More Cited By

Index Terms

Balanced Dominating Top-k Queries over Uncertain Data
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking
      1. Probabilistic retrieval models
      2. Top-k retrieval in databases

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CCIOT '20: Proceedings of the 2020 5th International Conference on Cloud Computing and Internet of Things

September 2020

93 pages

ISBN:9781450375276

DOI:10.1145/3429523

Copyright © 2020 ACM.

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Publication History

Published: 09 November 2020

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CCIOT 2020

CCIOT 2020: 2020 5th International Conference on Cloud Computing and Internet of Things

September 22 - 24, 2020

Okinawa, Japan

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Cited By

Hossen FAzharul Hasan K(2024)Dominance by Stability: A Framework for Top k Dominating Query on Incomplete DataProceedings of the 2nd International Conference on Big Data, IoT and Machine Learning10.1007/978-981-99-8937-9_2(19-32)Online publication date: 30-Mar-2024
https://doi.org/10.1007/978-981-99-8937-9_2
Hossen FAzharul Hasan KAbdul Fattah HTsuji T(2023)Partial Dominance: A New Framework for Top-k Dominating Queries on Highly Incomplete Data2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT56998.2023.10306585(1-6)Online publication date: 6-Jul-2023
https://doi.org/10.1109/ICCCNT56998.2023.10306585
Fattah HHasan KTsuji T(2022)Weighted top-k dominating queries on highly incomplete dataInformation Systems10.1016/j.is.2022.102008107:COnline publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1016/j.is.2022.102008
Miniak-Górecka APodlaski KGwizdałła T(2022)Self-Optimizing Neural Network in Classification of Real Valued Experimental DataIntelligent Information and Database Systems10.1007/978-3-031-21967-2_20(241-254)Online publication date: 28-Nov-2022
https://dl.acm.org/doi/10.1007/978-3-031-21967-2_20
Abdul Fattah HAzharul Hasan KTsuji T(2021)Indexed Top-k Dominating Queries on Highly Incomplete DataProceedings of the International Conference on Big Data, IoT, and Machine Learning10.1007/978-981-16-6636-0_19(231-241)Online publication date: 4-Dec-2021
https://doi.org/10.1007/978-981-16-6636-0_19

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