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Utility-Driven Data...
Utility-Driven Data Analytics on Uncertain Data
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- Gan, Wensheng (författare)
- College of Cyber Security/College of Information Science and Technology, Jinan University, Guangzhou 510632 Chin
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- Lin, Jerry Chun-Wei (författare)
- Western Norway University of Applied Sciences 5063, Bergen Norway
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- Chao, Han-Chieh (författare)
- National Dong Hwa University, Hualien 97401 Taiwan
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- Vasilakos, Athanasios V. (författare)
- Luleå tekniska universitet,Datavetenskap
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- Yu, Philip S. (författare)
- University of Illinois at Chicago, Chicago, IL 60607 USA
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(creator_code:org_t)
- IEEE, 2020
- 2020
- Engelska.
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Ingår i: IEEE Systems Journal. - : IEEE. - 1932-8184 .- 1937-9234. ; 14:3, s. 4442-4453
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Modern Internet of Things (IoT) applications generate massive amounts of data, much of them in the form of objects/items of readings, events, and log entries. Specifically, most of the objects in these IoT data contain rich embedded information (e.g., frequency and uncertainty) and different levels of importance (e.g., unit risk/utility of items, interestingness, cost, or weight). Many existing approaches in data mining and analytics have limitations, such as only the binary attribute is considered within a transaction, as well as all the objects/items having equal weights or importance. To solve these drawbacks, a novel utility-driven data analytics algorithm named HUPNU is presented in this article. As a general utility-driven uncertain data mining model, HUPNU can extract High-Utility patterns by considering both Positive and Negative unit utilities from Uncertain data. The qualified high-utility patterns can be effectively discovered for intrusion detection, risk prediction, manufacturing management, and decision-making, among others. By using the developed vertical Probability-Utility list with the positive and negative utilities structure, as well as several effective pruning strategies, experiments showed that the developed HUPNU approach with the pruning strategies performed great in mining the qualified patterns efficiently and effectively.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Medieteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Media and Communication Technology (hsv//eng)
Nyckelord
- Data analytics
- Internet of Things (IoT)
- manufacturing data
- uncertainty
- utility
- Pervasive Mobile Computing
- Distribuerade datorsystem
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