Cited by 2,410Big Data Technologies and ApplicationsInformation Retrieval and Data MiningData Mining Algorithms and Applications

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Data mining with big data

Xindong Wu, Xingquan Zhu, Gong-Qing Wu, Wei Ding·2014·IEEE Transactions on Knowledge and Data Engineering

DOI 10.1109/tkde.2013.109

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Abstract

Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.

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Authors: Wu, X., Zhu, X., Wu, G.-Q., & Ding, W.
Affiliations: Hefei University of Technology (CN)
University of Massachusetts Boston (US)
ORCID: Xindong Wu
Wei Ding
Venue: IEEE Transactions on Knowledge and Data Engineering
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Published: 2014-01
Volume: 26
Issue: 1
Pages: 97-107
ISSN: 1041-4347 (ISSN-L)
DOI: 10.1109/tkde.2013.109
OpenAlex: W2040263621
Cited by: 2,410
References: 53
Citations by year: 2026: 37 · 2025: 51 · 2024: 66 · 2023: 96 · 2022: 121 · 2021: 224 · 2020: 271 · 2019: 305 · 2018: 321 · 2017: 323 · 2016: 291 · 2015: 231 · 2014: 71
FWCI: 434.88
Type: journal article
Language: en
Open access: closed
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations: IEEE Transactions on Knowledge and Data Engineering (publishedVersion)
Topics: Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
Physical Sciences › Computer Science › Information Systems › Information Retrieval and Data Mining
Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
Keywords: big data, data mining, data-driven modeling, information sources, user interest modeling, data security and privacy

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