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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Rubing Duan Goh, R.S.M. Feng Yang Di Shang, R. Yong Liu Zengxiang Li Long Wang Sifei Lu Xulei Yang Zheng Qin |
| Copyright Year | 2015 |
| Description | Author affiliation: Long Island Univ., New York, NY, USA (Di Shang, R.) || Inst. of High Performance Comput., Singapore, Singapore (Rubing Duan; Goh, R.S.M.; Feng Yang; Yong Liu; Zengxiang Li; Long Wang; Sifei Lu; Xulei Yang; Zheng Qin) |
| Abstract | Data mining is a difficult task that relies on an exploratory and analytic process of processing large quantities of data in order to discover meaningful patterns for valuable insights. The increasing heterogeneity and complexity of data requires expert knowledge on how to combine multiple data mining techniques to process and analyze the data in an effective and efficient way. This paper presents a distributed architecture, HiPerData, for automated data processing and mining using large-scale computational resource management, model building and selection, and predictive and inference analysis. We illustrate two data mining tasks in which we automate the data mining knowledge flow construction based on the use of standards that have been defined in both data mining and automated-planning communities. |
| Starting Page | 449 |
| Ending Page | 454 |
| File Size | 410996 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479983896 |
| DOI | 10.1109/ICIEA.2015.7334155 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-06-15 |
| Publisher Place | New Zealand |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Data models Analytical models Computational modeling Buildings Data analysis Big data Data mining |
| Content Type | Text |
| Resource Type | Article |
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