Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6729403 | Energy and Buildings | 2018 | 13 Pages |
Abstract
Data mining is an advanced technology for analyzing big data. It consists of two main types of data analytics, i.e., supervised and unsupervised analytics. Despite of the power of supervised analytics in predictive modeling, unsupervised analytics are more practical and promising in discovering novel knowledge given limited prior knowledge. This paper provides a comprehensive review on the current utilization of unsupervised data analytics in mining massive building operational data. The commonly used unsupervised analytics are summarized according to their knowledge representations and applications. The challenges and opportunities are elaborated as guidance for future research in this multi-disciplinary field.
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Authors
Cheng Fan, Fu Xiao, Zhengdao Li, Jiayuan Wang,