2015 DiscoveryofMeaningfulRulesinTim
- (Shokoohi-Yekta et al., 2015) ⇒ Mohammad Shokoohi-Yekta, Yanping Chen, Bilson Campana, Bing Hu, Jesin Zakaria, and Eamonn Keogh. (2015). “Discovery of Meaningful Rules in Time Series.” In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2015). ISBN:978-1-4503-3664-2 doi:10.1145/2783258.2783306
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- http://scholar.google.com/scholar?q=%222015%22+Discovery+of+Meaningful+Rules+in+Time+Series
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Abstract
The ability to make predictions about future events is at the heart of much of science; so, it is not surprising that prediction has been a topic of great interest in the data mining community for the last decade. Most of the previous work has attempted to predict the future based on the current value of a stream. However, for many problems the actual values are irrelevant, whereas the shape of the current time series pattern may foretell the future. The handful of research efforts that consider this variant of the problem have met with limited success. In particular, it is now understood that most of these efforts allow the discovery of spurious rules. We believe the reason why rule discovery in real-valued time series has failed thus far is because most efforts have more or less indiscriminately applied the ideas of symbolic stream rule discovery to real-valued rule discovery. In this work, we show why these ideas are not directly suitable for rule discovery in time series. Beyond our novel definitions / representations, which allow for meaningful and extendable specifications of rules, we further show novel algorithms that allow us to quickly discover high quality rules in very large datasets that accurately predict the occurrence of future events.
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Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
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2015 DiscoveryofMeaningfulRulesinTim | Eamonn Keogh Bilson Campana Jesin Zakaria Yanping Chen Bing Hu Mohammad Shokoohi-Yekta | Discovery of Meaningful Rules in Time Series | 10.1145/2783258.2783306 | 2015 |