Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/rob-med/everything-shapelets
This repo contains useful links to research papers and implementations of shapelets discovery/learning techniques from different sources.
https://github.com/rob-med/everything-shapelets
data-analysis data-mining shapelets time-series-analysis timeseries
Last synced: about 1 month ago
JSON representation
This repo contains useful links to research papers and implementations of shapelets discovery/learning techniques from different sources.
- Host: GitHub
- URL: https://github.com/rob-med/everything-shapelets
- Owner: rob-med
- Created: 2017-03-29T07:36:31.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2017-04-07T19:14:34.000Z (over 7 years ago)
- Last Synced: 2023-10-20T22:51:46.105Z (about 1 year ago)
- Topics: data-analysis, data-mining, shapelets, time-series-analysis, timeseries
- Homepage:
- Size: 2.93 KB
- Stars: 17
- Watchers: 4
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Everything-Shapelets
>This repo contains useful links to descriptions and implementations of shapelets discovery/learning techniques from different sources.---------------------------------------
# 1 Research Papers and Implementations
## 1.0 Original Paper
**[0]** Lexiang Ye and Eamonn Keogh (2009) **Time Series Shapelets: A New Primitive for Data Mining**. SIGKDD 2009 [[pdf]](http://www.cs.ucr.edu/~eamonn/shaplet.pdf)
## 1.1 Logical Shapelets
**[1]** Abdullah Mueen, Eamonn Keogh, Neal Young (2011). **Logical-Shapelets: An Expressive Primitive for Time Series Classification**. SIGKDD 2011. [[pdf]](http://www.cs.ucr.edu/~eamonn/LogicalShapelet.pdf)
## 1.2 Fast Shapelets
**[2]** Thanawin Rakthanmanon and Eamonn Keogh. **Fast-Shapelets: A Scalable Algorithm for Discovering Time Series Shapelets**. SDM 2013 [[pdf]](http://www.cs.ucr.edu/~eamonn/SDM_FastShapelets.pdf) [[code&extra]](http://alumni.cs.ucr.edu/~rakthant/FastShapelet/)
## 1.3 Learning Shapelets
**[3]** Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme (2014).
**Learning Time-Series Shapelets**, SIGKDD 2014 [[pdf]](https://www.ismll.uni-hildesheim.de/pub/pdfs/grabocka2014e-kdd.pdf) [[code&extra]](http://fs.ismll.de/publicspace/LearningShapelets/)**[4]** Yi Yang, Qilin Deng, Furao Shen, Jinxi Zhao and Chaomin Luo (2016).
**A Shapelet Learning Method for Time Series Classification**, 2016 IEEE 28th International Conference on Tools with Artificial Intelligence [[link]](http://ieeexplore.ieee.org/abstract/document/7814631/) [[code&extra]](https://github.com/yyawesome/LearningShapelets)**[5]** LHJT Kwok, JM Zurada **Efficient learning of timeseries shapelets** AAAI'16 Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence [[pdf]](https://www.cse.ust.hk/~jamesk/papers/aaai16c.pdf)
## 1.4 Scalable Discovery
**[6]** J Grabocka, M Wistuba, L Schmidt-Thieme. **Scalable discovery of time-series shapelets** [[pdf]](https://arxiv.org/pdf/1503.03238)
[[code&extra]](https://www.dropbox.com/sh/btiee2pyn6a989q/AACDfzkkpdYPmgw7pgTgUoeYa)## 1.5 Random Shapelet Forests
**[7]** Karlsson, Isak Papapetrou, Panagiotis Boström, Henrik **Generealized Random Shapelet Forests** [[link]](https://link.springer.com/article/10.1007/s10618-016-0473-y) [[code&extra]](http://people.dsv.su.se/~isak-kar/grsf/)