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ORCIDNurjahan Begum
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- affiliation: University of California, Riverside, USA
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2010 – 2019
- 2018
[j2]Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Zachary Zimmerman, Diego Furtado Silva, Abdullah Mueen, Eamonn J. Keogh:
Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile. Data Min. Knowl. Discov. 32(1): 83-123 (2018)- 2016
- [b1]Nurjahan Begum:
Exploiting Time Series Primitives to Solve Realistic Data Mining Problems. University of California, Riverside, USA, 2016 - [c7]Hoang Anh Dau, Nurjahan Begum, Eamonn J. Keogh:
Semi-Supervision Dramatically Improves Time Series Clustering under Dynamic Time Warping. CIKM 2016: 999-1008 - [c6]Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Diego Furtado Silva, Abdullah Mueen, Eamonn J. Keogh:
Matrix Profile I: All Pairs Similarity Joins for Time Series: A Unifying View That Includes Motifs, Discords and Shapelets. ICDM 2016: 1317-1322 - [c5]Liudmila Ulanova, Nurjahan Begum, Mohammad Shokoohi-Yekta, Eamonn J. Keogh:
Clustering in the Face of Fast Changing Streams. SDM 2016: 1-9 - [i1]Nurjahan Begum, Liudmila Ulanova, Hoang Anh Dau, Jun Wang, Eamonn J. Keogh:
A General Framework for Density Based Time Series Clustering Exploiting a Novel Admissible Pruning Strategy. CoRR abs/1612.00637 (2016) - 2015
- [c4]Nurjahan Begum, Liudmila Ulanova, Jun Wang, Eamonn J. Keogh:
Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy. KDD 2015: 49-58 - [c3]Liudmila Ulanova, Nurjahan Begum, Eamonn J. Keogh:
Scalable Clustering of Time Series with U-Shapelets. SDM 2015: 900-908 - 2014
- [j1]Nurjahan Begum, Eamonn J. Keogh:
Rare Time Series Motif Discovery from Unbounded Streams. Proc. VLDB Endow. 8(2): 149-160 (2014) - 2013
- [c2]Nurjahan Begum, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh:
A Minimum Description Length Technique for Semi-Supervised Time Series Classification. IRI (best papers) 2013: 171-192 - [c1]Nurjahan Begum, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh:
Towards a minimum description length based stopping criterion for semi-supervised time series classification. IRI 2013: 333-340
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