Chotirat (Ann) Ratanamahatana
Signal Processing · 2001–2018
A researcher in the Science corpus: 8 papers; trusts 22 researchers and is trusted by 117 researchers here, as inferred from the citation graph.
Subfields
- Signal Processing — 28 citations into it; #176 of 7,572 by trust here, #440 by citations
- Artificial Intelligence — 17 citations into it; #3,822 of 35,345 by trust here, #7,858 by citations
- Computer Vision and Pattern Recognition — 8 citations into it
- Economics and Econometrics — 8 citations into it; #3,626 of 23,481 by trust here, #9,863 by citations
- Computer Networks and Communications — 6 citations into it
- Molecular Biology — 6 citations into it
Whom Chotirat (Ann) Ratanamahatana trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Eamonn J. Keogh
- Toni M. Rath
- Zsolt Miklós Kovács-Vajna
- Yunyue Zhu
- Kaushik Chakrabarti
- Raghavan Manmatha
- Michail Vlachos
- Dennis E. Shasha
- George M. Church
- Byoung-Kee Yi
Who trusts Chotirat (Ann) Ratanamahatana overall
- Eamonn J. Keogh
- Mustafa Gokce Baydogan
- Tak-Chung Fu
- Pierre-Francois Marteau
- John Paparrizos
- Youngseon Jeong
- Philippe Esling
- Li Wei
- George C. Runger
- Rohit J. Kate
Papers from Chotirat (Ann) Ratanamahatana's perspective
Ordered by how strongly the researchers Chotirat (Ann) Ratanamahatana trusts endorse each paper. Same corpus, a different order for every researcher.
- Fast Time Sequence Indexing for Arbitrary Lp Norms (Very Large Data Bases Conference)
- Using Dynamic Time Warping to Find Patterns in Time Series
- Locally adaptive dimensionality reduction for indexing large time series databases (ACM SIGMOD Conference)
- Exact indexing of dynamic time warping (Knowledge and Information Systems)
- Word image matching using dynamic time warping (2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.)
- On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
- Making Time-Series Classification More Accurate Using Learned Constraints (SDM)
- Fundamentals of speech recognition
- Scaling up dynamic time warping for datamining applications
- Discovering similar multidimensional trajectories (Proceedings / International Conference on Data Engineering)
Their papers
- Towards parameter-free data mining (2004) — 662 citations
- Three Myths about Dynamic Time Warping Data Mining (2005) — 477 citations
- The UCR time series archive (2018) — 1,107 citations
- Fast time series classification using numerosity reduction (2006) — 658 citations
- Everything you know about Dynamic Time Warping is Wrong (2004) — 412 citations
- Making Time-Series Classification More Accurate Using Learned Constraints (2004) — 473 citations
- Exact indexing of dynamic time warping (2002) — 2,764 citations
- Studying the language and structure in non-programmers' solutions to programming problems (2001) — 337 citations