Myong Kee Jeong

Artificial Intelligence · 2009–2011

A researcher in the Science corpus: 2 papers; trusts 16 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it; #13,041 of 35,345 by trust here, #25,040 by citations
• Control and Systems Engineering — 8 citations into it; #7,111 of 8,257 by trust here, #3,865 by citations
• Building and Construction — 7 citations into it; #2,301 of 2,909 by trust here, #1,674 by citations
• Signal Processing — 7 citations into it; #2,454 of 7,572 by trust here, #4,900 by citations
• Transportation — 6 citations into it; #1,618 of 2,062 by trust here, #994 by citations

Whom Myong Kee Jeong trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Eamonn J. Keogh
2. Chotirat (Ann) Ratanamahatana
3. Toni M. Rath
4. Michael Hüsken
5. Vladimir Naumovich Vapni
6. Stephen Clark
7. Michail Vlachos
8. Xiaopeng Xi
9. Xiaomo Jiang
10. A. Stathopoulos

Who trusts Myong Kee Jeong overall

1. Anthony J. Bagnall
2. Charu C. Aggarwal
3. Jason Lines
4. Sarvesh Vishwakarma
5. Jon Hills
6. Mustafa Gokce Baydogan
7. Feng Jiang
8. Yongxue Tian

Papers from Myong Kee Jeong's perspective

Ordered by how strongly the researchers Myong Kee Jeong trusts endorse each paper. Same corpus, a different order for every researcher.

1. Word image matching using dynamic time warping (2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.)
2. Exact indexing of dynamic time warping (Knowledge and Information Systems)
3. Making Time-Series Classification More Accurate Using Learned Constraints (SDM)
4. Discovering similar multidimensional trajectories (Proceedings / International Conference on Data Engineering)
5. Fast time series classification using numerosity reduction (International Conference on Machine Learning)
6. The Nature of Statistical Learning Theory
7. An object-oriented neural network approach to short-term traffic forecasting (European Journal of Operational Research)
8. A multivariate state space approach for urban traffic flow modeling and prediction
9. Dynamic Wavelet Neural Network Model for Traffic Flow Forecasting
10. Optimized and meta-optimized neural networks for short-term traffic flow prediction: A genetic approach

Their papers

• Weighted dynamic time warping for time series classification (2011) — 700 citations
• Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions (2009) — 828 citations