Publications:

2005

 Longin Jan Latecki, Vasileios Megalooikonomou, Qiang Wang, Rolf Lakaemper, Chotirat Ann Ratanamahatana , and Eamonn Keogh. Partial Elastic Matching of Time Series. In Proceedings of 5th International Conference on Data Mining (ICDM), Houston, TX, November 27-30.

Anthony Bagnall, Chotirat Ann Ratanamahatana, Eamonn Keogh, Stefano Lonardi, and Gareth Janacek. A Bit Level Representation for Time Series Data Mining with Shape Based Similarity. Data Mining and Knowledge Discovery Journal (DMKD). To Appear.

Chotirat Ann Ratanamahatana and Eamonn Keogh. Multimedia Retrieval Using Time Series Representation and Relevance Feedback. In Proceedings of 8th International Conference on Asian Digital Library (ICADL), Bangkok, Thailand, December 12-15

Longin Jan Latecki, Vasileios Megalooikonomou, Qiang Wang, Rolf Lakaemper, Chotirat Ann Ratanamahatana, and Eamonn Keogh. Elastic Partial Matching of Time Series In Proceedings of 9th European Conference on Principles and Practice in Knowledge Discovery in Databases (PKDD), Porto, Portugal, October 3-7.

Ada Wai-chee Fu, Eamonn Keogh, Yung Hang Lau, and Chotirat Ann Ratanamahatana. Scaling and Time Warping in Time Series Querying. In Proceedings of 31st International Conference on Very Large Data Bases (VLDB 2005), Trondheim, Norway, August 30 - September 2, 2005. 

Nitin Kumar, Venkata Nishanth Lolla, Eamonn Keogh, Stefano Lonardi, Chotirat Ann Ratanamahatana, and Li Wei, Time-series Bitmaps: A Practical Visualization Tool for Working with Large Time Series Databases. In proceedings of SIAM International Conference on Data Mining (SDM '05), Newport Beach, CA, April 21-23, 2005.

Chotirat Ann Ratanamahatana and Eamonn Keogh Three Myths about Dynamic Time Warping Data Mining. In proceedings of SIAM International Conference on Data Mining (SDM '05), Newport Beach, CA, April 21-23, 2005.

Chotirat Ann Ratanamahatana , Jessica Lin, Dimitrios Gunopulos, Eamonn Keogh, Michail Vlachos, and Gautam Das. "Mining Time Series Data". In O. Maimon and Rokach (eds.), Data Mining and Knowledge Discovery Handbook: A Complete Guide for Practitioners and Researchers, Kluwer Academic Publishers.

Chotirat Ann Ratanamahatana, Eamonn Keogh, Anthony J. Bagnall, and Stefano Lonardi. A Novel Bit Level Time Series Representation with Implications of Similarity Search and Clustering. In proceedings of the Ninth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Hanoi, Vietnam, May 18-20, 2005.

Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamonn Keogh, Stefano Lonardi, and Chotirat Ann Ratanamahatana. A Practical Tool for Visualizing and Data Mining Medical Time Series. The Eighteenth IEEE International Symposium on Computer-Based Medical Systems (CBMS), Dublin, Ireland, June 23-24, 2005.

Chotirat Ann Ratanamahatana and Eamonn Keogh. Using Relevance Feedback to Learn both the Distance Measure and the Query in Multimedia Databases. In Proceedings of the Ninth International Conference on Knowledge-Based & Intelligent Information & Engineering Systems, Melbourne, Australia, September 14-16, 2005. 

Li Wei, Nitin Kumar, Venkata Nishanth Lolla, Eamonn Keogh, Stefano Lonardi, and Chotirat Ann Ratanamahatana. Assumption-Free Anomaly Detection in Time Series. The Seventeenth International Scientific and Statistical Database Management Conference (SSDBM), Santa Barbara, CA, June 27-29, 2005.

Jiyuan An, Yi-Ping Phoebe Chen, Jeffrey Xu Yu, and Chotirat Ann Ratanamahatana. A Dimensionality Reduction Algorithm and Its Application for Interactive Visualization. Under Journal Review.

2004

 Nitin Kumar, Venkata Nishanth Lolla, Eamonn Keogh, Stefano Lonardi, and Chotirat Ann Ratanamahatana, Time-series Bitmaps: A Practical Visualization Tool for Working with Large Time Series Databases. Technical Report, University of California, Riverside, TR-2004-94.

Chotirat Ann Ratanamahatana, Eamonn Keogh, Anthony J. Bagnall, and Stefano Lonardi. A Novel Bit Level Time Series Representation with Implications of Similarity Search and Clustering. Technical Report, University of California, Riverside, TR-2004-93.

Chotirat Ann Ratanamahatana and Eamonn Keogh. Using Relevance Feedback in Multimedia Databases. In proceedings of the International Conferences of VISual Information System (VIS '04) San Francisco, CA, Sept 8-10, 2004.  Presentation Slides

Eamonn Keogh, Stefano Lonardi, and Chotirat Ann Ratanamahatana. Towards Parameter-Free Data Mining. In proceedings of the tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Seattle, WA, Aug 22-25, 2004. Presentation Slides

Chotirat Ann Ratanamahatana and Eamonn Keogh. Everything you know about Dynamic Time Warping is Wrong. Third Workshop on Mining Temporal and Sequential Data, in conjunction with the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004), August 22-25, 2004 - Seattle, WA. Presentation Slides

Chotirat Ann Ratanamahatana and Eamonn Keogh. Making Time-series Classification More Accurate Using Learned Constraints.  In proceedings of SIAM International Conference on Data Mining (SDM '04), Lake Buena Vista, Florida, April 22-24, 2004. pp. 11-22  Presentation Slides (email me if you'd like the full-version slides with video clips).

Eamonn Keogh and Chotirat Ann Ratanamahatana. Exact Indexing of Dynamic Time Warping. Knowledge and Information Systems: An International Journal (KAIS). DOI 10.1007/s10115-004-0154-9. May 2004.

2003

 Chotirat Ann Ratanamahatana. (2003). CloNI: Clustering of Sqrt(N)-interval discretization.  In proceedings of the 4th International Conference on Data Mining Including Building Application for CRM & Competitive Intelligence, Rio de Janeiro, Brazil, December 2003.

Eamonn Keogh, Bhrigu Celly, Chotirat Ann Ratanamahatana, and Victor Zordan. (2003). A Novel Technique for Indexing Video Surveillance Data.  In proceedings of ACM SIGMM 2003 Workshop on Video Surveillance, in conjunction with eleventh ACM International Conference on Multimedia, Berkeley, CA, November 2003.

Chotirat Ann Ratanamahatana and Dimitrios Gunopulos. (2003). Feature Selection for the Naive Bayesian Classifier Using Decision Trees.  Applied Artificial Intelligence: International Journal. Vol.17, No.5-6, pp. 475-487, May-July 2003.

2002

 Chotirat Ann Ratanamahatana and Dimitrios Gunopulos. (2002). Scaling up the Naive Bayesian Classifier: Using Decision Trees for Feature Selection.  In proceedings of Workshop on Data Cleaning and Preprocessing (DCAP 2002), at IEEE International Conference on Data Mining (ICDM 2002), Maebashi, Japan.

Chotirat Ann Ratanamahatana and Dimitrios Gunopulos. (2002). Selective Bayesian Classifier: Feature Selection for the Naive Bayesian Classifier Using Decision Trees.  In proceedings of the 3rd International Conference on Data Mining Methods and Databases for Engineering, Finance and Other Fields, Bologna, Italy, September 2002. pp. 613-623

2001

John F. Pane, Chotirat Ann Ratanamahatana, and Brad A. Myers. (2001). Studying the Language and Structure in Non-Programmers' Solutions to Programming Problems.  International Journal of Human-Computer Studies, vol.54, No.2, Feb 2001, pp. 237-264.

2000

John F. Pane, Chotirat Ann Ratanamahatana, and Brad A. Myers. (2000). Analysis of the Language and Structure in Non-Programmers' Solutions to Programming Problems(School of Computer Science Technical Report). Pittsburgh, PA: Carnegie Mellon University.

1998

Chotirat Ann Ratanamahatana (1998). Evaluating What is Natural for Beginners. Undergraduate Thesis.  School of Computer Science, Carnegie Mellon University.




Main Page   About Me   Awards   Publications   Work/Activities/etc.   Teaching   My Family    CV   DEMO