Thanawin Rakthanmanon

According to our database, Thanawin Rakthanmanon authored at least 44 papers between 2004 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

CCE-Stream: Semi-supervised Stream Clustering Using Color-based Constraints.

Kritsana Treechalong, Thanawin Rakthanmanon, Kitsana Waiyamai

Proceedings of the 20th IEEE International Joint Conference on Computer Science and Software Engineering, 2023

2020

Native Language Identification of Fluent and Advanced Non-Native Writers.

Raheem Sarwar, Attapol T. Rutherford, Saeed-Ul Hassan, Thanawin Rakthanmanon, Sarana Nutanong

ACM Trans. Asian Low Resour. Lang. Inf. Process., 2020

<i>StyloThai: </i>: A Scalable Framework for Stylometric Authorship Identification of Thai Documents.

Raheem Sarwar, Thanasarn Porthaveepong, Attapol Rutherford, Thanawin Rakthanmanon, Sarana Nutanong

ACM Trans. Asian Low Resour. Lang. Inf. Process., 2020

CAG: Stylometric Authorship Attribution of Multi-Author Documents Using a Co-Authorship Graph.

Raheem Sarwar, Norawit Urailertprasert, Nattapol Vannaboot, Chenyun Yu, Thanawin Rakthanmanon, Ekapol Chuangsuwanich, Sarana Nutanong

IEEE Access, 2020

2019

A fast LSH-based similarity search method for multivariate time series.

Chenyun Yu, Lintong Luo, Leanne Lai Hang Chan, Thanawin Rakthanmanon, Sarana Nutanong

Inf. Sci., 2019

Entropy-based Approach for Parameter-free Attribute Clustering.

Adison Khomprasert, Thanawin Rakthanmanon, Kitsana Waiyamai

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2019

2018

A scalable framework for cross-lingual authorship identification.

Raheem Sarwar, Qing Li, Thanawin Rakthanmanon, Sarana Nutanong

Inf. Sci., 2018

An Effective and Scalable Framework for Authorship Attribution Query Processing.

Raheem Sarwar, Chenyun Yu, Ninad Tungare, Kanatip Chitavisutthivong, Sukrit Sriratanawilai, Yaohai Xu, Dickson Chow, Thanawin Rakthanmanon, Sarana Nutanong

IEEE Access, 2018

Single Channel ECG for Obstructive Sleep Apnea Severity Detection Using a Deep Learning Approach.

Nannapas Banluesombatkul, Thanawin Rakthanmanon, Theerawit Wilaiprasitporn

Proceedings of the TENCON 2018, 2018

Information gain Aggregation-based Approach for Time Series Shapelets Discovery.

Chutimol Kramakum, Thanawin Rakthanmanon, Kitsana Waiyamai

Proceedings of the 10th International Conference on Knowledge and Systems Engineering, 2018

A Scalable Framework for Stylometric Analysis of Multi-author Documents.

Raheem Sarwar, Chenyun Yu, Sarana Nutanong, Norawit Urailertprasert, Nattapol Vannaboot, Thanawin Rakthanmanon

Proceedings of the Database Systems for Advanced Applications, 2018

2016

Cluster-Based Minority Over-Sampling for Imbalanced Datasets.

Kamthorn Puntumapon, Thanawin Rakthanmanon, Kitsana Waiyamai

IEICE Trans. Inf. Syst., 2016

2015

Establishing the provenance of historical manuscripts with a novel distance measure.

Bing Hu, Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Eamonn J. Keogh

Pattern Anal. Appl., 2015

A general framework for never-ending learning from time series streams.

Yanping Chen, Yuan Hao, Thanawin Rakthanmanon, Jesin Zakaria, Bing Hu, Eamonn J. Keogh

Data Min. Knowl. Discov., 2015

Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series.

Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh

Data Min. Knowl. Discov., 2015

Semi-Supervised Stream Clustering Using Labeled Data Points.

Kritsana Treechalong, Thanawin Rakthanmanon, Kitsana Waiyamai

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2015

2014

Beyond one billion time series: indexing and mining very large time series collections with i SAX2+.

Alessandro Camerra, Jin Shieh, Themis Palpanas, Thanawin Rakthanmanon, Eamonn J. Keogh

Knowl. Inf. Syst., 2014

SED-Stream: discriminative dimension selection for evolution-based clustering of high dimensional data streams.

Kitsana Waiyamai, Thanapat Kangkachit, Thanawin Rakthanmanon, Rattanapong Chairukwattana

Int. J. Intell. Syst. Technol. Appl., 2014

ACCD: Associative Classification over Concept-Drifting Data Streams.

Kitsana Waiyamai, Thanapat Kangkachit, Bordin Saengthongloun, Thanawin Rakthanmanon

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2014

2013

Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping.

Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Gustavo E. A. P. A. Batista, M. Brandon Westover, Qiang Zhu, Jesin Zakaria, Eamonn J. Keogh

ACM Trans. Knowl. Discov. Data, 2013

Fast Shapelets: A Scalable Algorithm for Discovering Time Series Shapelets.

Eamonn J. Keogh, Thanawin Rakthanmanon

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

SE-Stream: Dimension Projection for Evolution-Based Clustering of High Dimensional Data Streams.

Rattanapong Chairukwattana, Thanapat Kangkachit, Thanawin Rakthanmanon, Kitsana Waiyamai

Proceedings of the Knowledge and Systems Engineering, 2013

Towards never-ending learning from time series streams.

Yuan Hao, Yanping Chen, Jesin Zakaria, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

A Minimum Description Length Technique for Semi-Supervised Time Series Classification.

Nurjahan Begum, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh

Proceedings of the Integration of Reusable Systems [extended versions of the best papers which were presented at IEEE International Conference on Information Reuse and Integration and IEEE International Workshop on Formal Methods Integration, 2013

Towards a minimum description length based stopping criterion for semi-supervised time series classification.

Nurjahan Begum, Bing Hu, Thanawin Rakthanmanon, Eamonn J. Keogh

Proceedings of the IEEE 14th International Conference on Information Reuse & Integration, 2013

Data Mining a Trillion Time Series Subsequences Under Dynamic Time Warping.

Thanawin Rakthanmanon, Eamonn J. Keogh

Proceedings of the IJCAI 2013, 2013

Efficient Proper Length Time Series Motif Discovery.

Sorrachai Yingchareonthawornchai, Haemwaan Sivaraks, Thanawin Rakthanmanon, Chotirat Ann Ratanamahatana

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Clustering of Symbols Using Minimal Description Length.

Oben M. Tataw, Thanawin Rakthanmanon, Eamonn J. Keogh

Proceedings of the 12th International Conference on Document Analysis and Recognition, 2013

2012

Efficient Algorithms for High Dimensional Data Mining.

Thanawin Rakthanmanon

PhD thesis, 2012

MDL-based time series clustering.

Thanawin Rakthanmanon, Eamonn J. Keogh, Stefano Lonardi, Scott Evans

Knowl. Inf. Syst., 2012

Efficiently Finding Near Duplicate Figures in Archives of Historical Documents.

Thanawin Rakthanmanon, Qiang Zhu, Eamonn J. Keogh

J. Multim., 2012

A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets.

Qiang Zhu, Gustavo E. A. P. A. Batista, Thanawin Rakthanmanon, Eamonn J. Keogh

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Image Mining of Historical Manuscripts to Establish Provenance.

Bing Hu, Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Eamonn J. Keogh

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Searching and mining trillions of time series subsequences under dynamic time warping.

Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Gustavo E. A. P. A. Batista, M. Brandon Westover, Qiang Zhu, Jesin Zakaria, Eamonn J. Keogh

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

2011

Mining Historical Documents for Near-Duplicate Figures.

Thanawin Rakthanmanon, Qiang Zhu, Eamonn J. Keogh

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data.

Thanawin Rakthanmanon, Eamonn J. Keogh, Stefano Lonardi, Scott Evans

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL.

Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Searching historical manuscripts for near-duplicate figures.

Thanawin Rakthanmanon, Qiang Zhu, Eamonn J. Keogh

Proceedings of the 2011 Workshop on Historical Document Imaging and Processing, 2011

Towards Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL.

Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh

Proceedings of the Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 2011

2010

Using Rule Order Difference Criterion to Decide Whether to Update Class Association Rules.

Kritsadakorn Kongubol, Thanawin Rakthanmanon, Kitsana Waiyamai

Proceedings of the Advances in Intelligent Information and Database Systems, 2010

2008

Concept Lattice-Based Mutation Control for Reactive Motifs Discovery.

Kitsana Waiyamai, Peera Liewlom, Thanapat Kangkachit, Thanawin Rakthanmanon

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

2007

E-Stream: Evolution-Based Technique for Stream Clustering.

Komkrit Udommanetanakit, Thanawin Rakthanmanon, Kitsana Waiyamai

Proceedings of the Advanced Data Mining and Applications, Third International Conference, 2007

Prediction of Enzyme Class by Using <i>Reactive Motifs</i> Generated from Binding and Catalytic Sites.

Peera Liewlom, Thanawin Rakthanmanon, Kitsana Waiyamai

Proceedings of the Advanced Data Mining and Applications, Third International Conference, 2007

2004

Object-Oriented Database Mining: Use of Object Oriented Concepts for Improving Data Classification Technique.

Kitsana Waiyamai, Chidchanok Songsiri, Thanawin Rakthanmanon

Proceedings of the Computational Science, 2004