Thanawin Rakthanmanon

Orcid: 0000-0001-6598-2971

According to our database1, Thanawin Rakthanmanon authored at least 45 papers between 2004 and 2023.

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Bibliography

2023
CCE-Stream: Semi-supervised Stream Clustering Using Color-based Constraints.
Proceedings of the 20th IEEE International Joint Conference on Computer Science and Software Engineering, 2023

Crowdsourced Data Validation for ASR Training.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

2020
Native Language Identification of Fluent and Advanced Non-Native Writers.
ACM Trans. Asian Low Resour. Lang. Inf. Process., 2020

<i>StyloThai: </i>: A Scalable Framework for Stylometric Authorship Identification of Thai Documents.
ACM Trans. Asian Low Resour. Lang. Inf. Process., 2020

CAG: Stylometric Authorship Attribution of Multi-Author Documents Using a Co-Authorship Graph.
IEEE Access, 2020

2019
A fast LSH-based similarity search method for multivariate time series.
Inf. Sci., 2019

Entropy-based Approach for Parameter-free Attribute Clustering.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2019

2018
A scalable framework for cross-lingual authorship identification.
Inf. Sci., 2018

An Effective and Scalable Framework for Authorship Attribution Query Processing.
IEEE Access, 2018

Single Channel ECG for Obstructive Sleep Apnea Severity Detection Using a Deep Learning Approach.
Proceedings of the TENCON 2018, 2018

Information gain Aggregation-based Approach for Time Series Shapelets Discovery.
Proceedings of the 10th International Conference on Knowledge and Systems Engineering, 2018

A Scalable Framework for Stylometric Analysis of Multi-author Documents.
Proceedings of the Database Systems for Advanced Applications, 2018

2016
Cluster-Based Minority Over-Sampling for Imbalanced Datasets.
IEICE Trans. Inf. Syst., 2016

2015
Establishing the provenance of historical manuscripts with a novel distance measure.
Pattern Anal. Appl., 2015

A general framework for never-ending learning from time series streams.
Data Min. Knowl. Discov., 2015

Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series.
Data Min. Knowl. Discov., 2015

Semi-Supervised Stream Clustering Using Labeled Data Points.
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+.
Knowl. Inf. Syst., 2014

SED-Stream: discriminative dimension selection for evolution-based clustering of high dimensional data streams.
Int. J. Intell. Syst. Technol. Appl., 2014

ACCD: Associative Classification over Concept-Drifting Data Streams.
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.
ACM Trans. Knowl. Discov. Data, 2013

Fast Shapelets: A Scalable Algorithm for Discovering Time Series Shapelets.
Proceedings of the 13th SIAM International Conference on Data Mining, 2013

SE-Stream: Dimension Projection for Evolution-Based Clustering of High Dimensional Data Streams.
Proceedings of the Knowledge and Systems Engineering, 2013

Towards never-ending learning from time series streams.
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.
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.
Proceedings of the IEEE 14th International Conference on Information Reuse & Integration, 2013

Data Mining a Trillion Time Series Subsequences Under Dynamic Time Warping.
Proceedings of the IJCAI 2013, 2013

Efficient Proper Length Time Series Motif Discovery.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Clustering of Symbols Using Minimal Description Length.
Proceedings of the 12th International Conference on Document Analysis and Recognition, 2013

2012
Efficient Algorithms for High Dimensional Data Mining.
PhD thesis, 2012

MDL-based time series clustering.
Knowl. Inf. Syst., 2012

Efficiently Finding Near Duplicate Figures in Archives of Historical Documents.
J. Multim., 2012

A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Image Mining of Historical Manuscripts to Establish Provenance.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Searching and mining trillions of time series subsequences under dynamic time warping.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

2011
Mining Historical Documents for Near-Duplicate Figures.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Searching historical manuscripts for near-duplicate figures.
Proceedings of the 2011 Workshop on Historical Document Imaging and Processing, 2011

Towards Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL.
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.
Proceedings of the Advances in Intelligent Information and Database Systems, 2010

2008
Concept Lattice-Based Mutation Control for Reactive Motifs Discovery.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2008

2007
E-Stream: Evolution-Based Technique for Stream Clustering.
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.
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.
Proceedings of the Computational Science, 2004


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