| # | Document title | Authors | Year | Source | Cited by |
| 1 | Searching and mining trillions of time series subsequences under dynamic time warping | Rakthanmanon T., Campana B., Mueen A., Batista G., Westover B., Zhu Q., Zakaria J., Keogh E. | 2012 | Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,
pp. 262-270 | 902 |
| 2 | Fast shapelets: A scalable algorithm for discovering time series shapelets | Rakthanmanon T., Keogh E. | 2013 | Proceedings of the 2013 SIAM International Conference on Data Mining, SDM 2013,
pp. 668-676 | 378 |
| 3 | Addressing big data time series: Mining trillions of time series subsequences under dynamic time warping | Rakthanmanon T., Campana B., Mueen A., Batista G., Westover B., Zhu Q., Zakaria J., Keogh E. | 2013 | ACM Transactions on Knowledge Discovery from Data,
7(3), 10 | 206 |
| 4 | Beyond one billion time series: Indexing and mining very large time series collections with iSAX2+ | Camerra A., Shieh J., Palpanas T., Rakthanmanon T., Keogh E. | 2014 | Knowledge and Information Systems,
39(1), pp. 123-151 | 97 |
| 5 | Time series epenthesis: Clustering time series streams requires ignoring some data | Rakthanmanon T., Keogh E., Lonardi S., Evans S. | 2011 | Proceedings - IEEE International Conference on Data Mining, ICDM,
pp. 547-556, 6137259 | 92 |
| 6 | E-stream: Evolution-based technique for stream clustering | Udommanetanakit K., Rakthanmanon T., Waiyamai K. | 2007 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
4632 LNAI, pp. 605-615 | 82 |
| 7 | Single Channel ECG for Obstructive Sleep Apnea Severity Detection Using a Deep Learning Approach | Banluesombatkul N., Rakthanmanon T., Rakthanmanon T., Wilaiprasitporn T. | 2019 | IEEE Region 10 Annual International Conference, Proceedings/TENCON,
2018-October, pp. 2011-2016, 8650429 | 53 |
| 8 | MDL-based time series clustering | Rakthanmanon T., Keogh E., Lonardi S., Evans S. | 2012 | Knowledge and Information Systems,
33(2), pp. 371-399 | 51 |
| 9 | Discovering the intrinsic cardinality and dimensionality of time series using MDL | Hu B., Rakthanmanon T., Hao Y., Evans S., Lonardi S., Keogh E. | 2011 | Proceedings - IEEE International Conference on Data Mining, ICDM,
pp. 1086-1091, 6137319 | 44 |
| 10 | A general framework for never-ending learning from time series streams | Chen Y., Hao Y., Rakthanmanon T., Zakaria J., Hu B., Keogh E. | 2015 | Data Mining and Knowledge Discovery,
29(6), pp. 1622-1664 | 40 |
| 11 | A novel approximation to dynamic time warping allows anytime clustering of massive time series datasets | Zhu Q., Batista G., Rakthanmanon T., Keogh E. | 2012 | Proceedings of the 12th SIAM International Conference on Data Mining, SDM 2012,
pp. 999-1010 | 36 |
| 12 | A fast LSH-based similarity search method for multivariate time series | Yu C., Luo L., Chan L.L.H., Rakthanmanon T., Rakthanmanon T., Nutanong S. | 2019 | Information Sciences,
476, pp. 337-356 | 32 |
| 13 | Rapid annotation of interictal epileptiform discharges via template matching under Dynamic Time Warping | Jing J., Dauwels J., Rakthanmanon T., Keogh E., Cash S., Westover M. | 2016 | Journal of Neuroscience Methods,
274, pp. 179-190 | 28 |
| 14 | Efficient proper length time series motif discovery | Yingchareonthawornchai S., Sivaraks H., Rakthanmanon T., Ratanamahatana C. | 2013 | Proceedings - IEEE International Conference on Data Mining, ICDM,
pp. 1265-1270, 6729632 | 26 |
| 15 | Towards never-ending learning from time series streams | Hao Y., Chen Y., Zakaria J., Hu B., Rakthanmanon T., Keogh E. | 2013 | Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,
Part F128815, pp. 874-882, 2487634 | 25 |
| 16 | A scalable framework for cross-lingual authorship identification | Sarwar R., Li Q., Rakthanmanon T., Rakthanmanon T., Nutanong S. | 2018 | Information Sciences,
465, pp. 323-339 | 22 |
| 17 | CAG : Stylometric Authorship Attribution of Multi-Author Documents Using a Co-Authorship Graph | Sarwar R., Urailertprasert N., Vannaboot N., Yu C., Rakthanmanon T., Chuangsuwanich E., Nutanong S. | 2020 | IEEE Access,
8, pp. 18374-18393, 8962080 | 21 |
| 18 | Towards a minimum description length based stopping criterion for semi-supervised time series classification | Begum N., Hu B., Rakthanmanon T., Keogh E. | 2013 | Proceedings of the 2013 IEEE 14th International Conference on Information Reuse and Integration, IEEE IRI 2013,
pp. 333-340, 6642490 | 21 |
| 19 | Data mining a trillion time series subsequences under dynamic time warping | Rakthanmanon T., Campana B., Mueen A., Batista G., Westover B., Zhu Q., Zakaria J., Keogh E. | 2013 | IJCAI International Joint Conference on Artificial Intelligence,
pp. 3047-3051 | 20 |
| 20 | Native Language Identification of Fluent and Advanced Non-Native Writers | Sarwar R., Rutherford A.T., Hassan S.U., Rakthanmanon T., Nutanong S. | 2020 | ACM Transactions on Asian and Low-Resource Language Information Processing,
19(4), 55 | 17 |
| 21 | An effective and scalable framework for authorship attribution query processing | Sarwar R., Yu C., Tungare N., Tungare N., Chitavisutthivong K., Sriratanawilai S., Xu Y., Chow D., Rakthanmanon T., Rakthanmanon T., Nutanong S. | 2018 | IEEE Access,
6, pp. 50030-50048, 8457490 | 16 |
| 22 | StyloThai: A scalable framework for stylometric authorship identification of Thai documents | Sarwar R., Porthaveepong T., Rutherford A., Rakthanmanon T., Rakthanmanon T., Nutanong S. | 2020 | ACM Transactions on Asian and Low-Resource Language Information Processing,
19(3), A36 | 15 |
| 23 | A scalable framework for stylometric analysis of multi-author documents | Sarwar R., Yu C., Nutanong S., Urailertprasert N., Vannaboot N., Rakthanmanon T., Rakthanmanon T. | 2018 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
10827 LNCS, pp. 813-829 | 15 |
| 24 | A minimum description length technique for semi-supervised time series classification | Begum N., Hu B., Rakthanmanon T., Keogh E. | 2014 | Advances in Intelligent Systems and Computing,
263, pp. 171-192 | 14 |
| 25 | Using the minimum description length to discover the intrinsic cardinality and dimensionality of time series | Hu B., Rakthanmanon T., Hao Y., Evans S., Lonardi S., Keogh E. | 2015 | Data Mining and Knowledge Discovery,
29(2), pp. 358-399 | 14 |
| 26 | Image mining of historical manuscripts to establish provenance | Hu B., Rakthanmanon T., Campana B., Mueen A., Keogh E. | 2012 | Proceedings of the 12th SIAM International Conference on Data Mining, SDM 2012,
pp. 804-815 | 8 |
| 27 | Mining historical documents for near-duplicate figures | Rakthanmanon T., Zhu Q., Keogh E. | 2011 | Proceedings - IEEE International Conference on Data Mining, ICDM,
pp. 557-566, 6137260 | 8 |
| 28 | Object-oriented database mining: use of object oriented concepts for improving data classification technique | Waiyamai K., Songsiri C., Rakthanmanon T. | 2004 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
3036, pp. 303-309 | 7 |
| 29 | Establishing the provenance of historical manuscripts with a novel distance measure | Hu B., Rakthanmanon T., Campana B.J.L., Mueen A., Keogh E. | 2015 | Pattern Analysis and Applications,
18(2), pp. 313-331 | 7 |
| 30 | SE-Stream: Dimension projection for evolution-based clustering of high dimensional data streams | Chairukwattana R., Kangkachit T., Rakthanmanon T., Waiyamai K. | 2014 | Advances in Intelligent Systems and Computing,
245, pp. 365-376 | 6 |
| 31 | SED-Stream: Discriminative dimension selection for evolution-based clustering of high dimensional data streams | Waiyamai K., Kangkachit T., Rakthanmanon T., Chairukwattana R. | 2014 | International Journal of Intelligent Systems Technologies and Applications,
13(3), pp. 187-201 | 6 |
| 32 | Top-of-line corrosion via physics-guided machine learning: A methodology integrating field data with theoretical models | Silakorn P., Jantrakulchai N., Wararatkul N., Wanwilairat S., Kangkachit T., Techapiesancharoenkij R., Rakthanmanon T., Hanlumyuang Y. | 2022 | Journal of Petroleum Science and Engineering,
215, 110558 | 6 |
| 33 | Thai Fingerspelling Recognition Using Hand Landmark Clustering | Phothiwetchakun W., Rakthanmanon T. | 2021 | ICSEC 2021 - 25th International Computer Science and Engineering Conference,
pp. 256-261 | 5 |
| 34 | Efficiently finding near duplicate figures in archives of historical documents | Rakthanmanon T., Zhu Q., Keogh E. | 2012 | Journal of Multimedia,
7(2), pp. 109-123 | 5 |
| 35 | Towards discovering the intrinsic cardinality and dimensionality of time series using MDL | Hu B., Rakthanmanon T., Hao Y., Evans S., Lonardi S., Keogh E. | 2013 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
7070 LNAI, pp. 184-197 | 4 |
| 36 | Efficient evolution-based clustering of high dimensional data streams with dimension projection | Chairukwattana R., Kangkachit T., Rakthanmanon T., Waiyamai K. | 2013 | 2013 International Computer Science and Engineering Conference, ICSEC 2013,
pp. 185-190, 6694776 | 4 |
| 37 | Semi-supervised stream clustering using labeled data points | Treechalong K., Rakthanmanon T., Waiyamai K. | 2015 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
9166, pp. 281-295 | 4 |
| 38 | ACCD: Associative classification over concept-drifting data streams | Waiyamai K., Kangkachit T., Saengthongloun B., Rakthanmanon T. | 2014 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
8556 LNAI, pp. 78-90 | 3 |
| 39 | Clustering of symbols using minimal description length | Tataw O.M., Rakthanmanon T., Keogh E.J. | 2013 | Proceedings of the International Conference on Document Analysis and Recognition, ICDAR,
pp. 180-184, 6628608 | 3 |
| 40 | AC-Stream: Associative classification over data streams using multiple class association rules | Saengthongloun B., Kangkachit T., Rakthanmanon T., Waiyamai K. | 2013 | Proceedings of the 2013 10th International Joint Conference on Computer Science and Software Engineering, JCSSE 2013,
pp. 223-228, 6567349 | 3 |
| 41 | Prediction of enzyme class by using reactive motifs generated from binding and catalytic sites | Liewlom P., Rakthanmanon T., Waiyamai K. | 2007 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
4632 LNAI, pp. 442-453 | 3 |
| 42 | Concept lattice-based mutation control for reactive motifs discovery | Waiyamai K., Liewlom P., Kangkachit T., Rakthanmanon T. | 2008 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
5012 LNAI, pp. 767-776 | 3 |
| 43 | Estimation of ethylene/1-butene copolymerization conditions using the autoencoder model | Amnuaykijvanit O., Anantawaraskul S., Rakthanmanon T. | 2022 | Journal of Physics: Conference Series,
2175(1), 012028 | 3 |
| 44 | Hierarchical multi-label associative classification for protein function prediction using gene ontology | Sangsuriyun S., Rakthanmanon T., Waiyamai K. | 2019 | Chiang Mai Journal of Science,
46(1), pp. 165-179 | 2 |
| 45 | AutoShapelet: Reconstructable Time Series Shapelets | Ajchariyasakchai P., Rakthanmanon T. | 2020 | 2020 24th International Computer Science and Engineering Conference, ICSEC 2020,
9375153 | 1 |
| 46 | Evolution and affinity-propagation based approach for data stream clustering | Sunmood A., Rakthanmanon T., Rakthanmanon T., Waiyamai K. | 2018 | ACM International Conference Proceeding Series,
pp. 97-101 | 1 |
| 47 | Information gain Aggregation-based Approach for Time Series Shapelets Discovery | Kramakum C., Rakthanmanon T., Rakthanmanon T., Waiyamai K. | 2018 | Proceedings of 2018 10th International Conference on Knowledge and Systems Engineering, KSE 2018,
pp. 97-101, 8573365 | 1 |
| 48 | Crowdsourced Data Validation for ASR Training | Phatthiyaphaibun W., Chaksangchaichot C., Rakthammanon T., Chuangsuwanich E., Nutanong S. | 2023 | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH,
2023-August, pp. 551-555 | 1 |
| 49 | Using rule order difference criterion to decide whether to update class association rules | Kongubol K., Rakthanmanon T., Waiyamai K. | 2010 | Studies in Computational Intelligence,
283, pp. 241-252 | 1 |
| 50 | Searching historical manuscripts for near-duplicate figures | Rakthanmanon T., Zhu Q., Keogh E. | 2011 | ACM International Conference Proceeding Series,
pp. 14-21 | 1 |
| 51 | Object-oriened Data Mining System: A Tightly-coupled Association Rule Discovery from Object-oriented Databases | Rakthanmanon T., Songsiri C., Waiyamai K. | 2003 | Proceedings of 41st Kasetsart University Annual Conference,
pp. 296-306 | 0 |
| 52 | Classification model with subspace data-dependent balls | Klakhaeng N., Kangkachit T., Rakthanmanon T., Waiyamai K. | 2013 | Proceedings of the 2013 10th International Joint Conference on Computer Science and Software Engineering, JCSSE 2013,
pp. 211-216, 6567347 | 0 |
| 53 | Data Analytics for Thai Teenager Sleep Quality Check-up | Mahatkeerati P., Aksornsuwan B., Chinnapatpakdeekul P., Rakthanmanon T., Sangkawetai C. | 2024 | International Conference on Cybernetics and Innovations, ICCI 2024 | 0 |
| 54 | CCE-Stream: Semi-supervised Stream Clustering Using Color-based Constraints | Treechalong K., Rakthanmanon T., Waiyamai K. | 2023 | Proceedings of JCSSE 2023 - 20th International Joint Conference on Computer Science and Software Engineering,
pp. 43-48 | 0 |