Person Image

    Education

    • Ph. D. (Computer Science), University of California, USA, 2555
    • วศ. ม. .(วิศวกรรมคอมพิวเตอร์), มหาวิทยาลัยเกษตรศาสตร์, ไทย, 2546
    • วศ. บ..(วิศวกรรมคอมพิวเตอร์), มหาวิทยาลัยเกษตรศาสตร์, ไทย, 2543

    Expertise Cloud

    affinity propagation clusteringApplication scenarioApproximation AlgorithmApproximation methodsArtificial Intelligenceassociative classificationAuthor profilingAuthorship analysisAuthorship attributionauthorship identificationAutomatic feature extractionBiomedical signal processingBulk loadingchange detectionChanging environmentchanging environmentsClassificationClassification (of information)Clsssificationscluster-based minority over-samplingClusteringCo-Authorship GraphCo-authorship graphsComputational linguisticsComputer scienceComputersconcept driftConcept driftsConvolutional neural networkCorrosion PredictionCross-lingualCyber forensicCyber forensicsData acquisitionData communication systemsData handlingData MiningData ProcessingData representation modelsData streamData Streamsdata streams classificationData structuresDatabase systemsDecision MakingDecision treesDeep LearningDetermine dataDimensionality reductiondiscriminative dimension selectionDynamic rule updatingDynamic Time WarpingEEGElectrocardiographyEntropyError analysisEvolution-based clusteringevolution-based stream clusteringevolving data streamsFast Nearest Neighbor SearchFeature extractionfeature selectionsforensic investigationForestryFully connected neural networkGraphical user interfacehierarchicalHier-archical clusteringHigh dimensional data streamsImage Similarityimbalanced dataIncremental associative classificationIncremental data databasesIndexingInformation GainInterictal dischargesJob analysisK fold cross validationslarge scale databaseLarge-scale databaseLearning systemsLocality sensitive hashingLong short-term memorymulti-author documentsmultiple class-sssociation rulesObstructive sleep apneaObstructive sleep apnea (OSA) severity detectionOrder differencePattern recognitionQuery processingReal time systemsSemi-supervised learningSimilarity searchSingle channel ECGSleep researchstylometrySudden cardiac deaths (SCD)Temporal information extractionTime SeriesTrees (mathematics)

    Interest

    Data Mining, Time Series Mining, Machine Learning, Scalable Algorithms

    Administrative Profile


      Resource


      งานวิจัยในรอบ 5 ปี

      Project

      งานวิจัยที่อยู่ระหว่างการดำเนินการ
      • ทุนใน 0 โครงการ
      • ทุนนอก 0 โครงการ
      งานวิจัยที่เสร็จสิ้นแล้ว
      • ทุนใน 1 โครงการ (ผู้ร่วมวิจัย 1 โครงการ)
      • ทุนนอก 4 โครงการ (หัวหน้าโครงการ 3 โครงการ, ผู้ร่วมวิจัย 1 โครงการ)

      แนวโน้มผลงานทั้งหมดเทียบกับแนวโน้มผลงานในรอบ 5 ปี

      Output

      • บทความ 37 เรื่อง (ตีพิมพ์ในวารสารวิชาการ 22 เรื่อง, นำเสนอในการประชุม/สัมมนา 15 เรื่อง)
      • ทรัพย์สินทางปัญญา 1 เรื่อง (สิทธิบัตร 1 เรื่อง)

      แนวโน้มการนำผลงานไปใช้ประโยชน์ในด้านต่างๆ

      Outcome

      • การนำผลงานไปใช้ประโยชน์ 0 เรื่อง (เชิงวิชาการ 0 เรื่อง, เชิงนโยบาย/บริหาร 0 เรื่อง, เชิงสาธารณะ 0 เรื่อง, เชิงพาณิชย์ 0 เรื่อง)

      รางวัลที่ได้รับ

      Award

      • รางวัลที่ได้รับ 0 เรื่อง (ประกาศเกียรติคุณ/รางวัลนักวิจัย 0 เรื่อง, รางวัลผลงานวิจัย/สิ่งประดิษฐ์ 0 เรื่อง, รางวัลผลงานนำเสนอในการประชุมวิชาการ 0 เรื่อง)

      นักวิจัยที่มีผลงานงานร่วมกันมากที่สุด 10 คนแรก

      Person Relation

      Show All (83)

      Scopus h-index

      #Document titleAuthorsYearSourceCited by
      1Searching and mining trillions of time series subsequences under dynamic time warpingRakthanmanon T., Campana B., Mueen A., Batista G., Westover B., Zhu Q., Zakaria J., Keogh E.2012Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
      ,pp. 262-270
      541
      2Fast shapelets: A scalable algorithm for discovering time series shapeletsRakthanmanon T., Keogh E.2013Proceedings of the 2013 SIAM International Conference on Data Mining, SDM 2013
      ,pp. 668-676
      201
      3Addressing big data time series: Mining trillions of time series subsequences under dynamic time warpingRakthanmanon T., Campana B., Mueen A., Batista G., Westover B., Zhu Q., Zakaria J., Keogh E.2013ACM Transactions on Knowledge Discovery from Data
      7(3)
      107
      4Beyond one billion time series: Indexing and mining very large time series collections with iSAX2+Camerra A., Shieh J., Palpanas T., Rakthanmanon T., Keogh E.2014Knowledge and Information Systems
      39(1),pp. 123-151
      64
      5Time series epenthesis: Clustering time series streams requires ignoring some dataRakthanmanon T., Keogh E., Lonardi S., Evans S.2011Proceedings - IEEE International Conference on Data Mining, ICDM
      ,pp. 547-556
      63
      6E-stream: Evolution-based technique for stream clusteringUdommanetanakit K., Rakthanmanon T., Waiyamai K.2007Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
      4632 LNAI,pp. 605-615
      60
      7Discovering the intrinsic cardinality and dimensionality of time series using MDLHu B., Rakthanmanon T., Hao Y., Evans S., Lonardi S., Keogh E.2011Proceedings - IEEE International Conference on Data Mining, ICDM
      ,pp. 1086-1091
      39
      8MDL-based time series clusteringRakthanmanon T., Keogh E., Lonardi S., Evans S.2012Knowledge and Information Systems
      33(2),pp. 371-399
      35
      9A novel approximation to dynamic time warping allows anytime clustering of massive time series datasetsZhu Q., Batista G., Rakthanmanon T., Keogh E.2012Proceedings of the 12th SIAM International Conference on Data Mining, SDM 2012
      ,pp. 999-1010
      25
      10Efficient proper length time series motif discoveryYingchareonthawornchai S., Sivaraks H., Rakthanmanon T., Ratanamahatana C.2013Proceedings - IEEE International Conference on Data Mining, ICDM
      ,pp. 1265-1270
      23
      11Towards a minimum description length based stopping criterion for semi-supervised time series classificationBegum N., Hu B., Rakthanmanon T., Keogh E.2013Proceedings of the 2013 IEEE 14th International Conference on Information Reuse and Integration, IEEE IRI 2013
      ,pp. 333-340
      15
      12Rapid annotation of interictal epileptiform discharges via template matching under Dynamic Time WarpingJing J., Dauwels J., Rakthanmanon T., Keogh E., Cash S., Westover M.2016Journal of Neuroscience Methods
      274,pp. 179-190
      14
      13Towards never-ending learning from time series streamsHao Y., Chen Y., Zakaria J., Hu B., Rakthanmanon T., Keogh E.2013Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
      Part F128815,pp. 874-882
      13
      14A fast LSH-based similarity search method for multivariate time seriesYu C., Luo L., Chan L.L.H., Rakthanmanon T., Rakthanmanon T., Nutanong S.2019Information Sciences
      476,pp. 337-356
      13
      15Data mining a trillion time series subsequences under dynamic time warpingRakthanmanon T., Campana B., Mueen A., Batista G., Westover B., Zhu Q., Zakaria J., Keogh E.2013IJCAI International Joint Conference on Artificial Intelligence
      ,pp. 3047-3051
      12
      16A minimum description length technique for semi-supervised time series classificationBegum N., Hu B., Rakthanmanon T., Keogh E.2014Advances in Intelligent Systems and Computing
      263,pp. 171-192
      10
      17Using the minimum description length to discover the intrinsic cardinality and dimensionality of time seriesHu B., Rakthanmanon T., Hao Y., Evans S., Lonardi S., Keogh E.2015Data Mining and Knowledge Discovery
      29(2),pp. 358-399
      9
      18A general framework for never-ending learning from time series streamsChen Y., Hao Y., Rakthanmanon T., Zakaria J., Hu B., Keogh E.2015Data Mining and Knowledge Discovery
      29(6),pp. 1622-1664
      9
      19Image mining of historical manuscripts to establish provenanceHu B., Rakthanmanon T., Campana B., Mueen A., Keogh E.2012Proceedings of the 12th SIAM International Conference on Data Mining, SDM 2012
      ,pp. 804-815
      8
      20Mining historical documents for near-duplicate figuresRakthanmanon T., Zhu Q., Keogh E.2011Proceedings - IEEE International Conference on Data Mining, ICDM
      ,pp. 557-566
      8
      21A scalable framework for cross-lingual authorship identificationSarwar R., Li Q., Rakthanmanon T., Rakthanmanon T., Nutanong S.2018Information Sciences
      465,pp. 323-339
      8
      22Object-oriented database mining: use of object oriented concepts for improving data classification techniqueWaiyamai K., Songsiri C., Rakthanmanon T.2004Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
      3036,pp. 303-309
      6
      23Establishing the provenance of historical manuscripts with a novel distance measureHu B., Rakthanmanon T., Campana B.J.L., Mueen A., Keogh E.2015Pattern Analysis and Applications
      18(2),pp. 313-331
      6
      24A scalable framework for stylometric analysis of multi-author documentsSarwar R., Yu C., Nutanong S., Urailertprasert N., Vannaboot N., Rakthanmanon T., Rakthanmanon T.2018Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
      10827 LNCS,pp. 813-829
      6
      25Single Channel ECG for Obstructive Sleep Apnea Severity Detection Using a Deep Learning ApproachBanluesombatkul N., Rakthanmanon T., Rakthanmanon T., Wilaiprasitporn T.2019IEEE Region 10 Annual International Conference, Proceedings/TENCON
      2018-October,pp. 2011-2016
      5
      26An effective and scalable framework for authorship attribution query processingSarwar R., Yu C., Tungare N., Tungare N., Chitavisutthivong K., Sriratanawilai S., Xu Y., Chow D., Rakthanmanon T., Rakthanmanon T., Nutanong S.2018IEEE Access
      6,pp. 50030-50048
      4
      27SE-Stream: Dimension projection for evolution-based clustering of high dimensional data streamsChairukwattana R., Kangkachit T., Rakthanmanon T., Waiyamai K.2014Advances in Intelligent Systems and Computing
      245,pp. 365-376
      4
      28Efficiently finding near duplicate figures in archives of historical documentsRakthanmanon T., Zhu Q., Keogh E.2012Journal of Multimedia
      7(2),pp. 109-123
      4
      29AC-Stream: Associative classification over data streams using multiple class association rulesSaengthongloun B., Kangkachit T., Rakthanmanon T., Waiyamai K.2013Proceedings of the 2013 10th International Joint Conference on Computer Science and Software Engineering, JCSSE 2013
      ,pp. 223-228
      3
      30Concept lattice-based mutation control for reactive motifs discoveryWaiyamai K., Liewlom P., Kangkachit T., Rakthanmanon T.2008Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
      5012 LNAI,pp. 767-776
      3
      31SED-Stream: Discriminative dimension selection for evolution-based clustering of high dimensional data streamsWaiyamai K., Kangkachit T., Rakthanmanon T., Chairukwattana R.2014International Journal of Intelligent Systems Technologies and Applications
      13(3),pp. 187-201
      3
      32Towards discovering the intrinsic cardinality and dimensionality of time series using MDLHu B., Rakthanmanon T., Hao Y., Evans S., Lonardi S., Keogh E.2013Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
      7070 LNAI,pp. 184-197
      3
      33Efficient evolution-based clustering of high dimensional data streams with dimension projectionChairukwattana R., Kangkachit T., Rakthanmanon T., Waiyamai K.20132013 International Computer Science and Engineering Conference, ICSEC 2013
      ,pp. 185-190
      3
      34Clustering of symbols using minimal description lengthTataw O.M., Rakthanmanon T., Keogh E.J.2013Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
      ,pp. 180-184
      3
      35StyloThai: A scalable framework for stylometric authorship identification of Thai documentsSarwar R., Porthaveepong T., Rutherford A., Rakthanmanon T., Rakthanmanon T., Nutanong S.2020ACM Transactions on Asian and Low-Resource Language Information Processing
      19(3)
      3
      36CAG : Stylometric Authorship Attribution of Multi-Author Documents Using a Co-Authorship GraphSarwar R., Urailertprasert N., Vannaboot N., Yu C., Rakthanmanon T., Chuangsuwanich E., Nutanong S.2020IEEE Access
      8,pp. 18374-18393
      2
      37Semi-supervised stream clustering using labeled data pointsTreechalong K., Rakthanmanon T., Waiyamai K.2015Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
      9166,pp. 281-295
      2
      38Prediction of enzyme class by using reactive motifs generated from binding and catalytic sitesLiewlom P., Rakthanmanon T., Waiyamai K.2007Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
      4632 LNAI,pp. 442-453
      2
      39Using rule order difference criterion to decide whether to update class association rulesKongubol K., Rakthanmanon T., Waiyamai K.2010Studies in Computational Intelligence
      283,pp. 241-252
      1
      40Searching historical manuscripts for near-duplicate figuresRakthanmanon T., Zhu Q., Keogh E.2011ACM International Conference Proceeding Series
      ,pp. 14-21
      1
      41ACCD: Associative classification over concept-drifting data streamsWaiyamai K., Kangkachit T., Saengthongloun B., Rakthanmanon T.2014Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
      8556 LNAI,pp. 78-90
      1
      42Native Language Identification of Fluent and Advanced Non-Native WritersSarwar R., Rutherford A.T., Hassan S.U., Rakthanmanon T., Nutanong S.2020ACM Transactions on Asian and Low-Resource Language Information Processing
      19(4)
      1
      43Hierarchical multi-label associative classification for protein function prediction using gene ontologySangsuriyun S., Rakthanmanon T., Waiyamai K.2019Chiang Mai Journal of Science
      46(1),pp. 165-179
      0
      44Evolution and affinity-propagation based approach for data stream clusteringSunmood A., Rakthanmanon T., Rakthanmanon T., Waiyamai K.2018ACM International Conference Proceeding Series
      ,pp. 97-101
      0
      45Information gain Aggregation-based Approach for Time Series Shapelets DiscoveryKramakum C., Rakthanmanon T., Rakthanmanon T., Waiyamai K.2018Proceedings of 2018 10th International Conference on Knowledge and Systems Engineering, KSE 2018
      ,pp. 97-101
      0
      46Object-oriened Data Mining System: A Tightly-coupled Association Rule Discovery from Object-oriented DatabasesRakthanmanon T., Songsiri C., Waiyamai K.2003Proceedings of 41st Kasetsart University Annual Conference
      ,pp. 296-306
      0
      47Classification model with subspace data-dependent ballsKlakhaeng N., Kangkachit T., Rakthanmanon T., Waiyamai K.2013Proceedings of the 2013 10th International Joint Conference on Computer Science and Software Engineering, JCSSE 2013
      ,pp. 211-216
      0