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

    2-level classificationaffinity propagation clusteringApplication scenarioApproximation AlgorithmApproximation methodsArtificial intelligenceassociative classificationattribute clusteringAuthor 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 inhibitorsCorrosion PredictionCross-lingualCyber forensicCyber forensicsData acquisitionData clusteringData communication systemsData handlingData MiningData ProcessingData representation modelsData streamData Streamsdata streams classificationData structuresdata summarizationDatabase systemsDecision MakingDecision treesDeep LearningDetermine dataDimensionality reductiondiscriminative dimension selectionDynamic rule updatingDynamic Time WarpingElectrocardiographyFeature extractionForestryFully connected neural networkGraphical user interfaceHand LandmarkhierarchicalHier-archical clusteringHigh dimensional data streamsIncremental associative classificationIncremental data databasesIndexingInformation GainInterictal dischargesJob analysisK fold cross validationsLearning systemsLong 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 extractiontext classificationTextureThai authorshipThai fingerspellingTime SeriesTime series analysisTime Series MiningTime Series ShapeletsTop-of-lien corrosionTrees (mathematics)

    Interest

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

    Administrative Profile

    • มิ.ย. 2565 - ปัจจุบัน รองหัวหน้าภาควิชา คณะวิศวกรรมศาสตร์ ภาควิชาวิศวกรรมคอมพิวเตอร์

    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 40 เรื่อง (ตีพิมพ์ในวารสารวิชาการ 23 เรื่อง, นำเสนอในการประชุม/สัมมนา 17 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 (88)

    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
    700
    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
    291
    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)
    149
    4Time 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
    83
    5Beyond 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
    79
    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
    72
    7MDL-based time series clusteringRakthanmanon T., Keogh E., Lonardi S., Evans S.2012Knowledge and Information Systems
    33(2),pp. 371-399
    43
    8Discovering 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
    43
    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
    29
    10Single 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
    25
    11Efficient proper length time series motif discoveryYingchareonthawornchai S., Sivaraks H., Rakthanmanon T., Ratanamahatana C.2013Proceedings - IEEE International Conference on Data Mining, ICDM
    ,pp. 1265-1270
    24
    12A 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
    21
    13Rapid 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
    21
    14Towards 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
    21
    15Towards 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
    20
    16A 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
    20
    17Data 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
    18
    18A scalable framework for cross-lingual authorship identificationSarwar R., Li Q., Rakthanmanon T., Rakthanmanon T., Nutanong S.2018Information Sciences
    465,pp. 323-339
    16
    19A 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
    14
    20Using 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
    12
    21CAG : 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
    12
    22A 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
    10
    23An 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
    9
    24StyloThai: 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)
    8
    25Image 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
    26Mining historical documents for near-duplicate figuresRakthanmanon T., Zhu Q., Keogh E.2011Proceedings - IEEE International Conference on Data Mining, ICDM
    ,pp. 557-566
    8
    27Object-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
    28Establishing 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
    29Efficiently finding near duplicate figures in archives of historical documentsRakthanmanon T., Zhu Q., Keogh E.2012Journal of Multimedia
    7(2),pp. 109-123
    5
    30Native 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)
    5
    31SE-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
    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
    4
    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
    4
    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
    35SED-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
    36Semi-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
    3
    37AC-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
    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
    3
    39Concept 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
    40ACCD: 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
    2
    41Using 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
    42Searching historical manuscripts for near-duplicate figuresRakthanmanon T., Zhu Q., Keogh E.2011ACM International Conference Proceeding Series
    ,pp. 14-21
    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
    1
    44Thai Fingerspelling Recognition Using Hand Landmark ClusteringPhothiwetchakun W., Rakthanmanon T.2021ICSEC 2021 - 25th International Computer Science and Engineering Conference
    ,pp. 256-261
    1
    45Top-of-line corrosion via physics-guided machine learning: A methodology integrating field data with theoretical modelsSilakorn P., Jantrakulchai N., Wararatkul N., Wanwilairat S., Kangkachit T., Techapiesancharoenkij R., Rakthanmanon T., Hanlumyuang Y.2022Journal of Petroleum Science and Engineering
    215
    0
    46AutoShapelet: Reconstructable Time Series ShapeletsAjchariyasakchai P., Rakthanmanon T.20202020 24th International Computer Science and Engineering Conference, ICSEC 2020
    0
    47Entropy-based attribute clusteringKhomprasert A., Rakthamanon T., Waiyamai K.2019ECTI DAMT-NCON 2019 - 4th International Conference on Digital Arts, Media and Technology and 2nd ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering
    ,pp. 230-233
    0
    48Estimation of ethylene/1-butene copolymerization conditions using the autoencoder modelAmnuaykijvanit O., Anantawaraskul S., Rakthanmanon T.2022Journal of Physics: Conference Series
    2175(1)
    0
    49Evolution 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
    50Information 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
    51Object-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
    52Classification 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