Arno Knobbe
Associate professor
- Name
- Dr. A.J. Knobbe
- Telephone
- +31 71 527 8919
- a.j.knobbe@liacs.leidenuniv.nl
- ORCID iD
- 0000-0002-0335-5099
Arno Knobbe is a senior researcher at the LIACS, and head of the Data Mining group. For more infomation see his personal webpage below.
PhD Candidates
News
-
Measuring skate provides insight into ice-skating technique -
Growing super legs for the Tour de France with the aid of Leiden data science -
Sport Data Center appointed as Certified Partner of Sportinnovator -
New online national platform Sport Data Valley connects science and sport -
Will wind turbines take the long track speedskaters to gold? -
Data analysis is really helping the Dutch national women’s football team -
Wijnhaven: where you can get to know the world -
SewerSense: automatic measuring within the sewer system -
The Netherlands-Brazil: 1-1 -
Leiden researchers win public award in Smartest Project contest -
Data science and sports: a winning combination -
Using sensors to measure playground dynamics
See also
Associate professor
- Science
- Leiden Inst of Advanced Computer Science
- Leeuw A.W. de, Heijboer M., Verdonck T., Knobbe A.J. & Latre S. (2023), Exploiting sensor data in professional road cycling: personalized data-driven approach for frequent fitness monitoring, Data Mining and Knowledge Discovery 37: 1125-1153.
- Paraschiakos S., Sá C.R. de, Okai J., Slagboom P.E., Beekman M. & Knobbe A.J. (2022), A recurrent neural network architecture to model physical activity energy expenditure in older people, Data Mining and Knowledge Discovery 36: 477.
- Leeuw A.W. de, Zwaard S. van der, Baar R. van & Knobbe A.J. (2022), Personalized machine learning approach to injury monitoring in elite volleyball players, European Journal of Sport Science 22(4): 511-520.
- Meijer D.W.J., Luimes R., Knobbe A.J. & Bäck T.H.W. (2022), Anomaly detection in urban drainage with stereovision, Automation in Construction 139: 104285.
- Dwyer D.B., Kempe M. & Knobbe A.J. (2022), Editorial: using artificial intelligence to enhance sport performance, Frontiers in Sports and Active Living 4: 886730.
- Leeuw A.W. de, Baar R. van., Knobbe A.J. & Zwaard S. van der (2022), Modeling match performance in elite volleyball players: importance of jump load and strength training characteristics, Sensors 22(20): 7996.
- Goes F.R., Meerhoff L.A., Bueno M.J.O., Rodrigues D.M., Moura F.A., Brink M.S., Elferink-Gemser M.T., Knobbe A.J., Cunha S.A., Torres R.S. & Lemmink K.A.P.M. (2021), Unlocking the potential of big data to support tactical performance analysis in professional soccer: A systematic review, European Journal of Sport Science 21(4): 481-496.
- Paraschiakos S., Cachucho R.E., Moed M., Heemst D. van, Mooijaart S.P., Slagboom E.P., Knobbe A.J. & Beekman M. (2020), Activity recognition using wearable sensors for tracking the elderly, User Modeling and User-Adapted Interaction 30: 567-605.
- Okai J., Paraschiakos S., Beekman M., Knobbe A.J. & Rebelo de Sá C. (2019), Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks, 41st Annual international conference of the IEEE engineering in medicine and biology society (EMBC). 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'19) 23 July 2019 - 27 July 2019: IEEE. 2486-2491.
- Pinho Rebelo Sá S.F. de, Azevedo P., Soares C., Jorge A.M. & Knobbe A.J. (2018), Preference rules for label ranking: Mining patterns in multi-target relations, Information Fusion 40: 112-125.
- Leeuw A. de, Meerhoff L.A. & Knobbe A.J. (2018), Effects of pacing properties on performance in long-distance running, Big Data 6(4): 248-261.
- Pinho Rebelo de Sá C.F., Duivesteijn W., Azevedo P.J., Jorge A.M., Soares C. & Knobbe A.J. (2018), Discovering a taste for the unusual: exceptional models for preference mining, Machine Learning 107(11): 1775-1807.
- De Gouveia da Costa Cachucho R.E., Paraschiakos S., Liu K., Burgh B. van der & Knobbe A.J. (2018), ClaRe: Classification and Regression Tool for Multivariate Time Series. Brefeld U., Curry E., Daly E., MacNamee B., Marascu A., Pinelli F., Berlingerio M. & Hurley N. (Eds.), Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part III. Joint European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD) 10 September 2018 - 14 September 2018 no. Lecture Notes in Computer Science, volume 11053. Cham: Springer. 682-686.
- Veiga G., Ketelaar L., Leng W. de, De Gouveia da Costa Cachucho R.E., Kok J.N., Knobbe A.J., Neto C. & Rieffe C. (2017), Social Competence at the Playground: Preschoolers During Recess. Infant and Child Development, Infant and Child Development 26(1): e1957.
- Veiga G., Ketelaar L., De Leng W., Cachucho R., Kok J.N., Knobbe A.J., Neto C. & Rieffe C. (2017), Alone at the Playground, European Journal of Developmental Psychology 14(1): 44-61.
- Pinho Rebelo de Sa C.F., Soares C., Knobbe A.J. & Cortez P. (2017), Label Ranking Forests, Expert Systems 34(1): e12166.
- Knobbe A.J., Orie J., Hofman N., Burgh B. van der & De Gouveia da Costa Cachucho R.E. (2017), Sports analytics for professional speed skating, Data Mining and Knowledge Discovery 31(6): 1872-1902.
- Pinho Rebelo de Sá C.F., Soares C. & Knobbe A.J. (2016), Entropy-based discretization methods for ranking data, Information Sciences 329: 921-936.
- Miao S., Vespier U., De Gouveia da Costa Cachucho R.E., Meeng M. & Knobbe A.J. (2016), Predefined pattern detection in large time series, Information Sciences 329: 950–964.
- Cachucho R., Liu K., Nijssen S. & Knobbe A.J. (2016), Bipeline: a Web-based Visual Tool for Biclustering of Multivariate Time Series (demo). Berendt B., Bringmann B., Fromont É., Garriga G., Miettinen P., Tatti N. & Tresp V. (Eds.), Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part III. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases edition no. 9853. Heidelberg: Springer International Publishers. 12-17.
- Pinho Rebelo de Sá C.F., Duivesteijn W., Soares C. & Knobbe A. (2016), Exceptional Preferences Mining. Calders T., Ceci M. & Malerba D. (Eds.), Discovery Science. 19th International Conference on Discovery Science (DS 2016) 19 October 2016 - 21 October 2016 no. LNCS 9956. Cham: Springer. 3-18.
- Miao S., Koenders E. & Knobbe A.J. (2015), Automatic Baseline Correction of Strain Gauge Signals, Structural Control and Health Monitoring 22(1): 36-49.
- Pinho Rebelo de Sá C.F., Soares C. & Knobbe A.J. (2015), Distance-based Decision Tree Algorithms for Label Ranking. Pereira F., Machado P., Costa E. & Cardoso A. (Eds.), Progress in Artificial Intelligence (EPIA 2015). Progress in Artificial Intelligence - 17th Portugese Conference on Artificial Intelligence (EPIA 2015) 8 September 2015 - 11 September 2015 no. LNCS 9273. Cham: Springer. 525-534.
- Georgala K., Burgh B. van der, Meeng M. & Knobbe A.J. (2015), Record Linkage in Medieval and Early Modern Text. In: Bloothooft G., Christen P., Mandemakers K. & Schraagen M. (Eds.), Population Reconstruction. Cham: Springer. 173-195.
- Mampaey M., Nijssen S.G.R., Feelders A., Konijn R. & Knobbe A.J. (2015), Efficient algorithms for finding optimal binary features in numeric and nominal labeled data, Knowledge and Information Systems 42(2): 465-492.
- Konijn R.M., Duivesteijn W., Meeng M. & Knobbe A.J. (2015), Cost-based quality measures in subgroup discovery, Journal of Intelligent Information Systems 45(3): 337-355.
- Pinho Rebelo de Sá C.F., Soares C. & Knobbe A.J. (2015), Permutation Tests for Label Ranking, Proceedings of the 27th Benelux Conference on Artificial Intelligence (BNAIC 2015). The 27th Benelux Conference on Artificial Intelligence (BNAIC 2015) 5 November 2015 - 6 November 2015.
- Vanschoren J., Vespier U., Miao S., Meeng M., De Gouveia da Costa Cachucho R.E. & Knobbe A.J. (2014), Large-scale sensor network analysis - Applications in structural health monitoring, in Big Data Management, Technologies, and Applications. In: , Big Data Management, Technologies, and Applications: IGI Global. 314-347.
- Meeng M., Duivesteijn W. & Knobbe A.J. (2014), ROCsearch - An ROC-guided Search Strategy for Subgroup Discovery. Zaki M., Obradovic Z., Tan P.N., Banerjee A., Kamath C. & Parthasarathy S. (Eds.), Proceedings of the 2014 SIAM International Conference on Data Mining. 2014 SIAM International Conference on DATA MINING 24 April 2014 - 26 April 2014: SIAM. 704-712.
- Duivesteijn W., Meeng M. & Knobbe A.J. (2014), ROCsearch in a Wider Context - A ROC-Guided Search Strategy for Subgroup Discovery and Beyond, Proceedings First International Workshop on Learning over Multiple Contexts (LMCE 2014). .
- Vries H. de, Azzopardi G., Koelewijn A. & Knobbe A.J. (2014), Parametric Nonlinear Regression Models for Dike Monitoring Systems, Proceedings IDA 2014. 345-355.
- De Gouveia da Costa Cachu R.E., Meeng M., Vespier U., Nijssen S.G.R. & Knobbe A.J. (2014), Mining multivariate time series with mixed sampling rates, UbiComp '14: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. UbiComp '14: The 2014 ACM Conference on Ubiquitous Computing 13 September 2014 - 17 September 2017. New York, NY, U.S.A.: ACM. 413-423.
- Knobbe A.J., Meeng M., Vanschoren J., Rees Jones S. & Merlo Penning S. (2014), Reconstructing Medieval Social Networks from English and Latin Charters, Proceedings Population Reconstruction 2014. .
- Meeng M., Duivesteijn W. & Knobbe A.J. (2014), ROCsearch - An ROC-Guided Search Strategy for Subgroup Discovery, Proceedings of the 16th LWA Workshops: KDML, IR and FGWM. : CEUR. 180.
- Witteveen J., Duivesteijn W., Knobbe A.J. & Grünwald P. (2014), RealKrimp - Finding Hyperintervals that Compress with MDL for Real-Valued Data, Proceedings IDA 2014. 368-379.
- Jon N., Flach P., Wilcox T., Sellman R., Thumim J. & Knobbe A.J. (2014), Subgroup Discovery in Smart Electricity Meter Data, IEEE Transactions in Industrial Informatics 10(2): 1327-1336.
- Miao S., Veerman R.P., Koenders E. & Knobbe A.J. (2013), Modal Analysis of a Concrete Highway Bridge - Structural Calculations and Vibration-Based Results, Proceedings 6th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-6 2013). .
- Veerman R.P., Miao S., Koenders E. & Knobbe A.J. (2013), Data-Intensive Structural Health Monitoring in the InfraWatch Project,, Proceedings 6th International Conference on Structural Health Monitoring of Intelligent Infrastructure (SHMII-6 2013). .
- Konijn R.M., Duivesteijn W., Meeng M. & Knobbe A.J. (2013), Cost-based Quality Measures in Subgroup Discovery, Proceedings Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD Revised Selected Papers. no. Lecture Notes in Computer Science 404-415.
- Konijn R.M., Duivesteijn W., Kowalczyk W.J. & Knobbe A.J. (2013), Discovering Local Subgroups, with an Application to Fraud Detection, Proceedings of Advances in Knowledge Discovery and Data Mining, 17th Pacific-Asia Conference (PAKDD 2013). no. Lecture Notes in Computer Science 1-12.
- Miao S., Vespier U., Vanschoren J., Knobbe A.J. & De Gouveia da Costa Cachucho R.E. (2013), Modeling Sensor Dependencies between Multiple Sensor Types, Proceedings BENELEARN 2013. .
- Miao S. & Knobbe A.J. (2013), Traffic events identification with a sensor network on a dutch highway bridge, Proceedings BENELEARN 2013. .
- Miao S., Knobbe A.J., Koenders E. & Bosma C. (2013), Analysis of Traffic Effects on a Dutch Highway Bridge, Proceedings IABSE Conference on Assessment, Upgrading and Refurbishment of Infrastructures. .
- Pinho Rebelo de Sa C.F., Soares C. & Knobbe A.J. (2013), Multi-Interval Discretization of Continuous Attributes for Label Ranking, Proceedings 16th International Conference on Discovery Science. no. Lecture Notes in Computer Science: Springer-Verlag. 155-169.
- Vespier U., Nijssen S.G.R. & Knobbe A.J. (2013), Mining characteristic multi-scale motifs in sensor-based time series. He Q., Iyengar A., Nejdl W., Pei J. & Rastogi R. (Eds.), Proceedings 22nd ACM International Conference on Information and Knowledge Management (CIKM'13). : ACM. 2393-2398.
- Lohuis P.J.F.M., Faraj-Hakim S., Duivesteijn W., Knobbe A.J. & Tasman A.-J. (2013), Benefits of a Short, Practical Questionnaire to Measure Subjective Perception of Nasal Appearance under Aesthetic Rhinoplasty, Plastic and Reconstructive Surgery 132(6): 913e-923e.
- Ribeiro G., Duivesteijn W., Soares C. & Knobbe A. (2012), Multilayer Perceptron for Label Ranking, Proceedings ICANN 2012. 25-32.
- Leeuwen Matthijs van & Knobbe A. (2012), Diverse Subgroup Set Discovery, Data Mining and Knowledge Discovery (special issue best of ECML PKDD 2011). .
- Duivesteijn W., Feelders A. & Knobbe A. (2012), Different Slopes for Different Folks - Mining for Exceptional Regression Models with Cook's Distance, Proceedings KDD 2012. 868-876.
- Vespier U., Knobbe A., Nijssen S. & Vanschoren J. (2012), MDL-based Identification of Relevant Temporal Scales in Time Series, Proceedings WITMSE 2012. .
- Mampaey M., Nijssen S., Feelders A. & Knobbe A. (2012), Efficient Algorithms for Finding Richer Subgroup Descriptions in Numeric and Nominal Data, Proceedings ICDMD 2012. .
- Duivesteijn W., Loza Mencia E., Fürnkranz J. & Knobbe A. (2012), Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns, Proceedings IDA 2012. 114-125.
- Vespier U., Knobbe A., Nijssen S. & Vanschoren J. (2012), MDL-based Analysis of Time Series at Multiple Time-Scales, Proceedings ECML PKDD 2012. 371-386.
- Lohuis P.J.F.M., Hakim S., Knobbe A., Duivesteijn W. & Bran G.M. (2012), Split hump technique for reduction of the overprojected nasal dorsum - a statistical analysis on subjective body image in relation to nasal appearance and nasal patency in 97 aesthetic rhinoplasty patients, Archives of Facial Plastic Surgery 14(5): 346-353.
- Knobbe A., Feelders A. & Leman D. (2011), Exceptional Model Mining. In: Holmes D. & Jain L. (Eds.), Data Mining: Foundations and Intelligent Paradigms 2: Springer. 183-198.
- Miao S., Knobbe A., Vanschoren J., Vespier U., Koopman A., Cachucho R. & Chen Xiaoyun (2011), A Range of Data Mining Techniques to Correlate Multiple Sensor Types, Proceedings Dutch-Belgian Database Day. .
- Cachucho R. & Knobbe A. (2011), A Hierarchical Approach for Activity Recognition from Accelerometer Data Stream, Proceedings Dutch-Belgian Database Day. .
- Vespier U., Knobbe A., Vanschoren J. & Miao S. (2011), InfraWatch: modeling bridge behavior by event recognition in sensor measurements, Proceedings SMiLee 2010. .
- Leeuwen M. (Matthijs) & Knobbe A. (2011), Non-Redundant Subgroup Discovery in large and Complex Data, Proceedings Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2011). 459.
- Vespier U., Knobbe A., Vanschoren J., Miao S., Koopman A., Obladen B. & Bosma C. (2011), Traffic Events Modeling for Structural Health Monitoring, Advances in Intelligent Data Analysis X - 10th International Symposium, IDA 2011. : Springer. 376-387.
- Cachucho R., Knobbe A., Moreira J.M. & Gama J. (2011), Towards a Semi-Supervised Classifier for Activity Recognition from Accerelometer Data, PhD Spotlight Session late-breaking results, IDA 2011. .
- Meeng M. & Knobbe A. (2011), Flexible Enrichment with Contata (Software Demo), Proceedings 20th Annual Belgian-Dutch Conference on Machine Learning (BENELEARN 2011). 117-120.
- Meeng M., Knobbe A., Hoen P.-B. 't & Willems van Dijk K. (2011), Literature-Based Enrichment of Experimental Results (Software Demo), Proceedings International Symposium on Integrative Bioinformatics 2011. .
- Kok J.N., Knobbe A., Blockeel H., Obladen B. & Koenders E. (2011), Large Data Stream Processing for Bridge Management Systems, Proceedings First Middle East Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures (SMAR 2011). .
- Duivesteijn W. & Knobbe A. (2011), Exploiting False Discoveries - Statistical Validation of Patterns and Quality Measures in Subgroup Discovery, Proceedings IEEE International Conference on Data Mining (ICDM 2011). .
- Knobbe A., Hoogestijn P. & Kingma D. (2011), A Feature Construction and Classification Approach to Pixel Annotation, Proceedings 20th Annual Belgian-Dutch Conference on Machine Learning (BENELEARN 2011). 69-79.
- Hakim S., Knobbe A., Duivesteijn W. & Lohuis P.J.F.M. (2010), Results of a screening questionnaire measuring physical perception of patients undergoing esthetic rhinoplasty: a statistical analysis, Journal of Laryngology and Otology 2: 100-100.
- Fürnkranz J. & Knobbe A. (2010), Special Issue: Global Modeling Using Local Patterns. Heidelberg Berlin: Springer.
- Meeng M., Knobbe A., Koopman A., Klinken J.B. & Berg S.A.A. van den (2010), Equation Discovery for Whole-Body Metabolism Modelling, Proceedings Machine Learning in Systems Biology 2010 (MLSB 2010). .
- Knobbe A., Blockeel H., Koopman A., Calders T., Obladen Bas, Bosma C., Galenkamp H., Koenders E. & Kok J.N. (2010), InfraWatch: Data management of large systems for monitoring infrastructural performance, Intelligent Data Analysis (IDA). IDA: Springer. 91-102.
- Pieters B., Knobbe A. & Dzeroski S. (2010), Subgroup Discovery in Ranked Data, with an Application to Gene Set Enrichment, Proceedings Preference Learning workshop (PL 2010) at ECML PKDD 2010. .
- Duivesteijn W., Knobbe A. & Feelders A. (2010), Subgroup Discovery meets Bayesian networks: an Exceptional Model Mining approach, Proceedings ICDM 2010. .
- Koopman A., Knobbe A. & Meeng M. (2010), Pattern Selection Problems in Multivariate Time-Series using Equation Discovery. Vreeken J., Tatti N. & Goethals B. (Eds.), UP'10: Proceedings of the ACS SIGKDD Workshop on Useful Patterns. ACM SIGKDD Workshop on Useful Patterns 25 July 2010 - 25 July 2010. New York, NY, U.S.A.: Assocation for Computing Machinery. 74-81.
- Fuernkranz J. & Knobbe A. (Eds.) (2010), . Data Mining and Knowledge Discovery.
- Knobbe A., Koopman A., Kok J.N., Obladen B., Bosma C. & Galenkamp H. (2010), The Role of Fielded Applications in Machine Learning Education, Proceedings 20th Belgian Dutch Conference on Machine Learning (BENELEARN) : .
- Knobbe A. & Fuernkranz J. (2009), From Local Patterns to Global Models: Proceedings of the ECML PKDD 2009 Workshop. Heidelberg: Springer.
- Frank R., Ester M. & Knobbe A. (2009), A Multi-Relational Approach to Spatial Classification, Proceedings KDD 2009. .
- Knobbe A. & Valkonet J. (2009), Building Classifiers from Pattern Teams, From Local Patterns to Global Models: Proceedings of the ECML PKDD 2009 Workshop. 77-93.
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