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People: Prof. Dr. Dr. Lars Schmidt-Thieme
office hour:
C203, upon request
Phone, Fax, Email:
phone:+49 5121 / 883-40360
fax:+49 5121 / 883-40361
e-mail:
Postal address:
Information Systems and Machine Learning Lab
Universitätsplatz 1
University of Hildesheim
31141 Hildesheim
Germany
Visitor address:
Information Systems and Machine Learning Lab
Samelsonplatz 1
University of Hildesheim
31141 Hildesheim
Germany

Publications:
Books:

  • Myra Spiliopoulou, Lars Schmidt-Thieme, Ruth Janning (eds., 2014):
    Data Analysis, Machine Learning and Knowledge Discovery, Springer.
  • Leandro Balby Marinho, Andreas Hotho, Robert Jäschke, Alexandros Nanopoulos, Steffen Rendle, Lars Schmidt-Thieme, Gerd Stumme, Panagiotis Symeonidis (2011):
    Recommender Systems for Social Tagging Systems, Springer.
  • Wolfgang Gaul, Andreas Geyer-Schulz, Lars Schmidt-Thieme, Jonas Kunze (eds., 2012):
    Challenges at the Interface of Data Analysis, Computer Science, and Optimization., Springer.
  • Lawrence Bergman, Alex Tuzhilin, Robin Burke, Alexander Felfernig, Lars Schmidt-Thieme (eds., 2009):
    RecSys '09: Proceedings of the Third ACM Conference on Recommender Systems, New York, NY, USA, ACM.
  • Christine Preisach, Hans Burkhardt, Lars Schmidt-Thieme, Reinhold Decker (eds., 2008):
    Data Analysis, Machine Learning and Applications, Springer.
  • Daniel Baier, Reinhold Decker, Lars Schmidt-Thieme (eds., 2005):
    Data Analysis and Decision Support, Springer.
  • Lars Schmidt-Thieme (2003):
    Assoziationsregel-Algorithmen für Daten mit komplexer Struktur - mit Anwendungen im Web Mining, Frankfurt am Main.
  • Martin Schader, Lars Schmidt-Thieme (2003):
    Java, Eine Einführung, Springer, 4th edition.
  • Lars Schmidt-Thieme (2000):
    Die Gestaltung von Exposition und Reprise in den Streichquartetten Haydns, Frankfurt am Main.
Journal Papers:
  • Josif Grabocka, Nicolas Schilling, Lars Schmidt-Thieme (2016):
    Latent Time-Series Motifs, ACM Transactions on Knowledge Discovery from Data, TKDD journal. PDF
  • Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme (2015):
    Perceived Task-Difficulty Recognition from Log-file Information for the Use in Adaptive Intelligent Tutoring Systems, Springer.
  • Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme (2015):
    Fast Classification of Univariate and Multivariate Time series Through Shapelets Discovery, Journal of Knowledge and Information Systems, 5-year average impact factor 2.02. PDF
  • Rasoul Karimi, Alexandros Nanopoulos, Lars Schmidt-Thieme (2015):
    A Supervised Active Learning Framework for Recommender Systems based on Decision Trees, User Modeling and User-Adapted Interaction (UMUAI), Springer-Verlag, 2015, Volume 25, Issue 1, pp 39-64, ISI/Thomson Impact Factor 3.037. (The final publication is available at link.springer.com ) . PDF
  • Josif Grabocka, Martin Wistuba, Lars Schmidt-Thieme (2014):
    Scalable Classification of Repetitive Time Series Through Frequencies of Local Polynomials, IEEE Transactions on Knowledge and Data Engineering, 5-year average impact 2.87. PDF
  • Josif Grabocka, Lars Schmidt-Thieme (2014):
    Invariant Time-Series Factorization, Journal of Data Mining and Knowledge Discovery, 5-year average impact factor 2.77. PDF
  • Josif Grabocka, Lars Schmidt-Thieme (2014):
    Learning Through Non-linearly Supervised Dimensionality Reduction, Springer Transactions on Large-Scale Data- and Knowledge-Centered Systems, LNCS. PDF
  • Ruth Janning, Andre Busche, Tomas Horvath, Lars Schmidt-Thieme (2013):
    Buried Pipe Localization Using an Iterative Geometric Clustering on GPR Data, Springer Artificial Intelligence Review. PDF
  • Alexander Felfernig, Gerhard Friedrich, Lars Schmidt-Thieme (guest eds., 2007):
    IEEE Intelligent Systems Special Issue on Recommender Systems, IEEE Computer Society.
Articles:
  • Nghia Duong-Trung, Nicolas Schilling, Lucas Rego Drumond, Lars Schmidt-Thieme (2016):
    Matrix Factorization for Near Real-time Geolocation Prediction in Twitter Stream, in Proceedings of Knowledge Discovery, Data Mining and Machine Learning (KDML 2016), Potsdam, Germany. PDF
  • Nghia Duong-Trung, Nicolas Schilling, Lars Schmidt-Thieme (2016):
    Near Real-time Geolocation Prediction in Twitter Streams via Matrix Factorization Based Regression, in Proceedings of ACM International Conference on Information and Knowledge Management (CIKM 2016), Indianapolis, USA. PDF
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2016):
    Two-Stage Transfer Surrogate Model for Automatic Hyperparameter Optimization, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'16), Riva del Garda, Italy.
  • Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme (2016):
    Scalable Hyperparameter Optimization with Products of Gaussian Process Experts, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'16), Riva del Garda, Italy.
  • Mit Shah, Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme (2016):
    Learning DTW-Shapelets for Time-Series Classification, in ACM IKDD Conference on Data Science. Best Paper Award. PDF
  • Umer Khan, Alexandros Nanopoulos, Lars Schmidt-Thieme (2016):
    Collaborative SVM Classification in Skewed Peer-to-Peer Networks, in SIAM International Conference on Data Mining - 3rd Workshop on Mining Networks and Graphs: A Big Data Analytic Challenge (SDM-Networks 2016), Miami, USA.
  • Carlotta Schatten, Lars Schmidt-Thieme (2016):
    Student Progress Modeling with skills deficiency aware Kalman Filters, in Proceedings of the 8th International Conference on Computer Supported Education (www.csedu.org), Springer.
  • Nghia Duong-Trung, Martin Wistuba, Lucas Rego Drumond, Lars Schmidt-Thieme (2015):
    Geo_ML@MediaEval Placing Task 2015, in Proceedings of the MediaEval 2015 Multimedia Benchmark Workshop, Wurzen, Germany. PDF
  • Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme (2015):
    Comparing Prediction Models for Active Learning in Recommender systems, in Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML), Trier, Germany. PDF
  • Nicolas Schilling, Martin Wistuba, Lucas Drumond, Lars Schmidt-Thieme (2015):
    Joint Model Choice and Hyperparameter Optimization with Factorized Multilayer Perceptrons, in 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2015), Vietri sul Mare, Italy. PDF
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2015):
    Sequential Model-free Hyperparameter Tuning, in Proceedings of IEEE International Conference on Data Mining (ICDM'15), Atlantic City, NJ, USA. Acceptance Rate: 18.2% (147 out of 807). PDF
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2015):
    Learning Hyperparameter Optimization Initializations, in Proceedings of IEEE International Conference on Data Science and Advanced Analytics (DSAA'15), Paris, France. PDF
  • Nicolas Schilling, Martin Wistuba, Lucas Drumond, Lars Schmidt-Thieme (2015):
    Hyperparameter Optimization with Factorized Multilayer Perceptrons, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'15), Porto, Portugal. PDF
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2015):
    Hyperparameter Search Space Pruning - A New Component for Sequential Model-Based Hyperparameter Optimization, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'15), Porto, Portugal. PDF
  • Martin Wistuba, Nicolas Schilling, Lars Schmidt-Thieme (2015):
    Learning Data Set Similarities for Hyperparameter Optimization Initializations, in Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2015 (MetaSel@ECML'15), Porto, Portugal. PDF
  • Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme (2015):
    Improving Automatic Affect Recognition on Low-Level Speech Features in Intelligent Tutoring Systems, in Proceedings of the 10th European Conference on Technology Enhanced Learning (EC-TEL 2015) (to appear), Toledo, Spain.
  • Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme (2015):
    Recognising perceived task difficulty from speech and pause histograms, in Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015) , Madrid, Spain.
  • Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme (2015):
    How to aggregate multimodal features for perceived task difficulty recognition in intelligent tutoring systems, in Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015) , Madrid, Spain.
  • Lydia Voß, Carlotta Schatten, Claudia Mazziotti, Lars Schmidt-Thieme (2015):
    A Transfer Learning approach for applying Matrix Factorization to small ITS datasets, in Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015) , Madrid, Spain.
  • Carlotta Schatten, Ruth Janning, Lars Schmidt-Thieme (2015):
    Integration and Evaluation of a Matrix Factorization Sequencer in Large Commercial ITS, in Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI15) , Austin, Texas.
  • Carlotta Schatten, Ruth Janning, Lars Schmidt-Thieme (2014):
    Vygotsky based Sequencing without Domain Information: A Matrix Factorization Approach, in Computer Supported Education, CSEDU 2014, Revised Selected Papers .
  • Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme, Gerhard Backfried, Norbert Pfannerer (2014):
    An SVM Plait for Improving Affect Recognition in Intelligent Tutoring Systems, in Proceedings of the IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2014. PDF
  • Lucas Drumond, Ernesto Diaz-Aviles, Lars Schmidt-Thieme, Wolfgang Nejdl (2014):
    Optimizing Multi-Relational Factorization Models for MultipleTarget Relations , in Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014) , Shanghai, China. PDF
  • Lucas Drumond, Lars Schmidt-Thieme, Christoph Freudenthaler, Artus Krohn-Grimberghe (2014):
    Collective Matrix Factorization of Predictors, Neighborhood and Targets for Semi-supervised Classification , in Advances in Knowledge Discovery and Data Mining - 18th Pacific-Asia Conference, (PAKDD 2014) , Tainan, Taiwan. PDF
  • Rasoul Karimi, Alexandros Nanopoulos, Lars Schmidt-Thieme (2014):
    Improved Questionnaire Trees for Active Learning in Recommender Systems, in Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML), Aachen, Germany. PDF
  • Josif Grabocka, Alexandros Dalkalitsis, Athanasios Lois, Evangelos Katsaros, Lars Schmidt-Thieme (2014):
    Realistic Optimal Policies for Energy-Efficient Train Driving, in Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems, ITSC 2014. PDF
  • Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme (2014):
    Local Feature Extractors Accelerating HNNP for Phoneme Recognition, in Proceedings of the 37th German Conference on Artificial Intelligence (KI 2014).
  • Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme (2014):
    Feature Analysis for Affect Recognition Supporting Task Sequencing in Adaptive Intelligent Tutoring Systems, in Proceedings of the 9th European Conference on Technology Enhanced Learning (EC-TEL 2014).
  • Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme (2014):
    Multimodal Affect Recognition for Adaptive Intelligent Tutoring Systems, in Extended Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014). PDF
  • Carlotta Schatten, Manolis Mavrikis, Ruth Janning, Lars Schmidt-Thieme (2014):
    Matrix Factorization Feasibility for Sequencing and Adaptive Support in ITS, in Proceedings of the 7th International Conference on Educational Data Mining, EDM 2014 (to appear).
  • Josif Grabocka, Nicolas Schilling, Martin Wistuba, Lars Schmidt-Thieme (2014):
    Learning Time-Series Shapelets, in Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2014. Acceptance Rate: 14.6% (151 out of 1036). PDF
  • Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme (2014):
    Automatic Subclasses Estimation for a Better Classification with HNNP, in Proceedings of the 21th International Symposium on Methodologies for Intelligent Systems (ISMIS 2014), in Lecture Notes in Artificial Intelligence, Springer.
  • Carlotta Schatten, Martin Wistuba, Lars Schmidt-Thieme, Sergio Gutiérrez-Santos (2014):
    Minimal Invasive Integration of Learning Analytics Services in Intelligent Tutoring Systems, in Proceedings of the 14th IEEE International Conference on Advanced Learning Technologies.
  • Carlotta Schatten, Lars Schmidt-Thieme (2014):
    Adaptive Content Sequencing without Domain Information, in Proceedings of the 6th International Conference on Computer Supported Education (www.csedu.org), Springer. PDF
  • Nicolas Schilling, Andre Busche, Simone Miller, Michael Jungheim, Martin Ptok, Lars Schmidt-Thieme (2014):
    Event Prediction in Pharyngeal High-Resolution Manometry , to appear in Proceedings of the European Conference on Data Analysis, ECDA 2013, Springer, Luxemburg. PDF
  • Umer Khan, Pavlos Basaras, Lars Schmidt-Thieme, Alexandros Nanopoulos, Dimitrios Katsaros (2014):
    Analyzing Cooperative Lane Change Models for Connected Vehicles, in 3rd IEEE International Conference on Connected Vehicles and Expo, Viena, Austria. PDF
  • Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme (2014):
    Supervised Nonlinear Factorizations Excel In Semi-supervised Regression , in Proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014, Springer, LNCS, Tainan, Taiwan. PDF
  • Andre Busche, Daniel Seyfried, Lars Schmidt-Thieme (2013):
    Hough Transform and Kirchhoff Migration for Supervised GPR Data Analysis, in Proceedings of the European Conference on Data Analysis, ECDA 2013, Springer, Luxemburg.
  • Andre Busche, Ruth Janning, Lars Schmidt-Thieme (2013):
    Analysing the Potential Impact of Labeling Disagreements for Engineering Sensor Data, in Proceedings of the LWA 2013 - Lernen, Wissen und Adaptivität, Knowledge Discovery and Machine Learning track, Bamberg.
  • Rasoul Karimi, Martin Wistuba, Alexandros Nanopoulos, Lars Schmidt-Thieme (2013):
    Factorized Decision Trees for Active Learning in Recommender Systems, in 25th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Washington D.C, USA. PDF
  • Umer Khan, Alexandros Nanopoulos, Lars Schmidt-Thieme (2013):
    P2P RVM for Distributed Classification, in European Conference on Data Analysis (ECDA), Luxembourg. PDF
  • Martin Wistuba, Lars Schmidt-Thieme (2013):
    Supervised Clustering of Social Media Streams, in Working Notes Proceedings of the MediaEval 2013 Workshop, Barcelona, Spain, October 18-19, 2013, CEUR-WS.org. PDF
  • Ruth Janning, Carlotta Schatten, Lars Schmidt-Thieme (2013):
    HNNP - A Hybrid Neural Network Plait for Improving Image Classification with Additional Side Information, in Proceedings of the IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2013. PDF
  • Josif Grabocka, Lucas Drumond, Lars Schmidt-Thieme (2013):
    Supervised Dimensionality Reduction Via Nonlinear Target Estimation, in Proceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2013 . PDF
  • Martin Wistuba, Lars Schmidt-Thieme (2013):
    Move Prediction in Go – Modelling Feature Interactions Using Latent Factors, in KI 2013: Advances in Artificial Intelligence, Springer-Verlag Berlin Heidelberg, pp. 260-271. Nominated for Best Paper Award (1 out of 3). PDF
  • Andre Busche, Ruth Janning, Tomas Horvath, Lars Schmidt-Thieme (2012):
    A Unifying Framework for GPR Image Reconstruction, in 36nd Annual Conference of the Gesellschaft für Klassifikation (GfKl 2012).
  • Josif Grabocka, Erind Bedalli, Lars Schmidt-Thieme (2012):
    Efficient Classification of Long Time Series, in Proceedings of ICT Innovations Conference 2012, Advances in Intelligent Systems and Computing, Volume 207, pp 47-57, Springer, Berlin/Heidelberg . PDF
  • Andre Busche, Ruth Janning, Tomas Horvath, Lars Schmidt-Thieme (2012):
    Some Improvements for Multi-Hyperbola Detection on GPR Data, in Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML 2012).
  • Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme (2012):
    Exploiting the Characteristics of Matrix Factorization for Active Learning in Recommender Systems, in Doctoral Symposium of the 6th Annual ACM Conference on Recommender Systems (RecSys), Dublin, Irelan, pp. 317-320. PDF
  • Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme (2012):
    Invariant Time-Series Classification, in Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML'12) , Bristol, United Kingdom. PDF
  • Nguyen Thai-Nghe, Lucas Drumond, Tomáš Horváth, Lars Schmidt-Thieme (2012):
    Using factorization machines for student modeling, in Workshop and Poster Proceedings of the 20th Conference on User Modeling, Adaptation, and Personalization, Montreal, Canada. PDF
  • Ernesto Diaz-Aviles, Lucas Drumond, Zeno Gantner, Lars Schmidt-Thieme, Wolfgang Nejdl (2012):
    What is Happening Right Now ... That Interests Me? Online Topic Discovery and Recommendation in Twitter , Proceedings of the 21st ACM International Conference on Information and Knowledge Management (CIKM 2012) . PDF
  • Ernesto Diaz-Aviles, Lucas Drumond, Lars Schmidt-Thieme, Wolfgang Nejdl (2012):
    Real-Time Top-N Recommendation within Social Streams , Proceedings of the 6th ACM International Conference on Recommender Systems (RecSys'12) . PDF
  • Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Lars Schmidt-Thieme (2012):
    Personalized Ranking for Non-Uniformly Sampled Items, Journal of Machine Learning Research Workshop and Conference Proceedings . PDF
  • Ruth Janning, Tomas Horvath, Andre Busche, Lars Schmidt-Thieme (2012):
    Pipe Localization by Apex Detection, in Proceedings of the IET international conference on radar systems (Radar 2012), Glasgow, Scotland.
  • Ruth Janning, Tomas Horvath, Andre Busche, Lars Schmidt-Thieme (2012):
    GamRec: a Clustering Method Using Geometrical Background Knowledge for GPR Data Preprocessing, in Artificial Intelligence Applications and Innovations (IFIP Advances in Information and Communication Technology 381), Springer, Heidelberg, Halkidiki, Greece, pp. 347--356. PDF
  • Daniel Seyfried, Andre Busche, Ruth Janning, Lars Schmidt-Thieme, Jörg Schöbel (2012):
    Information Extraction From Ultrawideband Ground Penetrating Radar Data: A Machine Learning Approach, Proceedings of the 7th German Microwave Conference .
  • Josif Grabocka, Alexandros Nanopoulos, Lars Schmidt-Thieme (2012):
    Classification of Sparse Time Series via Supervised Matrix Factorization, in Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI'12), Toronto, Canada. PDF
  • Artus Krohn-Grimberghe, Lucas Drumond, Christoph Freudenthaler, Lars Schmidt-Thieme (2012):
    Multi-Relational Matrix Factorization using Bayesian Personalized Ranking for Social Network Data , Proceedings of the Fifth ACM International Conference on Web Search and Data Mining . PDF
  • Lucas Drumond, Steffen Rendle, Lars Schmidt-Thieme (2012):
    Predicting RDF Triples in Incomplete Knowledge Bases with Tensor Factorization, in Proceedings of the 27th ACM International Symposium on Applied Computing, Riva del Garda, Italy. PDF
  • Christoph Freudenthaler, Lars Schmidt-Thieme, Steffen Rendle (2011):
    Bayesian Factorization Machines, in Workshop on Sparse Representation and Low-rank Approximation, Neural Information Processing Systems (NIPS), Granada, Spain. PDF
  • Christoph Freudenthaler, Lars Schmidt-Thieme, Steffen Rendle (2011):
    Factorization Machines - Factorized Polynomial Regression Models , in Proceedings of the 2nd German Polish Symposium on Data Analysis and Its Applications (GPSDAA), Cracow, Poland. PDF
  • Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme (2011):
    Factorizing Markov Models for Categorical Time Series Prediction , in American Institute of Physics (AIP) Conference Proceedings of the 9th International Conference of Numerical Analysis and Applied Mathematics (ICNAAM), Halkidiki, Greece. PDF
  • Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Towards Optimal Active Learning for Matrix Factorization in Recommender Systems, in 23th IEEE International Conference on Tools With Artificial Intelligence (ICTAI), Florida, USA. PDF
  • Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Non-myopic Active Learning for Recommender Systems based on Matrix Factorization, in 12th IEEE International Conference on Information Reuse and Integration (IRI), Las Vegas, USA. PDF
  • Rasoul Karimi, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    RFID-Enhanced Museum for Interactive Experience, in MultiMedia for Cultural Heritage (MM4CH), Modena, Italy. PDF
  • Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Lars Schmidt-Thieme (2011):
    Bayesian Personalized Ranking for Non-Uniformly Sampled Items, in KDD Cup Workshop 2011, San Diego, USA. PDF
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme, Julia Koller (2011):
    Fast Classification of Electrocardiograph Signals via Instance Selection, in Proceedings of the First IEEE conference on Healthcare Informatics, Imaging and Systems Biology. PDF
  • Nguyen Thai-Nghe, Lucas Drumond, Tomáš Horváth, Lars Schmidt-Thieme (2011):
    Multi-Relational Factorization Models for Predicting Student Performance, in KDD 2011 Workshop on Knowledge Discovery in Educational Data (KDDinED 2011). Held as part of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. PDF
  • Zeno Gantner, Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme (2011):
    MyMediaLite: A Free Recommender System Library, in 5th ACM International Conference on Recommender Systems (RecSys 2011), Chicago, USA. PDF
  • Steffen Rendle, Zeno Gantner, Christoph Freudenthaler, Lars Schmidt-Thieme (2011):
    Fast Context-aware Recommendations with Factorization Machines, in Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2011), Beijing, China. PDF
  • Christian Wartena, Wout Slakhorst, Martin Wibbels, Zeno Gantner, Christoph Freudenthaler, Chris Newell, Lars Schmidt-Thieme (2011):
    Keyword-Based TV Program Recommendation, to appear in 9th Workshop on Intelligent Techniques for Web Personalization and Recommender Systems (ITWP'11), Barcelona, Spain.
  • Artus Krohn-Grimberghe, Andre Busche, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Active Learning for Technology Enhanced Learning, to appear in Proceedings of the European Conference on Technology Enhanced Learning (EC-TEL) 2011, LNCS, Springer.
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    INSIGHT: Efficient and Effective Instance Selection for Time-Series Classification, to appear in Proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), LNCS Vol. 6635, Springer. PDF
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Fusion of Similarity Measures for Time-Series Classification, to appear in Proceedings of the 6th International Conference on Hybrid Artificial Intelligence Systems (HAIS), LNCS Vol. 6679, Springer. PDF
  • Krisztian Buza, Alexandros Nanopoulos, Tomáš Horváth, Lars Schmidt-Thieme (2011):
    GRAMOFON: General Model-selection Framework based on Networks, to appear in Neurocomputing, Elsevier .
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    IQ Estimation for Accurate Time-Series Classification, in IEEE Symposium Series on Computational Intelligence (SSCI) - IEEE Symposium on Computational Intelligence and Data Mining (CIDM). PDF
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Individualized Error Estimation for Classification and Regression Models, in 34nd Annual Conference of the Gesellschaft für Klassifikation (GfKl 2010). PDF
  • Timo Reuter, Philipp Cimiano, Lucas Drumond, Krisztian Buza, Lars Schmidt-Thieme (2011):
    Scalable event-based clustering of social media via record linkage techniques, in Fifth International AAAI Conference on Weblogs and Social Media. PDF
  • Nguyen Thai-Nghe, Tomáš Horváth, Lars Schmidt-Thieme (2011):
    Factorization Models for Forecasting Student Performance, in Pechenizkiy, M., Calders, T., Conati, C., Ventura, S., Romero , C., and Stamper, J. (Eds.) Proceedings of the 4th International Conference on Educational Data Mining (EDM 2011). PDF
  • Nguyen Thai-Nghe, Lucas Drumond, Tomáš Horváth, Artus Krohn-Grimberghe, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Factorization Techniques for Predicting Student Performance, to appear in Educational Recommender Systems and Technologies: Practices and Challenges (ERSAT 2011): Santos, O. C. and Boticario, J. G. (Eds.), IGI Global. PDF
  • Nguyen Thai-Nghe, Tomáš Horváth, Lars Schmidt-Thieme (2011):
    Context-Aware Factorization for Personalized Student's Task Recommendation, in Proceedings of International Workshop on Personalization Approaches in Learning Environments (PALE 2011) at UMAP 2011, CEUR-WS (ISSN 1613-0073).
  • Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme (2011):
    A New Evaluation Measure for Learning from Imbalanced Data, in Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN 2011), IEEE Xplore. Student Travel Grant by INNS. PDF
  • Nguyen Thai-Nghe, Tomáš Horváth, Lars Schmidt-Thieme (2011):
    Personalized Forecasting Student Performance, in Proceedings of IEEE International Conference on Advanced Learning Technologies (ICALT 2011), IEEE Computer Society. PDF
  • Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Active Learning for Aspect Model in Recommender Systems, in IEEE Symposium on Computational Intelligence and Data Mining (CIDM). PDF
  • Nguyen Thai-Nghe, Lucas Drumond, Tomáš Horváth, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Matrix and Tensor Factorization for Predicting Student Performance, in Proceedings of the 3rd International Conference on Computer Supported Education (CSEDU 2011). Best Student Paper Award. PDF
  • Sebastian Blohm, Krisztian Buza, Philipp Cimiano, Lars Schmidt-Thieme (2011):
    Relation Extraction for the Semantic Web with Taxonomic Sequential Patterns, to appear in Applied Semantic Web Technologies.
  • Zeno Gantner, Lucas Drumond, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme (2010):
    Learning Attribute-to-Feature Mappings for Cold-Start Recommendations, in Proceedings of the 10th IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia. PDF
  • Zeno Gantner, Steffen Rendle, Lars Schmidt-Thieme (2010):
    Factorization Models for Context-/Time-Aware Movie Recommendations, in Challenge on Context-aware Movie Recommendation (CAMRa2010), ACM, Barcelona, Spain. Winner of 'Weekly Recommendation' and 'Live Evaluation' tracks. PDF
  • Andre Busche, Artus Krohn-Grimberghe, Lars Schmidt-Thieme (2010):
    Mining Music Playlogs for Next Song Recommendations, in Workshop Proceedings of Knowledge Discovery, Data Mining, Maschinelles Lernen 2010 (KDML 2010).
  • Nguyen Thai-Nghe, Lucas Drumond, Artus Krohn-Grimberghe, Lars Schmidt-Thieme (2010):
    Recommender System for Predicting Student Performance, in Proceedings of ACM RecSys 2010 Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2010), Elsevier Computer Science Procedia, pp. 2811-2819. PDF
  • Artus Krohn-Grimberghe, Alexandros Nanopoulos, Lars Schmidt-Thieme (2010):
    Integrating OLAP and Recommender Systems: An Evaluation Perspective, in Proceeding of the ACM 13th international workshop on Data Warehousing and OLAP, ACM. PDF
  • Artus Krohn-Grimberghe, Alexandros Nanopoulos, Lars Schmidt-Thieme (2010):
    A Novel Multidimensional Framework for Evaluating Recommender Systems, in Proceedings of the ACM RecSys 2010 Workshop on User-Centric Evaluation of Recommender Systems and Their Interfaces (UCERSTI), CEUR-WS. PDF
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2010):
    Time-Series Classification based on Individualised Error Prediction, in 13th IEEE International Conference on Computational Science and Engineering (CSE-2010). Best paper award. PDF
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2010):
    Graph-Based Model-Selection Framework for Large Ensembles, in 5th International Conference on Hybrid Artificial Intelligence Systems, HAIS2010, LNCS/LNAI 6076, pp. 559-566, Springer, Berlin/Heidelberg. PDF
  • Nguyen Thai-Nghe, Thanh-Nghi Do, Lars Schmidt-Thieme (2010):
    Learning Optimal Threshold on Resampling Data to Deal with Class Imbalance, in Proceedings of the 8th IEEE International Conference on Computing and Communication Technologies: Research, Innovation, and Vision for the Future (RIVF 2010), IEEE Xplore. PDF
  • Nguyen Thai-Nghe, Thanh-Nghi Do, Lars Schmidt-Thieme (2010):
    Learning Optimal Threshold for Bayesian Posterior Probabilities to Mitigate the Class Imbalance Problem, in Proceedings of the 3rd International Conference on Theories and Applications of Computer Science (ICTACS 2010).
  • Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme (2010):
    Cost-Sensitive Learning Methods for Imbalanced Data, in Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN 2010), IEEE Xplore. Student Travel Grant by INNS. PDF
  • Christine Preisach, Leandro Balby Marinho, Lars Schmidt-Thieme (2010):
    Semi-Supervised Tag Recommendation - Using Untagged Resources to Mitigate Coldstart Problems, in PAKDD 2010: Proceedings of the 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining. PDF
  • Steffen Rendle, Christoph Freudenthaler, Lars Schmidt-Thieme (2010):
    Factorizing Personalized Markov Chains for Next-Basket Recommendation, in Proceedings of the 19th International World Wide Web Conference (WWW 2010), ACM. Best Paper Award. PDF
  • Steffen Rendle, Lars Schmidt-Thieme (2010):
    Pairwise Interaction Tensor Factorization for Personalized Tag Recommendation, in Proceedings of the Third ACM International Conference on Web Search and Data Mining (WSDM 2010), ACM. Best Student Paper Award. PDF
  • Christine Preisach, Leandro Balby Marinho, Lars Schmidt-Thieme (2009):
    Semi-Supervised Tag Recommendation for Cold-Start Problems, in 4th Annual Workshop for Women in Machine Learning, Poster Session.
  • Krisztian Buza, Lars Schmidt-Thieme (2009):
    A Simple Ensemble Technique, in Analytic Challenge 'Ensembling' at the Australian Data Mining Conference (AusDM 2009). PDF
  • Zeno Gantner, Christoph Freudenthaler, Steffen Rendle, Lars Schmidt-Thieme (2009):
    Optimal Ranking for Video Recommendation, in User Centric Media: First International Conference, UCMedia 2009, Revised Selected Papers, Springer. PDF
  • Krisztian Buza, Christine Preisach, Andre Busche, Lars Schmidt-Thieme, Wye Houn Leong, Mark Walters (2009):
    Eigenmode Identification in Campbell Diagrams, in International Workshop on Machine Learning for Aerospace. PDF
  • Lorenza Romano, Krisztian Buza, Claudio Giuliano, Lars Schmidt-Thieme (2009):
    XMedia: Web People Search by Clustering with Machinely Learned Similarity Measures, in 2nd Web People Search Evaluation Workshop at World Wide Web Conference. PDF
  • Steffen Rendle, Lars Schmidt-Thieme (2009):
    Factor Models for Tag Recommendation in BibSonomy, in ECML/PKDD Discovery Challenge 2009 at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-DC 2009). Best Discovery Challenge Award. PDF
  • Leandro Balby Marinho, Christine Preisach, Lars Schmidt-Thieme (2009):
    Relational Classification for Personalized Tag Recommendation, in ECML/PKDD Discovery Challenge 2009 at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-DC 2009). 2nd place in graph-based tag recommendation task. PDF
  • Nguyen Thai-Nghe, Andre Busche, Lars Schmidt-Thieme (2009):
    Improving Academic Performance Prediction by Dealing with Class Imbalance, in Proceedings of the 9th IEEE International Conference on Intelligent Systems Design and Applications (ISDA 2009), IEEE Computer Society, pp. 878--883. PDF
  • Zeno Gantner, Lars Schmidt-Thieme (2009):
    Automatic Content-based Categorization of Wikipedia Articles, in The People's Web Meets NLP: Collaboratively Constructed Semantic Resources. Workshop at Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL 2009). PDF
  • Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Lars Schmidt-Thieme (2009):
    BPR: Bayesian Personalized Ranking from Implicit Feedback, in Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009). PDF
  • Avaré Stewart, Ernesto Diaz-Aviles, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme, Wolfgang Nejdl (2009):
    Cross-Tagging for Personalized Open Social Networking, in Proceedings of the 20th ACM Conference on Hypertext and Hypermedia (Hypertext2009) .
  • Steffen Rendle, Leandro Balby Marinho, Alexandros Nanopoulos, Lars Schmidt-Thieme (2009):
    Learning Optimal Ranking with Tensor Factorization for Tag Recommendation, in Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2009), Paris, ACM. PDF
  • Steffen Rendle, Christine Preisach, Lars Schmidt-Thieme (2009):
    Learning to Extract Relations for Relational Classification, in Proceedings of the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Springer. PDF
  • Krisztian Buza, Lars Schmidt-Thieme (2009):
    Motif-based Classification of Time Series with Bayesian Networks and SVMs, in Proceedings of 32nd Annual Conference of the Gesellschaft für Klassifikation (GfKl 2008). PDF
  • Krisztian Buza, Leandro Balby Marinho, Lars Schmidt-Thieme (2008):
    On Learning Knowledge Bases for Collabularies, in Internation Scientific Conference Series in Honour of the Hungarian Science Day at the College of Dunaujvaros. PDF
  • Robert Jaeschke, Leandro Marinho, Andreas Hotho, Lars Schmidt-Thieme, Gerd Stumme (2008):
    Tag Recommendations in Social Bookmarking Systems, AI Commun. 21(4):231--247.
  • Steffen Rendle, Lars Schmidt-Thieme (2008):
    Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference, in Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), Pisa. PDF
  • Christine Preisach, Steffen Rendle, Lars Schmidt-Thieme (2008):
    Relational Classification Using Automatically Extracted Relations by Record Linkage, in Proceedings of the High Level Information Extraction Workshop at the European Conference on Machine Learning (ECML-WS 2008). PDF
  • Leandro Balby Marinho, Krisztian Buza, Lars Schmidt-Thieme (2008):
    Folksonomy-based Collabulary Learning, in Proceedings of the International Semantic Web Conference (ISWC'08), Springer. PDF
  • Steffen Rendle, Lars Schmidt-Thieme (2008):
    Online-Updating Regularized Kernel Matrix Factorization Models for Large-Scale Recommender Systems, in Proceedings of the 2008 ACM Conference on Recommender Systems (RecSys 2008), ACM. PDF
  • Steffen Rendle, Lars Schmidt-Thieme (2008):
    Scaling Record Linkage to Non-Uniform Distributed Class Sizes, in Proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2008), Osaka, Springer. PDF
  • Karen Tso-Sutter, Leandro Marinho, Lars Schmidt-Thieme (2008):
    Tag-aware Recommender Systems by Fusion of Collaborative Filtering Algorithms, in Proceedings of 23rd Annual ACM Symposium on Applied Computing (SAC'08), Fortaleza, Brazil. PDF
  • Manuel Stritt, Lars Schmidt-Thieme, Gerhard Poeppel (2007):
    Combining Multi-Distributed Mixture Models and Bayesian Networks for Semi-Supervised Learning, in ICMLA '07: Proceedings of the Sixth International Conference on Machine Learning and Applications.
  • Steffen Rendle, Lars Schmidt-Thieme (2007):
    Information Integration of Partially Labeled Data, in Proceedings of 31st Annual Conference of the German Classification Society (GfKl 2007), Freiburg, Springer. PDF
  • Stefan Hauger , Karen Tso, Lars Schmidt-Thieme (2007):
    Comparison of Recommender System Algorithms focusing on the New-Item and User-Bias Problem, in Proceedings of 31st Annual Conference of the Gesellschaft für Klassifikation (GfKl) 2007, Freiburg. PDF
  • Leandro Balby Marinho, Lars Schmidt-Thieme (2007):
    Collaborative Tag Recommendations, in Proceedings of 31st Annual Conference of the Gesellschaft für Klassifikation (GfKl) 2007, Freiburg, Springer. PDF
  • Dominik Benz, Karen Tso, Lars Schmidt-Thieme (2007):
    Supporting Collaborative Hierarchical Classification: Bookmarks as an Example, Special Issue on Innovations in Web Communications Infrastructure, Journal of Computer Networks Volume 51:16:4574--4585. PDF
  • Robert Jaeschke, Leandro Marinho, Andreas Hotho, Lars Schmidt-Thieme, Gerd Stumme (2007):
    Tag Recommendations in Folksonomies, in Proceedings of the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) 2007, Warsaw, Poland. PDF
  • Robert Jaeschke, Leandro Marinho, Andreas Hotho, Lars Schmidt-Thieme, Gerd Stumme (2007):
    Tag Recommendations in Folksonomies, in Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivitaet (LWA 2007) 13-20.
  • Christine Preisach, Lars Schmidt-Thieme (2008):
    Ensembles of Relational Classifiers, Knowledge and Information Systems Journal 14(3).
  • Christine Preisach, Lars Schmidt-Thieme (2006):
    Relational Ensemble Classification, in Proceedings of the 6th IEEE International Conference on Data Mining (ICDM) 2006, Hong Kong. PDF
  • Steffen Rendle, Lars Schmidt-Thieme (2006):
    Object Identification with Constraints, in Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), Hong Kong. PDF
  • Karen Tso, Lars Schmidt-Thieme (July 2006):
    Empirical Analysis of Attribute-Aware Recommender System Algorithms Using Synthetic Data, Journal of Computers Volume 1 Issue 4:18--29. PDF
  • Manuel Stritt, Karen Tso, Lars Schmidt-Thieme (2006):
    Attribute-Aware Anonymous Recommender Systems, in Proceedings of 30th Annual Conference of the Gesellschaft für Klassifikation (GfKl) 2006, Berlin, Springer, pp. 497--506. PDF
  • Dominik Benz, Karen Tso, Lars Schmidt-Thieme (2006):
    Automatic Bookmark Classification: A Collaborative Approach, in Proceedings of the Second Workshop on Innovations in Web Infrastructure (IWI 2006), Edinburgh, Scotland. PDF
  • Jochen Fischer, Zeno Gantner, Steffen Rendle, Manuel Stritt, Lars Schmidt-Thieme (2006):
    Ideas and Improvements for Semantic Wikis, in Proceedings of the Third European Semantic Web Conference (ESWC 2006), Budva, Montenegro, Springer. PDF
  • Karen Tso, Lars Schmidt-Thieme (2006):
    Evaluation of Attribute-aware Recommender System Algorithms on Data with Varying Characteristics, in Proceedings of the Tenth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006), Singapore, Springer, pp. 831-840. PDF
  • Manuel Stritt, Karen Tso, Lars Schmidt-Thieme, Dirk Schwarz (2005):
    Anonymous Recommender Systems, ÖGAI Journal Jahrgang 2005, Nr. 4:4-11.
  • Lars Schmidt-Thieme (2005):
    Compound Classification Models for Recommender Systems, in Proceedings of the IEEE International Conference on Data Mining (ICDM) 2005, Houston, USA. PDF
  • Ferenc Bodon, Lars Schmidt-Thieme (2005):
    The Relation of Closed Itemset Mining, Complete Pruning Strategies and Item Ordering in APRIORI-based FIM algorithms, in Proceedings of the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) 2005, Porto, Portugal. PDF
  • Ferenc Bodon, Balazs Racz, Lars Schmidt-Thieme (2005):
    On Benchmarking Frequent Itemset Mining Algorithms, in Proceedings of the Open Source Data Mining Workshop, 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) 2005, Chicago, USA. PDF
  • Karen Tso, Lars Schmidt-Thieme (2005):
    Sensitivity of Attributes on the Performance of Attribute-Aware Collaborative Filtering, in Proceedings of the 5th biennial meeting of CLAssification and Data Analysis Group (CLADAG'05) 2005, Parma, Italy, Springer, pp. 279--286. PDF
  • Karen Tso, Lars Schmidt-Thieme (2005):
    Attribute-aware Collaborative Filtering, in Proceedings of 29th Annual Conference of the Gesellschaft für Klassifikation (GfKl) 2005, Magdeburg, Springer, pp. 614--621. PDF
  • Lars Schmidt-Thieme, Martin Schader (2005):
    Performance Drivers for Depth-First Frequent Pattern Mining, in Daniel Baier, Reinhold Decker, Lars Schmidt-Thieme (eds.): Data Analysis and Decision Support, Springer.
  • Peter Fankhauser, Manfred Fuhr, Jens Hartmann, Anthony Jameson, P. Klas, Stefan Klink, Agnes Koschmider, S. Kriewel, Patrick Lethi, P. Luksch, E.W. Mayr, Andreas Oberweis, Paul Ortyl, Stefan Pfingstl, P. Reuther, Ute Rusnak, G. Sautter, K. Böhm, A. Schaefer, Lars Schmidt-Thieme, Eric Schwarzkopf, Nenad Stojanovic, Rudi Studer, R. Vollmar, Bernd Walter, Alexander Weber (2005):
    Fachinformationsystem Informatik (FIS-I) und Semantische Technologien für Informationsportale (SemIPort), in Proceedings of Informatik 2005, Bonn.
  • Ernesto Diaz-Aviles, Lars Schmidt-Thieme, Cai Ziegler (2005):
    Emergence of Spontaneous Order Through Neighbourhood Formation in Peer-to-Peer Recommender Systems, in 1st International Workshop on Innovations In Web Infrastructure, 14th International World Wide Web Conference (WWW) 2005, Keio, Japan. PDF
  • Peter Haase, Andreas Hotho, Lars Schmidt-Thieme, York Sure (2005):
    Usage-driven Evolution of Personal Ontologies, in Proceedings of the 3rd International Conference on Universal Access in Human-Computer Interaction (UAHCI), 22--27 July, 2005, Las Vegas, Nevada USA. PDF
  • Jens Hartmann, Nenad Stojanovic, Rudi Studer, Lars Schmidt-Thieme (2005):
    Ontology-Based Query Refinement for Semantic Portals, in Hemmje, M., Niederee, C., Risse, Th. (eds.): From Integrated Publication and Information Systems to Information and Knowledge Environments, Springer, pp. 41-50.
  • Lars Schmidt-Thieme (2004):
    Algorithmic Features of Eclat, in Proceedings of the Frequent Itemset Mining Implementations Workshop, IEEE International Conference on Data Mining (ICDM), Brighton, UK. PDF
  • Philipp Cimiano, Lars Schmidt-Thieme, Alexander Pivk, Steffen Staab (2004):
    Learning Taxonomic Relations from Heterogeneous Evidence, in Proceedings of the Ontology Learning and Population Workshop, 16th European Conference on Artificial Intelligence (ECAI) 2004, Valencia, Spanien. PDF
  • Cai Ziegler, Georg Lausen, Lars Schmidt-Thieme (2004):
    Taxonomy-driven Computation of Product Recommendations, in Proceedings of the 2004 ACM International Conference on Information and Knowledge Management (CIKM '04), November 8-13, 2004, Washington D.C., USA. PDF
  • Cai Ziegler, Lars Schmidt-Thieme, Georg Lausen (2004):
    Exploiting Semantic Product Descriptions for Recommender Systems, in Proceedings of the 2nd ACM SIGIR Semantic Web and Information Retrieval Workshop (SWIR '04), July 25-29, 2004, Sheffield, UK. PDF
  • Stefan Born, Lars Schmidt-Thieme (2004):
    Optimal Discretization of Quantitative Attributes for Association Rules, in Classification, Clustering, and Data Mining Applications, Proceedings of the Meeting of the International Federation of Classification Societies (IFCS), Illinois Institute of Technology, Chicago, 15--18 July 2004, pp. 287--296. PDF
  • Christoph Breidert, Michael Hahsler, Lars Schmidt-Thieme (2004):
    Reservation Price Estimation by Adaptive Conjoint Analysis, in Proceedings of the 28th Annual Conference of the Gesellschaft für Klassifikation (GfKl), University of Dortmund, March 9--11, 2004, Springer, pp. 569-576. PDF
  • Wolfgang Gaul, Patrick Thoma, Lars Schmidt-Thieme, Sven van den Bergh (2003):
    Visualizing Recommender Systems via Multidimensional Scaling, in Ahr, D., Fahrion, R., Oswald, M., Reinelt, G. (eds.): Operations Research Proceedings 2003, Selected Papers of the International Conference on Operations Research (OR 2003), Heidelberg, September 3--5, 2003, pp. 189-196.
  • Wolfgang Gaul, Lars Schmidt-Thieme (2002):
    Mining Web Navigation Path Fragments, in Nishisato, S., Baba, Y., Bozdogan, H., Kanefuji, K. (Eds.): Measurement and Multivariate Analysis, Springer, pp. 249-260.
  • Wolfgang Gaul, Andreas Geyer-Schulz, Michael Hahsler, Lars Schmidt-Thieme (2002):
    eMarketing mittels Recommendersystemen, Marketing ZFP 24:47-55.
  • Wolfgang Gaul, Lars Schmidt-Thieme (2002):
    Recommender Systems Based on User Navigational Behavior in the Internet, Behaviormetrika 29:1-22.
  • Lars Schmidt-Thieme, Wolfgang Gaul (2002):
    Aufzeichnung des Nutzerverhaltens - Erhebungstechniken und Datenformate, in Hajo Hippner et. al. (eds.): Handbuch Web Mining im Marketing, Braunschweig/Wiesbaden.
  • Wolfgang Gaul, Lars Schmidt-Thieme (2002):
    Web Controlling und Recommendersysteme, in Hajo Hippner et. al. (eds.): Handbuch Web Mining im Marketing, Braunschweig/Wiesbaden.
  • Wolfgang Gaul, Lars Schmidt-Thieme (2001):
    Mining Generalized Association Rules for Sequential and Path Data, in Proceedings of the 2001 IEEE International Conference on Data Mining (ICDM), San Jose, pp. 593-596. PDF
  • Wolfgang Gaul, Lars Schmidt-Thieme (2001):
    Recommender Systems Based on Navigation Path Features, in Proceedings of the Web Mining Workshop, The Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), San Francisco.
  • Lars Schmidt-Thieme, Wolfgang Gaul (2001):
    Frequent Substructures in Web Usage Data -- a Unified Approach, in Proceedings of the Web Mining Workshop, First SIAM International Conference on Data Mining 2001 (SDM), Chicago.
  • Wolfgang Gaul, Lars Schmidt-Thieme (2000):
    Mining Web Navigation Path Fragments, in Proceedings of WebKDD Workshop 2000, The Sixt ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2000 (KDD), Boston.
  • Wolfgang Gaul, Lars Schmidt-Thieme (2000):
    Frequent Generalized Subsequences - a Problem from Web Mining, in Wolfgang Gaul, Otto Opitz, and Martin Schader (eds.): Data Analysis, Scientific Modelling and Practical Application, Springer, pp. 429-445.
  • Lars Schmidt-Thieme (1999):
    Lineare Differentialoperatoren mit endlicher Galoisgruppe, Preprint des Instituts für Wissenschaftliches Rechnen (IWR), Universität Heidelberg.
  • Lars Schmidt-Thieme (2000):
    Haydns Sonatenrondo, in Chr.-H. Mahling, Kr. Pfarr (eds.): Aspekte historischer und systematischer Musikforschung, Mainz, pp. 229-239.
  • Lars Schmidt-Thieme (1997):
    Form und Harmonik der zweistimmigen ballate Francesco Landinis, Musiktheorie 12:125-145.