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ORCIDPKDD/ECML 2019: Würzburg, Germany - Workshops
- Peggy Cellier, Kurt Driessens
:
Machine Learning and Knowledge Discovery in Databases - International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part II. Communications in Computer and Information Science 1168, Springer 2020, ISBN 978-3-030-43886-9
Second International Workshop on Knowledge Discovery and User Modeling for Smart Cities (UMCit)
- Shahrooz Abghari, Veselka Boeva, Jens Brage, Christian Johansson:
District Heating Substation Behaviour Modelling for Annotating the Performance. 3-11 - Veselka Boeva, Christian Nordahl:
Modeling Evolving User Behavior via Sequential Clustering. 12-20 - Fitore Muharemi, Egzon Syka, Doina Logofatu:
Recognizing User's Activity and Transport Mode Detection: Maintaining Low-Power Consumption. 21-37 - Amit Agarwal, Durga Toshniwal, Jatin Bedi:
Can Twitter Help to Predict Outcome of 2019 Indian General Election: A Deep Learning Based Study. 38-53 - Akio Sashima, Mitsuru Kawamoto:
Towards Sensing and Sharing Auditory Context Information Using Wearable Device. 54-59
Workshop on Data Integration and Applications (DINA)
- Birgit Kirsch, Zamira Niyazova, Michael Mock, Stefan Rüping:
Noise Reduction in Distant Supervision for Relation Extraction Using Probabilistic Soft Logic. 63-78 - Abel N. Kho, Jingzhi Yu, Molly Scannell Bryan, Charon Gladfelter, Howard S. Gordon, Shaun J. Grannis, Margaret B. Madden, Eneida A. Mendonça, Vesna Mitrovic, Raj C. Shah, Umberto Tachinardi, Bradley Taylor:
Privacy-Preserving Record Linkage to Identify Fragmented Electronic Medical Records in the All of Us Research Program. 79-87 - Samuel Roeslin, Quincy Ma, Jörg Wicker, Liam Wotherspoon:
Data Integration for the Development of a Seismic Loss Prediction Model for Residential Buildings in New Zealand. 88-100 - Katsiaryna Mirylenka, Paolo Scotton, Christoph Miksovic, Salah-Eddine Bariol Alaoui:
Linking IT Product Records. 101-111 - David Haller, Richard Lenz:
Pharos: Query-Driven Schema Inference for the Semantic Web. 112-124 - Victor Christen, Peter Christen, Erhard Rahm:
Informativeness-Based Active Learning for Entity Resolution. 125-141 - Rainer Schnell, Christian Borgs:
Encoding Hierarchical Classification Codes for Privacy-Preserving Record Linkage Using Bloom Filters. 142-156
Machine Learning for Cybersecurity (MLCS)
- Félix Iglesias, Alexander Hartl, Tanja Zseby, Arthur Zimek:
Are Network Attacks Outliers? A Study of Space Representations and Unsupervised Algorithms. 159-175 - Georgios Kaiafas, Christian A. Hammerschmidt, Sofiane Lagraa, Radu State:
Auto Semi-supervised Outlier Detection for Malicious Authentication Events. 176-190 - Xiang Li, Shihao Ji:
Defense-VAE: A Fast and Accurate Defense Against Adversarial Attacks. 191-207 - Fabio Massimo Zennaro:
Analyzing and Storing Network Intrusion Detection Data Using Bayesian Coresets: A Preliminary Study in Offline and Streaming Settings. 208-222
6th Workshop on Sports Analytics: Machine Learning and Data Mining for Sports Analytics (MLSA)
- Kenneth Verstraete, Tom Decroos, Bruno Coussement, Nick Vannieuwenhoven, Jesse Davis:
Analyzing Soccer Players' Skill Ratings Over Time Using Tensor-Based Methods. 225-234 - Laurentius Antonius Meerhoff, Floris R. Goes, Arie-Willem de Leeuw, Arno J. Knobbe:
Exploring Successful Team Tactics in Soccer Tracking Data. 235-246 - Robert Müller, Stefan Langer, Fabian Ritz, Christoph Roch, Steffen Illium, Claudia Linnhoff-Popien:
Soccer Team Vectors. 247-257 - Arie-Willem de Leeuw, Aldo Hoekstra, Laurentius Antonius Meerhoff, Arno J. Knobbe:
Tactical Analyses in Professional Tennis. 258-269 - Stefan Langer, Robert Müller, Kyrill Schmid, Claudia Linnhoff-Popien:
Difficulty Classification of Mountainbike Downhill Trails Utilizing Deep Neural Networks. 270-280
First Workshop on Categorizing Different Types of Online Harassment Languages in Social Media
- Mozhgan Saeidi, Samuel Bruno da Silva Sousa, Evangelos E. Milios, Norbert Zeh, Lilian Berton:
Categorizing Online Harassment on Twitter. 283-297 - Margarita Constanza Bugueño, Marcelo Mendoza:
Learning to Detect Online Harassment on Twitter with the Transformer. 298-306 - Ignacio Espinoza, Fernanda Weiss:
Detection of Harassment on Twitter with Deep Learning Techniques. 307-313 - Fabíola S. F. Pereira, Thiago Andrade, André C. P. L. F. de Carvalho:
Gradient Boosting Machine and LSTM Network for Online Harassment Detection and Categorization in Social Media. 314-320 - Christos Karatsalos, Yannis Panagiotakis:
Attention-Based Method for Categorizing Different Types of Online Harassment Language. 321-330
IoT Stream for Data Driven Predictive Maintenance
- Cristian Axenie, Radu Tudoran, Stefano Bortoli, Mohamad Al Hajj Hassan, Alexander Wieder, Goetz Brasche:
SPICE: Streaming PCA Fault Identification and Classification Engine in Predictive Maintenance. 333-344 - Athanasios Naskos, Georgia Kougka, Theodoros Toliopoulos, Anastasios Gounaris, Cosmas Vamvalis, Daniel Caljouw:
Event-Based Predictive Maintenance on Top of Sensor Data in a Real Industry 4.0 Case Study. 345-356 - Mehmet Dinç, Seyda Ertekin, Hadi Özkan, Can Meydanli, Volkan Atalay:
Forecasting of Product Quality Through Anomaly Detection. 357-366 - Pawel Zyblewski, Robert Sabourin, Michal Wozniak:
Data Preprocessing and Dynamic Ensemble Selection for Imbalanced Data Stream Classification. 367-379 - Ehsan Aminian, Rita P. Ribeiro, João Gama:
A Study on Imbalanced Data Streams. 380-389 - Thiago Andrade, Brais Cancela, João Gama:
Mining Human Mobility Data to Discover Locations and Habits. 390-401 - Barbara Bobowska, Jakub Klikowski, Michal Wozniak:
Imbalanced Data Stream Classification Using Hybrid Data Preprocessing. 402-413 - Mathias Van Herreweghe, Mathias Verbeke, Wannes Meert, Tom Jacobs:
A Machine Learning-Based Approach for Predicting Tool Wear in Industrial Milling Processes. 414-425
12th International Workshop on Machine Learning and Music (MML 2019)
- Stylianos I. Mimilakis, Christof Weiss, Vlora Arifi-Müller, Jakob Abeßer, Meinard Müller:
Cross-version Singing Voice Detection in Opera Recordings: Challenges for Supervised Learning. 429-436 - Gino Brunner, Mazda Moayeri, Oliver Richter, Roger Wattenhofer, Chi Zhang:
Neural Symbolic Music Genre Transfer Insights. 437-445 - Lloyd May, Michael A. Casey:
Familiar Feelings: Listener-Rated Familiarity in Music Emotion Recognition. 446-453 - Cedric De Boom, Stephanie Van Laere, Tim Verbelen, Bart Dhoedt:
Rhythm, Chord and Melody Generation for Lead Sheets Using Recurrent Neural Networks. 454-461 - Alexander Leemhuis, Simon Waloschek, Aristotelis Hadjakos:
Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization. 462-469 - Luisa Micó, José Oncina, José M. Iñesta:
Adaptively Learning to Recognize Symbols in Handwritten Early Music. 470-477 - Renato de Castro Rabelo Profeta, Gerald Schuller:
Feature-Based Classification of Electric Guitar Types. 478-484 - David Meredith:
RecurSIA-RRT: Recursive Translatable Point-Set Pattern Discovery with Removal of Redundant Translators. 485-493 - David Dalmazzo, Rafael Ramírez:
Bow Gesture Classification to Identify Three Different Expertise Levels: A Machine Learning Approach. 494-501 - Kerstin Neubarth, Darrell Conklin:
Symbolic Music Classification Based on Multiple Sequential Patterns. 502-508 - Viktor Schmuck, David Meredith:
OPTISIA: An Evolutionary Approach to Parameter Optimisation in a Family of Point-Set Pattern-Discovery Algorithms. 509-516 - Fábio José Muneratti Ortega, Alfonso Pérez Carrillo, Rafael Ramírez:
Predicting Dynamics in Violin Pieces with Features from Melodic Motifs. 517-523 - Darrell Conklin:
Sequence Generation Using Unwords. 524-530 - Sergio I. Giraldo, Alberto Nasarre, Isabelle Heroux, Rafael Ramirez:
A Machine Learning Approach to Study Expressive Performance Deviations in Classical Guitar. 531-536 - Simon Hestermann, Niklas Deffner:
Enhanced De-Essing via Neural Networks. 537-542 - Piyush Papreja, Hemanth Venkateswara, Sethuraman Panchanathan:
Representation, Exploration and Recommendation of Playlists. 543-550
Large-Scale Biomedical Semantic Indexing and Question Answering (BioASQ)
- Anastasios Nentidis, Konstantinos Bougiatiotis, Anastasia Krithara, Georgios Paliouras:
Results of the Seventh Edition of the BioASQ Challenge. 553-568 - Bernd Müller, Dietrich Rebholz-Schuhmann:
Selected Approaches Ranking Contextual Term for the BioASQ Multi-label Classification (Task6a and 7a). 569-580 - Alastair R. Rae, James G. Mork, Dina Demner-Fushman:
Convolutional Neural Network for Automatic MeSH Indexing. 581-594 - Mónica Pineda Vargas, Andrés Rosso-Mateus, Fabio A. González, Manuel Montes-y-Gómez:
A Mixed Information Source Approach for Biomedical Question Answering: MindLab at BioASQ 7B. 595-606 - Dimitris Pappas, Ryan T. McDonald, Georgios-Ioannis Brokos, Ion Androutsopoulos:
AUEB at BioASQ 7: Document and Snippet Retrieval. 607-623 - Alexios Gidiotis, Grigorios Tsoumakas:
Structured Summarization of Academic Publications. 636-645 - Sanjay Kamath, Brigitte Grau, Yue Ma:
How to Pre-train Your Model? Comparison of Different Pre-training Models for Biomedical Question Answering. 646-660 - Dimitris Dimitriadis, Grigorios Tsoumakas:
Yes/No Question Answering in BioASQ 2019. 661-669 - Marilena Oita, K. Vani, Fatma Oezdemir-Zaech:
Semantically Corroborating Neural Attention for Biomedical Question Answering. 670-685 - Stefan Hosein, Daniel Andor, Ryan T. McDonald:
Measuring Domain Portability and Error Propagation in Biomedical QA. 686-694 - Sai Krishna Telukuntla, Aditya Kapri, Wlodek Zadrozny:
UNCC Biomedical Semantic Question Answering Systems. BioASQ: Task-7B, Phase-B. 695-710 - Michele Resta, Daniele Arioli, Alessandro Fagnani, Giuseppe Attardi:
Transformer Models for Question Answering at BioASQ 2019. 711-726 - Wonjin Yoon, Jinhyuk Lee, Donghyeon Kim, Minbyul Jeong, Jaewoo Kang:
Pre-trained Language Model for Biomedical Question Answering. 727-740
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