Table of Contents

• District Heating Substation Behaviour Modelling for Annotating the PerformanceShahrooz Abghari, Veselka Boeva, Jens Brage, Christian Johansson. 3-11 [doi]
• Modeling Evolving User Behavior via Sequential ClusteringVeselka Boeva, Christian Nordahl. 12-20 [doi]
• Recognizing User's Activity and Transport Mode Detection: Maintaining Low-Power ConsumptionFitore Muharemi, Egzon Syka, Doina Logofatu. 21-37 [doi]
• Can Twitter Help to Predict Outcome of 2019 Indian General Election: A Deep Learning Based StudyAmit Agarwal 0005, Durga Toshniwal, Jatin Bedi. 38-53 [doi]
• Towards Sensing and Sharing Auditory Context Information Using Wearable DeviceAkio Sashima, Mitsuru Kawamoto. 54-59 [doi]
• Noise Reduction in Distant Supervision for Relation Extraction Using Probabilistic Soft LogicBirgit Kirsch, Zamira Niyazova, Michael Mock, Stefan Rüping 0001. 63-78 [doi]
• Privacy-Preserving Record Linkage to Identify Fragmented Electronic Medical Records in the All of Us Research ProgramAbel 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. 79-87 [doi]
• Data Integration for the Development of a Seismic Loss Prediction Model for Residential Buildings in New ZealandSamuel Roeslin, Quincy Ma, Jörg Wicker, Liam Wotherspoon. 88-100 [doi]
• Linking IT Product RecordsKatsiaryna Mirylenka, Paolo Scotton, Christoph Miksovic, Salah-Eddine Bariol Alaoui. 101-111 [doi]
• Pharos: Query-Driven Schema Inference for the Semantic WebDavid Haller, Richard Lenz. 112-124 [doi]
• Informativeness-Based Active Learning for Entity ResolutionVictor Christen, Peter Christen, Erhard Rahm. 125-141 [doi]
• Encoding Hierarchical Classification Codes for Privacy-Preserving Record Linkage Using Bloom FiltersRainer Schnell, Christian Borgs. 142-156 [doi]
• Are Network Attacks Outliers? A Study of Space Representations and Unsupervised AlgorithmsFélix Iglesias, Alexander Hartl, Tanja Zseby, Arthur Zimek. 159-175 [doi]
• Auto Semi-supervised Outlier Detection for Malicious Authentication EventsGeorgios Kaiafas, Christian A. Hammerschmidt, Sofiane Lagraa, Radu State. 176-190 [doi]
• Defense-VAE: A Fast and Accurate Defense Against Adversarial AttacksXiang Li, Shihao Ji. 191-207 [doi]
• Analyzing and Storing Network Intrusion Detection Data Using Bayesian Coresets: A Preliminary Study in Offline and Streaming SettingsFabio Massimo Zennaro. 208-222 [doi]
• Analyzing Soccer Players' Skill Ratings Over Time Using Tensor-Based MethodsKenneth Verstraete, Tom Decroos, Bruno Coussement, Nick Vannieuwenhoven, Jesse Davis. 225-234 [doi]
• Exploring Successful Team Tactics in Soccer Tracking DataLaurentius Antonius Meerhoff, Floris R. Goes, Arie-Willem de Leeuw, Arno J. Knobbe. 235-246 [doi]
• Soccer Team VectorsRobert Müller, Stefan Langer, Fabian Ritz, Christoph Roch, Steffen Illium, Claudia Linnhoff-Popien. 247-257 [doi]
• Tactical Analyses in Professional TennisArie-Willem de Leeuw, Aldo Hoekstra, Laurentius Antonius Meerhoff, Arno J. Knobbe. 258-269 [doi]
• Difficulty Classification of Mountainbike Downhill Trails Utilizing Deep Neural NetworksStefan Langer, Robert Müller, Kyrill Schmid, Claudia Linnhoff-Popien. 270-280 [doi]
• Categorizing Online Harassment on TwitterMozhgan Saeidi, Samuel Bruno da Silva Sousa, Evangelos E. Milios, Norbert Zeh, Lilian Berton. 283-297 [doi]
• Learning to Detect Online Harassment on Twitter with the TransformerMargarita Bugueño, Marcelo Mendoza. 298-306 [doi]
• Detection of Harassment on Twitter with Deep Learning TechniquesIgnacio Espinoza, Fernanda Weiss. 307-313 [doi]
• Gradient Boosting Machine and LSTM Network for Online Harassment Detection and Categorization in Social MediaFabíola S. F. Pereira, Thiago Andrade, André C. P. L. F. de Carvalho. 314-320 [doi]
• Attention-Based Method for Categorizing Different Types of Online Harassment LanguageChristos Karatsalos, Yannis Panagiotakis. 321-330 [doi]
• SPICE: Streaming PCA Fault Identification and Classification Engine in Predictive MaintenanceCristian Axenie, Radu Tudoran, Stefano Bortoli, Mohamad Al Hajj Hassan, Alexander Wieder, Goetz Brasche. 333-344 [doi]
• Event-Based Predictive Maintenance on Top of Sensor Data in a Real Industry 4.0 Case StudyAthanasios Naskos, Georgia Kougka, Theodoros Toliopoulos, Anastasios Gounaris, Cosmas Vamvalis, Daniel Caljouw. 345-356 [doi]
• Forecasting of Product Quality Through Anomaly DetectionMehmet Dinç, Seyda Ertekin, Hadi Özkan, Can Meydanli, Volkan Atalay. 357-366 [doi]
• Data Preprocessing and Dynamic Ensemble Selection for Imbalanced Data Stream ClassificationPawel Zyblewski, Robert Sabourin, Michal Wozniak 0001. 367-379 [doi]
• A Study on Imbalanced Data StreamsEhsan Aminian, Rita P. Ribeiro, João Gama. 380-389 [doi]
• Mining Human Mobility Data to Discover Locations and HabitsThiago Andrade, Brais Cancela, João Gama. 390-401 [doi]
• Imbalanced Data Stream Classification Using Hybrid Data PreprocessingBarbara Bobowska, Jakub Klikowski, Michal Wozniak 0001. 402-413 [doi]
• A Machine Learning-Based Approach for Predicting Tool Wear in Industrial Milling ProcessesMathias Van Herreweghe, Mathias Verbeke, Wannes Meert, Tom Jacobs. 414-425 [doi]
• Cross-version Singing Voice Detection in Opera Recordings: Challenges for Supervised LearningStylianos I. Mimilakis, Christof Weiss, Vlora Arifi-Müller, Jakob Abeßer, Meinard Müller. 429-436 [doi]
• Neural Symbolic Music Genre Transfer InsightsGino Brunner, Mazda Moayeri, Oliver Richter, Roger Wattenhofer, Chi Zhang. 437-445 [doi]
• Familiar Feelings: Listener-Rated Familiarity in Music Emotion RecognitionLloyd May, Michael Casey. 446-453 [doi]
• Rhythm, Chord and Melody Generation for Lead Sheets Using Recurrent Neural NetworksCedric De Boom, Stephanie Van Laere, Tim Verbelen, Bart Dhoedt. 454-461 [doi]
• Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale HarmonizationAlexander Leemhuis, Simon Waloschek, Aristotelis Hadjakos. 462-469 [doi]
• Adaptively Learning to Recognize Symbols in Handwritten Early MusicLuisa Micó, José Oncina, José M. Iñesta. 470-477 [doi]
• Feature-Based Classification of Electric Guitar TypesRenato de Castro Rabelo Profeta, Gerald Schuller. 478-484 [doi]
• RecurSIA-RRT: Recursive Translatable Point-Set Pattern Discovery with Removal of Redundant TranslatorsDavid Meredith 0001. 485-493 [doi]
• Bow Gesture Classification to Identify Three Different Expertise Levels: A Machine Learning ApproachDavid Dalmazzo, Rafael Ramírez 0001. 494-501 [doi]
• Symbolic Music Classification Based on Multiple Sequential PatternsKerstin Neubarth, Darrell Conklin. 502-508 [doi]
• OPTISIA: An Evolutionary Approach to Parameter Optimisation in a Family of Point-Set Pattern-Discovery AlgorithmsViktor Schmuck, David Meredith 0001. 509-516 [doi]
• Predicting Dynamics in Violin Pieces with Features from Melodic MotifsFábio Jose Muneratti Ortega, Alfonso Pérez Carrillo, Rafael Ramírez. 517-523 [doi]
• Sequence Generation Using UnwordsDarrell Conklin. 524-530 [doi]
• A Machine Learning Approach to Study Expressive Performance Deviations in Classical GuitarSergio I. Giraldo, Alberto Nasarre, Isabelle Heroux, Rafael Ramirez. 531-536 [doi]
• Enhanced De-Essing via Neural NetworksSimon Hestermann, Niklas Deffner. 537-542 [doi]
• Representation, Exploration and Recommendation of PlaylistsPiyush Papreja, Hemanth Venkateswara, Sethuraman Panchanathan. 543-550 [doi]
• Results of the Seventh Edition of the BioASQ ChallengeAnastasios Nentidis, Konstantinos Bougiatiotis, Anastasia Krithara, Georgios Paliouras. 553-568 [doi]
• Selected Approaches Ranking Contextual Term for the BioASQ Multi-label Classification (Task6a and 7a)Bernd Müller, Dietrich Rebholz-Schuhmann. 569-580 [doi]
• Convolutional Neural Network for Automatic MeSH IndexingAlastair R. Rae, James G. Mork, Dina Demner-Fushman. 581-594 [doi]
• A Mixed Information Source Approach for Biomedical Question Answering: MindLab at BioASQ 7BMónica Pineda Vargas, Andrés Rosso-Mateus, Fabio A. González, Manuel Montes-y-Gómez. 595-606 [doi]
• AUEB at BioASQ 7: Document and Snippet RetrievalDimitris Pappas, Ryan T. McDonald, Georgios-Ioannis Brokos, Ion Androutsopoulos. 607-623 [doi]
• Structured Summarization of Academic PublicationsAlexios Gidiotis, Grigorios Tsoumakas. 636-645 [doi]
• How to Pre-train Your Model? Comparison of Different Pre-training Models for Biomedical Question AnsweringSanjay Kamath, Brigitte Grau, Yue Ma. 646-660 [doi]
• Yes/No Question Answering in BioASQ 2019Dimitris Dimitriadis, Grigorios Tsoumakas. 661-669 [doi]
• Semantically Corroborating Neural Attention for Biomedical Question AnsweringMarilena Oita, K. Vani, Fatma Oezdemir-Zaech. 670-685 [doi]
• Measuring Domain Portability and Error Propagation in Biomedical QAStefan Hosein, Daniel Andor, Ryan Mcdonald. 686-694 [doi]
• UNCC Biomedical Semantic Question Answering Systems. BioASQ: Task-7B, Phase-BSai Krishna Telukuntla, Aditya Kapri, Wlodek Zadrozny. 695-710 [doi]
• Transformer Models for Question Answering at BioASQ 2019Michele Resta, Daniele Arioli, Alessandro Fagnani, Giuseppe Attardi. 711-726 [doi]
• Pre-trained Language Model for Biomedical Question AnsweringWonjin Yoon, Jinhyuk Lee, Donghyeon Kim, Minbyul Jeong, Jaewoo Kang. 727-740 [doi]