caa a22 4500 605478228 CHVBK 20210128100404.0 cr unu---uuuuu 210128e20150901xx s 000 0 eng 10.1007/s10994-015-5512-1 doi (NATIONALLICENCE)springer-10.1007/s10994-015-5512-1 Incremental learning of event definitions with Inductive Logic Programming [Elektronische Daten] [Nikos Katzouris, Alexander Artikis, Georgios Paliouras] Event recognition systems rely on knowledge bases of event definitions to infer occurrences of events in time. Using a logical framework for representing and reasoning about events offers direct connections to machine learning, via Inductive Logic Programming (ILP), thus allowing to avoid the tedious and error-prone task of manual knowledge construction. However, learning temporal logical formalisms, which are typically utilized by logic-based event recognition systems is a challenging task, which most ILP systems cannot fully undertake. In addition, event-based data is usually massive and collected at different times and under various circumstances. Ideally, systems that learn from temporal data should be able to operate in an incremental mode, that is, revise prior constructed knowledge in the face of new evidence. In this work we present an incremental method for learning and revising event-based knowledge, in the form of Event Calculus programs. The proposed algorithm relies on abductive-inductive learning and comprises a scalable clause refinement methodology, based on a compressive summarization of clause coverage in a stream of examples. We present an empirical evaluation of our approach on real and synthetic data from activity recognition and city transport applications. The Author(s), 2015 Incremental learning nationallicence Abductive-Inductive Logic Programming nationallicence Event Calculus nationallicence Event recognition nationallicence Katzouris Nikos Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, Athens, Greece aut Artikis Alexander Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, Athens, Greece aut Paliouras Georgios Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, Athens, Greece aut Machine Learning Springer US; http://www.springer-ny.com 100/2-3(2015-09-01), 555-585 0885-6125 100:2-3<555 2015 100 10994 https://doi.org/10.1007/s10994-015-5512-1 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10994-015-5512-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Katzouris Nikos Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, Athens, Greece aut NATIONALLICENCE 700 1- Artikis Alexander Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, Athens, Greece aut NATIONALLICENCE 700 1- Paliouras Georgios Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, Athens, Greece aut NATIONALLICENCE 773 0- Machine Learning Springer US; http://www.springer-ny.com 100/2-3(2015-09-01), 555-585 0885-6125 100:2-3<555 2015 100 10994