Advances in Knowledge Discovery and Management: Volume 10

Author:   Rakia Jaziri ,  Arnaud Martin ,  Antoine Cornuéjols ,  Etienne Cuvelier
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2024
Volume:   1110
ISBN:  

9783031404023


Pages:   129
Publication Date:   01 February 2024
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Advances in Knowledge Discovery and Management: Volume 10


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Author:   Rakia Jaziri ,  Arnaud Martin ,  Antoine Cornuéjols ,  Etienne Cuvelier
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2024
Volume:   1110
Weight:   0.395kg
ISBN:  

9783031404023


ISBN 10:   3031404025
Pages:   129
Publication Date:   01 February 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1.New Methods for Compressing Table Constraints.- 2.Construction and Elicitation of a Black Box Model in the Game of Bridge.-  3.Knowledge graph publishing with anatomy, toward a new privacy and utility trade-off.-  4.Comparison of Short-Text Embeddings for Unsupervised Event Detection in a Stream of Tweets.- 5.Multilingual Question Answering applied to Conversational Agents.- 6.Reinforcement Learning for Expert Finding from Web Search Results.- List of Contributors.- Author Index.

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Antoine Cornuejols is Professor in Computer Science at AgroParisTech, University of Paris-Saclay. He is head of the Ekinocs research team and co-director of the H@rvest chair on the role of data sciences in agriculture. He has published a largenumber of research articles in major journals and conferences and is co-author of two books: one on Machine Learning’s concepts and algorithms (in French, 4th edition) and one on Phase Transitions in Machine Learning. He has been the general chair and program chair of several conferences, noticeably of EGC-2020 in Brussels. He has been thinking and working on artificial intelligence and machine learning since his doctorate studies at UCLA and Orsay University, from which he graduated. He is specifically interested in on line learning, transfer learning and collaborative learning, settings where the classical machine learning approach based on the assumption of a stationary environment must yield to new principles. Etienne Cuvelier is an assistant professor at ICHEC Brussels Management School (Brussels, Belgium), a trainer at CentraleSupélec Executive Education (Paris, France) and co-founder of the QUARESMI laboratory (Brussels, Belgium). After a degree in mathematics and a degree in computer science at UMons (Mons, Belgium),he started a first career in secondary, higher and social education. Etienne Cuvelier then completed a PhD in computer science at the Faculty of Computer Science of UNamur (Namur, Belgium) in 2009. His main research interests are in the area of complex data analysis (functional data, symbolic data, graphs). Arnaud Martin is full professor at University of Rennes 1 in the team DRUID of IRISA laboratory. He received a HDR (French ability to supervised research) in computer sciences (2009), a PhD degree in Signal Processing (2001), and Master in Probability (1998). Pr. Arnaud Martin joined the laboratory IRISA at the universityof Rennes 1 as full professor in 2010 and co-create the team DRUID in 2012. He teaches data fusion, data mining, and computer sciences. His research interests are mainly related to the belief functions with applications on social networks and crowdsourcing. He is author of numerous papers and invited talks. He supervised numerous Phd students. Rakia Jaziriis currently associate professor in computer science at Paris 8 University, researcherin the Artificial Intelligence Laboratory of Saint Denis (Paragraphe) and head of master program in Big Data and data mining. She is a former student of the Ecole Centrale de Lyon, she received the PhD degree in Computer Science in 2013 from the University of Paris Sorbonne in collaboration with the National Audiovisual Institute, then a post-doctorate in the field of Artificial Intelligence on massive data in particular, on algorithmsfor detecting aberrant data (suspicious behavior), the discovery of the typology of trajectories, and the prediction of the behavior of Internet users. As a member of the program committees for major conferences in her field, she has regularly organized French-speaking conferences around AI. Her research topics now focus on machine learning. She is interested in analyzing data from social networks to extract information deemed to be significant for decision support. Her work has been the subject of numerous international publications and she was able to form partnerships with industry from all over the world. Fabrice Guillet is a full professor in CS at Polytech’Nantes, the graduate engineering school of University of Nantes, France, and a member of the ” Data User Knowledge” team (DUKe) of the LS2N laboratory. He received a PhD degree in CS in 1995 from the ” École Nationale Supérieure des Télécommunications de Bretagne”, andhis Habilitation (HdR) in 2006 from Nantes university. He is a co-founder and vicepresident of the International French-speaking “Extraction et Gestion des Connaissances (EGC)” society. His research interests include knowledge quality and knowledge visualization in the frameworks of Data Science and Knowledge Management. He has co-edited two refereed books of chapter entitled “QualityMeasures in Data Min-ing” and ” Statistical Implicative Analysis — Theory and Applications” published by Springer in 2007 and 2008.

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