Optimization of Learning Strategies for ARTM-Based Topic Models
Topic modelling is a popular unsupervised method for text processing which provides interpretable document representation. One of the most high-level approaches, considering its capability of imitating the behaviour of various methods such as LDA or PLSA,
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Enrique Antonio de la Cal José Ramón Villar Flecha Héctor Quintián Emilio Corchado (Eds.)
Hybrid Artificial Intelligent Systems 15th International Conference, HAIS 2020 Gijón, Spain, November 11–13, 2020 Proceedings
123
Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science
Series Editors Randy Goebel University of Alberta, Edmonton, Canada Yuzuru Tanaka Hokkaido University, Sapporo, Japan Wolfgang Wahlster DFKI and Saarland University, Saarbrücken, Germany
Founding Editor Jörg Siekmann DFKI and Saarland University, Saarbrücken, Germany
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More information about this series at http://www.springer.com/series/1244
Enrique Antonio de la Cal José Ramón Villar Flecha Héctor Quintián Emilio Corchado (Eds.) •
•
•
Hybrid Artificial Intelligent Systems 15th International Conference, HAIS 2020 Gijón, Spain, November 11–13, 2020 Proceedings
123
Editors Enrique Antonio de la Cal University of Oviedo Oviedo, Spain
José Ramón Villar Flecha University of Oviedo Oviedo, Spain
Héctor Quintián University of A Coruña Ferrol, Spain
Emilio Corchado University of Salamanca Salamanca, Spain
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-030-61704-2 ISBN 978-3-030-61705-9 (eBook) https://doi.org/10.1007/978-3-030-61705-9 LNCS Sublibrary: SL7 – Artificial Intelligence © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
This volume of Lecture Notes on Artificial Intelligence (LNAI) includes accepted papers presented at the 15th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2020), held in the beautiful city of Gijón, Spain, November 2020. HAIS has become
