Proceedings Book

Abstract

The fifteenth event of the International Conference on Machine Learning and Data Mining MLDM was held in New York (www.mldm.de) running under the umbrella of the Worldcongress “The Frontiers in Intelligent Data and Signal Analysis, DSA2019” (www.worldcongressdsa.com). For this edition the Program Committee received 245 submissions. After the peerreview process, we accepted 65 high-quality papers for oral presentation. The topics range from theoretical topics for classification, clustering, pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and web mining. Extended versions of selected papers will appear in the International Journal Transactions on Machine Learning and Data Mining (www.ibai-publishing.org/journal/mldm). A tutorial on Data Mining and a tutorial on Case-Based Reasoning were held before the conference that took pleasure to high participation of researchers and practioners from industry, social and public services. We like to thank all presenter for your high-quality presentations and the audience for your high-professional questions and inspiring comments. All that has made the conference to a living and dreadful event. The presenters and the audience went home with a full bag of new insights into different topics the research and inspiring ideas for new work and research. Besides that, gave the banquet an excellent opportunity to network among the participants and set up new co-operations. We like to thank all reviewers for their highly professional work and their effort in reviewing the papers. We also thank members of Institute of Applied Computer Sciences, Leipzig, Germany (www.ibai-institut.de) who handed the conference as secretariat. We appreciate the help and understanding of the editorial staff of ibaipublishing house (www.ibai-publishing.org) that prepared and published the proceeding books in two volumes. We invite you to join us in 2020 in New York to the next Worldcongress (www.worldcongressdsa.com) “The Frontiers in Intelligent Data and Signal Analysis, DSA2020” that combines under his roof the following three events: International Conferences Machine Learning and Data Mining MLDM, the Industrial Conference on Data Mining ICDM , and the International Conference on Mass Data Analysis of Signals and Images in Artificial Intelligence and Pattern Recognition with Application in with Applications in Medicine, r/g/b Biotechnology, Food Industries and Dietetics, Biometry and Security, Agriculture, Drug Discover, and System Biology MDA-AI&PR.
Petra Perner, July 2019

Keywords:association rules, case-based reasoning and learning, classification and interpretation of images, text, video, conceptional learning and clustering, Goodness measures and evaluaion (e.g. false discovery rates), inductive learning including decision tree and rule induction learning, knowledge extraction from text, video, signals and images, mining gene data bases and biological data bases, mining images, temporal-spatial data, images from remote sensing, mining structural representations such as log files, text documents and HTML documents, mining text documents, organisational learning and evolutional learning, probabilistic information retrieval, Sampling methods, Selection with small samples, similarity measures and learning of similarity, statistical learning and neural net based learning, video mining, visualization and data mining, Applications of Clustering, Aspects of Data Mining, Applications in Medicine, Autoamtic Semantic Annotation of Media Content, Bayesian Models and Methods, Case-Based Reasoning and Associative Memory, Classification and Model Estimation, Content-Based Image Retrieval, Decision Trees, Deviation and Novelty Detection, Feature Grouping, Discretization, Selection and Transformation, Feature Learning, Frequent Pattern Mining, High-Content Analysis of Microscopic Images in Medicine, Biotechnology and Chemistry, Learning and adaptive control, Learning/adaption of recognition and perception, Learning for Handwriting Recognition, Learning in Image Pre-Processing and Segmentation, Learning in process automation, Learning of internal representations and models, Learning of appropriate behaviour, Learning of action patterns, Learning of Ontologies, Learning of Semantic Inferencing Rules, Learning of Visual Ontologies, Learning robots, Mining Images in Computer Vision, Mining Images and Texture, Mining Motion from Sequence, Neural Methods, Network Analysis and Intrusion Detection, Nonlinear Function Learning and Neural Net Based Learning, Real-Time Event Learning and Detection, Retrieval Methods Rule Induction and Grammars Speech Analysis Statistical and Conceptual Clustering Methods Statistical and Evolutionary Learning Subspace Methods Support Vector Machines Symbolic Learning and Neural Networks in Document Processing Time Series and Sequential Pattern Mining Audio Mining, Cognition and Computer Vision, Clustering, Classification & Prediction, Statistical Learning, Association Rules, Telecommunication, Design of Experiment, Strategy of Experimentation, Capability Indices, Deviation and Novelty Detection, Control Charts, Design of Experiments, Capability Indices, Conceptional Learning, Goodness Measures and Evaluation (e.g. false discovery rates), Inductive Learning Including Decision Tree and Rule Induction Learning, Organisational Learning and Evolutional Learning, Sampling Methods, Similarity Measures and Learning of Similarity, Statistical Learning and Neural Net Based Learning, Visualization and Data Mining, Deviation and Novelty Detection, Feature Grouping, Discretization, Selection and Transformation, Feature Learning, Frequent Pattern Mining, Learning and Adaptive Control, Learning/Adaption of Recognition and Perception, Learning for Handwriting Recognition, Learning in Image Pre-Processing and Segmentation, Mining Financial or Stockmarket Data, Mining Motion from Sequence, Subspace Methods, Support Vector Machines, Time Series and Sequential Pattern Mining, Desirabilities, Graph Mining, Agent Data Mining, Applications in Software Testing