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The three volume proceedings LNAI 11906 – 11908 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, held in Würzburg, Germany, in September 2019. The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track. The contributions were organized in topical sections named as follows: Part I: pattern mining; clustering, anomaly and outlier detection, and autoencoders; dimensionality reduction and feature selection; social networks and graphs; decision trees, interpretability, and causality; strings and streams; privacy and security; optimization. Part II: supervised learning; multi-label learning; large-scale learning; deep learning; probabilistic models; natural language processing. Part III: reinforcement learning and bandits; ranking; applied data science: computer vision and explanation; applied data science: healthcare; applied data science: e-commerce, finance, and advertising; applied data science: rich data; applied data science: applications; demo track.
The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and ...
This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.
This book constitutes the refereed proceedings of the 11th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2015, held in Hamburg, Germany in July 2015. The 41 full papers presented were carefully reviewed and selected from 123 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for “Extraction et Gestion des Connaissances” in French), which is concerned with, among others, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and SemanticWeb. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2009 Conference held in Strasbourg, France on January 2009. The volume is organized in four parts. Part I includes five papers concerned by various aspects of supervised learning or information retrieval. Part II presents five papers concerned with unsupervised learning issues. Part III includes two papers on data streaming and two on security while in Part IV the last four papers are concerned with ontologies and semantic.
Advances in hardware, software, and audiovisual rendering technologies of recent years have unleashed a wealth of new capabilities and possibilities for multimedia applications, creating a need for a comprehensive, up-to-date reference. The Encyclopedia of Multimedia Technology and Networking provides hundreds of contributions from over 200 distinguished international experts, covering the most important issues, concepts, trends, and technologies in multimedia technology. This must-have reference contains over 1,300 terms, definitions, and concepts, providing the deepest level of understanding of the field of multimedia technology and networking for academicians, researchers, and professionals worldwide.
This book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2010, held in Paisley, Scotland, in September 2010. The 47 revised full papers presented were carefully reviewed and selected from many submissions for inclusion in the book and present the latest theoretical advances and real-world applications in computational intelligence.
This book constitutes the refereed proceedings of the 21 International Conference on Database and Expert Systems Applications, DEXA 2010, held in Bilbao, Spain, August 30 - September 3, 2010. The 45 revised full papers and 36 short papers were carefully reviewed and selected from 197 submissions. The papers are organized in topical sections on Data Mining Systems, Parallelism and Query Planning, Data Warehousing and Decision Support Systems, Temporal, Spatial and High Dimensional Databases, Data Mining Algorithms, Information Retrieval, Query Processing and Optimization.
The illustrations in this book are created by “Team Educohack”. Data Science and AI Simplified provides comprehensive knowledge on the theories, techniques, and applications in Analytics, Data Science, and Artificial Intelligence (AI). We cover the entire analytics process, from data collection and processing to analysis and interpretation, helping you derive valuable insights that can significantly impact businesses. We explain data science, focusing on how to transform raw data into valuable information for strategic business development. By analyzing large amounts of structured and unstructured data, organizations can identify patterns, reduce costs, and increase performance and efficiency. Our book also explores AI, demonstrating how machines learn from experience, adapt to new inputs, and perform human-like tasks. From chess-playing computers to self-driving cars, we delve into AI applications that rely on deep learning and natural language processing. Whether you're a beginner or looking to expand your expertise, Data Science and AI Simplified offers clear, easy-to-understand explanations and practical examples, ensuring a thorough grasp of these essential fields.
Examines recent advances and surveys of applications in text and web mining which should be of interest to researchers and end-users alike.