Turn kids onto science with these exciting Internet learning adventures. The 88 lessons in this book connect young learners to the incredible array of science knowledge and resources on the Internet. Each unit includes engaging activities and Internet research projects based on specific science concepts, along with discussion questions and lists of relevant Web sites and related literature. Grades K-6.

This book constitutes the proceedings of the 17th International Conference on Discovery Science, DS 2014, held in Bled, Slovenia, in October 2014. The 30 full papers included in this volume were carefully reviewed and selected from 62 submissions. The papers cover topics such as: computational scientific discovery; data mining and knowledge discovery; machine learning and statistical methods; computational creativity; mining scientific data; data and knowledge visualization; knowledge discovery from scientific literature; mining text, unstructured and multimedia data; mining structured and relational data; mining temporal and spatial data; mining data streams; network analysis; discovery informatics; discovery and experimental workflows; knowledge capture and scientific ontologies; data and knowledge integration; logic and philosophy of scientific discovery; and applications of computational methods in various scientific domains.

This book constitutes the refereed proceedings of the 14th International Conference on Discovery Science, DS 2011, held in Espoo, Finland, in October 2011 - co-located with ALT 2011, the 22nd International Conference on Algorithmic Learning Theory. The 24 revised full papers presented together with 5 invited lectures were carefully revised and selected from 56 submissions. The papers cover a wide range including the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their application to knowledge discovery.

Many difficult scientific discovery tasks can only be solved in interactive ways, by combining intelligent computing techniques with intuitive and adaptive user interfaces. It is inevitable to use human intelligence in scientific discovery systems: human eyes can capture complex patterns and relationships, along with detecting the exceptional cases in a data set; the human brain can easily manipulate perceptions to make decisions. Ambient intelligence is about this kind of ubiquitous and autonomous human interaction with information. Scientific discovery is a process of creative perception and communication, dealing with questions like: how do we significantly reduce information while maintaining meaning, or how do we extract patterns from massive data and growing data resources. Originating from the SIGCHI Workshop on Ambient Intelligence for Scientific Discovery, this state-of-the-art survey is organized in three parts: new paradigms in scientific discovery, ambient cognition, and ambient intelligence systems. Many chapters share common features such as interaction, vision, language, and biomedicine.

This survey provides an introduction to computational approaches to the discovery of communicable scientific knowledge and details recent advances. It is partly inspired by the contributions of the International Symposium on Computational Discovery of Communicable Knowledge, held in Stanford, CA, USA in March 2001, a number of additional invited contributions provide coverage of recent research in computational discovery.

This book constitutes the refereed proceedings of the 7th International Conference on Discovery Science, DS 2004, held in Padova, Italy in October 2004. The 20 revised long papers and the 19 revised regular papers presented were carefully reviewed and selected from 80 submissions. The papers are organized in topical sections on pattern mining, classification, outlier detection, clustering, feature construction and generation, knowledge acquisition, discovery science in reality, machine learning algorithms, Web mining, applications of predictive methods, and interdisciplinary approaches.

This book constitutes the proceedings of the 20th International Conference on Discovery Science, DS 2017, held in Kyoto, Japan, in October 2017, co-located with the International Conference on Algorithmic Learning Theory, ALT 2017. The 18 revised full papers presented together with 6 short papers and 2 invited talks in this volume were carefully reviewed and selected from 42 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in topical sections on machine learning: online learning, regression, label classification, deep learning, feature selection, recommendation system; and knowledge discovery: recommendation system, community detection, pattern mining, misc.

This book constitutes the refereed proceedings of the 20th International Conference on The Semantic Web, ESWC 2023, held in Hersonissos, Crete, Greece, during May 28–June 1, 2023. The 41 full papers included in this book were carefully reviewed and selected from 167 submissions. They are organized in topical sections as follows: research, resource and in-use.