Andreas Hotho – författare

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 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.

Chapter "Incorporating Dependencies in Spectral Kernels for Gaussian Processes" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

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.

Chapter "Heavy-tailed Kernels Reveal a Finer Cluster Structure in t-SNE Visualisations" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book constitutes the proceedings of the 47th German Conference on AI, KI 2024, which was held in Würzburg, Germany, during September 25–27, 2024.

The 19 full papers, 7 short papers and 5 other papers presented in this book were carefully reviewed and selected from 63 submissions. KI is one of the major European AI conferences and traditionally brings together academic and industrial researchers from all areas of AI, providing an ideal place for exchanging news and research results on theory and applications. The papers have been categorized into the following sections: full technical papers;  technical communications; extended abstracts of papers from other AI conferences.

This book introduces and reviews recent advances inthe field in a comprehensive and non-technical way by focusing on the potentialof emerging citizen-science and social-computation frameworks, coupled with thelatest theoretical and modeling tools developed by physicists, mathematicians,computer and social scientists to analyse, interpret and visualize complex datasets.

There is overwhelming evidence that the currentorganisation of our economies and societies is seriously damaging biologicalecosystems and human living conditions in the short term, with potentiallycatastrophic effects in the long term. The need to re-organise the dailyactivities with the greatest impact – energy consumption, transport, housing –towards a more efficient and sustainable development model has recently beenraised in the public debate on several global, environmental issues. Above all,this requires the mismatch between global, societal and individual needs to beaddressed. Recent advancesin Information and Communication Technologies (ICT)can trigger important transitions at the individual and collective level toachieve this aim.

Based on the findings of the collaborative researchnetwork EveryAware the following developments among the emerging ICTtechnologies are discussed in depth in this volume:

• Participatory sensing – where ICT development ispushed to the level where it can supportinformed action at the hyperlocal scale, providing capabilities forenvironmental monitoring, data aggregation and mining, as well as informationpresentation and sharing.

• Web gaming, social computing and internet-mediatedcollaboration – where the Web will continue to acquire the status of aninfrastructure for social computing, allowing users’ cognitive abilities to becoordinated in online communities, and steering the collective action towardspredefined goals.

• Collective awareness and decision-making – where theaccess to both personal and community data, collected by users, processed withsuitable analysis tools, and re-presented in an appropriate format by usablecommunication interfaces leads to a bottom-up development of collective socialstrategies.

This book constitutes the joint thoroughly refereed post-proceedings of The Modeling Social Media Workshop, MSM 2010 held in Toronto, Canada in June 2010 and the International Workshop on Mining Ubiquitous and Social Environments, MUSE 2010, held in Barcelona, Spain in September 2010.

The eight revised full papers included were carefully reviewed and selected after two rounds of reviewing and revision. The papers address various aspects of the analysis and engineering of socio-computational systems in which social, ubiquitous and computational processes are interdependent and tightly interwoven