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For a long time an automatic detection of contacts between humans was not possible. In this work a new generation of resource-aware RFID tags (proximity tags) is used which has the ability to detect reliable face-to-face contacts. This innovation opens up new research possibilities in the ?elds of human contact behaviour analysis, link prediction and indoor localisation. In this context the identi?cation of human contact structures and their underlying pro¬cesses is a prominent research topic. However, the analysis of of?ine social networks has been largely neglected. In this work face-to-face information is utilised to study the link prediction problem as well as dynamic and static contact...
The success of diagnostic knowledge systems has been proved over the last decades. Nowadays, intelligent systems are embedded in machines within various domains or are used in interaction with a user for solving problems. However, the development of a knowledge system is still a critical issue. Similarly to projects dealing with customized software at a highly innovative level a precise specification often cannot be given in advance. Moreover, necessary requirements of the knowledge system can be defined not until the project has been started or are changing during the development phase. This thesis motivates that classical, document-centered approaches cannot be applied in such a setting. W...
This book constitutes the refereed proceedings of the 6th International Conference on Case-Based Reasoning, ICCBR 2005, held in Chicago, IL, USA, in August 2005. The 19 revised full research papers and 26 revised poster papers presented together with the abstracts of 3 invited talks were carefully reviewed and selected from 74 submissions. The papers address all current foundational, theoretical and research aspects of case-based reasoning as well as advanced applications either with innovative commercial deployment or practical, social, environmental or economic significance.
This book introduces and reviews recent advances in the field in a comprehensive and non-technical way by focusing on the potential of emerging citizen-science and social-computation frameworks, coupled with the latest theoretical and modeling tools developed by physicists, mathematicians, computer and social scientists to analyse, interpret and visualize complex data sets. There is overwhelming evidence that the current organisation of our economies and societies is seriously damaging biological ecosystems and human living conditions in the short term, with potentially catastrophic effects in the long term. The need to re-organise the daily activities with the greatest impact – energy con...
The significance of big data can be observed in any decision-making process as it is often used for forecasting and predictive analytics. Additionally, big data can be used to build a holistic view of an enterprise through a collection and analysis of large data sets retrospectively. As the data deluge deepens, new methods for analyzing, comprehending, and making use of big data become necessary. Enterprise Big Data Engineering, Analytics, and Management presents novel methodologies and practical approaches to engineering, managing, and analyzing large-scale data sets with a focus on enterprise applications and implementation. Featuring essential big data concepts including data mining, artificial intelligence, and information extraction, this publication provides a platform for retargeting the current research available in the field. Data analysts, IT professionals, researchers, and graduate-level students will find the timely research presented in this publication essential to furthering their knowledge in the field.
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The 9 papers presented in this book are revised and significantly extended versions of papers submitted to three related workshops: The 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and the First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, which were held on September 15, 2014, in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2014) in Nancy, France; and the 5th International Workshop on Modeling Social Media (MSM 2014) that was held on April 8, 2014 in conjunction with ACM WWW in Seoul, Korea.
The 7 papers presented in this book are revised and significantly extended versions of papers submitted to three related workshops: 6th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2015, held in Porto, Portugal, September 2015, in conjunction with the 6th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2015; 6th International Workshop on Modeling Social Media, MSM 2015, held in Florence, Italy, May 2015, in conjunction with the 24th International World Wide Web Conference, WWW 2015; 7th International Workshop on Modeling Social Media, MSM 2016, Montreal, QC, Canada, April 2016, in conjunction with the 25th International World Wide Web Conference, WWW 2016.
This book constitutes the joint thoroughly refereed post-proceedings of the Second International Workshop on Modeling Social Media, MSM 2011, held in Boston, MA, USA, in October 2011, and the Second International Workshop on Mining Ubiquitous and Social Environments, MUSE 2011, held in Athens, Greece, in September 2011. The 9 full papers included in the book are revised and significantly extended versions of papers submitted to the workshops. They cover a wide range of topics organized in three main themes: communities and networks in ubiquitous social media; mining approaches; and issues of user modeling, privacy and security.