These papers on Intelligent Data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines. The papers derive from the 2013 IDAM conference in Kaohsiung ,Taiwan. It is an interdisciplinary research field involving academic researchers in information technologies, computer science, public policy, bioinformatics, medical informatics, and social and behavior studies, etc. The techniques studied include (but are not limited to): data visualization, data pre-processing, data engineering, database mining techniques, tools and applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing, etc.

The proceedings from the eighth KMO conference represent the findings of this international meeting which brought together researchers and developers from industry and the academic world to report on the latest scientific and technical advances on knowledge management in organizations. This conference provided an international forum for authors to present and discuss research focused on the role of knowledge management for innovative services in industries, to shed light on recent advances in social and big data computing for KM as well as to identify future directions for researching the role of knowledge management in service innovation and how cloud computing can be used to address many of the issues currently facing KM in academia and industrial sectors.

Proceedings from the 2013 LTEC conference in Kaohsiung, Taiwan. The papers examine diverse aspects of Learning Technology for Education in Cloud environments, including social, technical and infrastructure implications. Also addressed is the question of how cloud computing can be used to design applications to support real time on demand learning using technologies. The workshop proceedings provide opportunities for delegates to discuss the latest research in TEL (Technology Enhanced Learning) and its impacts for learners and institutions, using cloud technologies.

The proceedings from the  eighth KMO conference represent the findings of this international meeting which brought together researchers and developers from industry and the academic world to report on the latest scientific and technical advances on knowledge management in organizations. This conference provided an international forum for authors to present and discuss research focused on the role of knowledge management for innovative services in industries, to shed light on recent advances in social and big data computing for KM as well as to identify future directions for researching the role of knowledge management in service innovation and how cloud computing can be used to address many of the issues currently facing KM in academia and industrial sectors.

This book constitutes the refereed proceedings of the 2014 Multidisciplinary International Social Networks Research, MISNC 2014, held in Kaohsiung, Taiwan, in September 2014. The 37 full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on electronic commerce, e-business management, and social networks; social networks issues on sociology, politics and statistics; information technology for social networks analysis and mining; social networks for global eHealth and bio-medics; security, open data, e-learning and other related topics; intelligent data analysis and its applications.

These papers on Intelligent Data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines. The papers derive from the 2013 IDAM conference in Kaohsiung ,Taiwan. It is an interdisciplinary research field involving academic researchers in information technologies, computer science, public policy, bioinformatics, medical informatics, and social and behavior studies, etc. The techniques studied include (but are not limited to): data visualization, data pre-processing, data engineering, database mining techniques, tools and applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing, etc.

Proceedings from the 2013 LTEC conference in Kaohsiung, Taiwan. The papers examine diverse aspects of Learning Technology for Education in Cloud environments, including social, technical and infrastructure implications. Also addressed is the question of how cloud computing can be used to design applications to support real time on demand learning using technologies. The workshop proceedings provide opportunities for delegates to discuss the latest research in TEL (Technology Enhanced Learning) and its impacts for learners and institutions, using cloud technologies.