Online social media have transformed the face of human interaction in the 21st century. Wikis, blogs, online groups and forums, podcasts, virtual worlds, and social tagging are but a few of the applications enabling innovative behaviors that support acquisition, access, manipulation, retrieval, and visualization of information. It is, therefore, no surprise that educational practitioners and theorists have begun to explore how social media can be harnessed to describe and implement new paradigms for communication, learning, and education.

The editors' goal in publishing this book was to identify original research on the application of online social media and related technologies in education as well as emerging applications in Web technologies that could provide and shape future educational platforms. The selected contributions deal with questions such as how social media can truly enrich and enhance learning and teaching experiences in ways not otherwise possible; how learning can be integrated in a distributed and ubiquitous social computing environment; or what theories, paradigms, and models are applicable for the support of social computing in education. Researchers in education or educational software will find interesting and sometimes provocative chapters on paradigms and methodologies, virtual and mobile learning spaces, and assessment and social factors. Practitioners in these fields will benefit from an additional section devoted to case studies and first experience reports.

Ever since its inception, the Web has changed the landscape of human experiences on how we interact with one another and data through service infrastructures via various computing devices. This interweaving environment is now becoming ever more embedded into devices and systems that integrate seamlessly on how we live, both in our working or leisure time. For this volume, King and Baeza-Yates selected some pioneering and cutting-edge research work that is pointing to the future of the Web. Based on the Workshop Track of the 17th International World Wide Web Conference (WWW2008) in Beijing, they selected the top contributions and asked the authors to resubmit their work with a minimum of one third of additional material from their original workshop manuscripts to be considered for this volume. After a second-round of reviews and selection, 16 contributions were finally accepted. The work within this volume represents the tip of an iceberg of the many exciting advancements on the WWW. It covers topics like semantic web services, location-based and mobile applications, personalized and context-dependent user interfaces, social networks, and folksonomies. The presentations aim at researchers in academia and industry by showcasing latest research findings. Overall they deliver an excellent picture of the current state-of-the-art, and will also serve as the basis for ongoing research discussions and point to new directions.

This timely text/reference presents the latest advances in various aspects of social media modeling and social media computing research. Gathering together superb research from a range of established international conferences and workshops, the editors coherently organize and present each of the topics in relation to the basic principles and practices of social media modeling and computing. Individual chapters can be also be used as self-contained references on the material covered. Topics and features: presents contributions from an international selection of preeminent experts in the field; discusses topics on social-media content analysis; examines social-media system design and analysis, and visual analytic tools for event analysis; investigates access control for privacy and security issues in social networks; describes emerging applications of social media, for music recommendation, automatic image annotation, and the analysis and improvement of photo-books.

The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.*For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis. * The conference was held virtually due to the COVID-19 pandemic.

The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.*For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis. * The conference was held virtually due to the COVID-19 pandemic.

Online social media have transformed the face of human interaction in the 21st century. Wikis, blogs, online groups and forums, podcasts, virtual worlds, and social tagging are but a few of the applications enabling innovative behaviors that support acquisition, access, manipulation, retrieval, and visualization of information. It is, therefore, no surprise that educational practitioners and theorists have begun to explore how social media can be harnessed to describe and implement new paradigms for communication, learning, and education. The editors' goal in publishing this book was to identify original research on the application of online social media and related technologies in education as well as emerging applications in Web technologies that could provide and shape future educational platforms. The selected contributions deal with questions such as how social media can truly enrich and enhance learning and teaching experiences in ways not otherwise possible; how learning can be integrated in a distributed and ubiquitous social computing environment; or what theories, paradigms, and models are applicable for the support of social computing in education. Researchers in education or educational software will find interesting and sometimes provocative chapters on paradigms and methodologies, virtual and mobile learning spaces, and assessment and social factors. Practitioners in these fields will benefit from an additional section devoted to case studies and first experience reports.

Ever since its inception, the Web has changed the landscape of human experiences on how we interact with one another and data through service infrastructures via various computing devices. This interweaving environment is now becoming ever more embedded into devices and systems that integrate seamlessly on how we live, both in our working or leisure time. For this volume, King and Baeza-Yates selected some pioneering and cutting-edge research work that is pointing to the future of the Web. Based on the Workshop Track of the 17th International World Wide Web Conference (WWW2008) in Beijing, they selected the top contributions and asked the authors to resubmit their work with a minimum of one third of additional material from their original workshop manuscripts to be considered for this volume. After a second-round of reviews and selection, 16 contributions were finally accepted. The work within this volume represents the tip of an iceberg of the many exciting advancements on the WWW. It covers topics like semantic web services, location-based and mobile applications, personalized and context-dependent user interfaces, social networks, and folksonomies. The presentations aim at researchers in academia and industry by showcasing latest research findings. Overall they deliver an excellent picture of the current state-of-the-art, and will also serve as the basis for ongoing research discussions and point to new directions.

This timely text/reference presents the latest advances in various aspects of social media modeling and social media computing research. Gathering together superb research from a range of established international conferences and workshops, the editors coherently organize and present each of the topics in relation to the basic principles and practices of social media modeling and computing. Individual chapters can be also be used as self-contained references on the material covered. Topics and features: presents contributions from an international selection of preeminent experts in the field; discusses topics on social-media content analysis; examines social-media system design and analysis, and visual analytic tools for event analysis; investigates access control for privacy and security issues in social networks; describes emerging applications of social media, for music recommendation, automatic image annotation, and the analysis and improvement of photo-books.

This book constitutes the thoroughly refereed proceedings of the International Workshops on Behavior and Social Informatics and Computing, BSIC 2013, held as collocated event of IJCAI 2013, in Beijing, China in August 2013 and the International Workshop on Behavior and Social Informatics, BSI 2013, held as satellite workshop of PAKDD 2013, in Gold Coast, Australia, in April 2013. The 23 papers presented were carefully reviewed and selected from 58 submissions. The papers study a wide range of techniques and methods for behavior/social-oriented analyses including behavioral and social interaction and network, behavioral/social patterns, behavioral/social impacts, the formation of behavioral/social-oriented groups and collective intelligence and behavioral/social intelligence emergence.

The two-volume set LNAI 7120 and LNAI 7121 constitutes the refereed proceedings of the 7th International Conference on Advanced Data Mining and Applications, ADMA 2011, held in Beijing, China, in December 2011. The 35 revised full papers and 29 short papers presented together with 3 keynote speeches were carefully reviewed and selected from 191 submissions. The papers cover a wide range of topics presenting original research findings in data mining, spanning applications, algorithms, software and systems, and applied disciplines.

The two-volume set LNAI 7120 and LNAI 7121 constitutes the refereed proceedings of the 7th International Conference on Advanced Data Mining and Applications, ADMA 2011, held in Beijing, China, in December 2011. The 35 revised full papers and 29 short papers presented together with 3 keynote speeches were carefully reviewed and selected from 191 submissions. The papers cover a wide range of topics presenting original research findings in data mining, spanning applications, algorithms, software and systems, and applied disciplines.

The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually. The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The second volume, LNCS 12533, is organized in topical sections on computational intelligence; machine learning; robotics and control.

The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually. The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The third volume, LNCS 12534, is organized in topical sections on biomedical information; neural data analysis; neural network models; recommender systems; time series analysis.

The three-volume set of LNCS 12532, 12533, and 12534 constitutes the proceedings of the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020. Due to COVID-19 pandemic the conference was held virtually.The 187 full papers presented were carefully reviewed and selected from 618 submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing techniques across different domains. The first volume, LNCS 12532, is organized in topical sections on human-computer interaction; image processing and computer vision; natural language processing.

This book systematically introduces Point-of-interest (POI) recommendations in Location-based Social Networks (LBSNs). Starting with a review of the advances in this area, the book then analyzes user mobility in LBSNs from geographical and temporal perspectives. Further, it demonstrates how to build a state-of-the-art POI recommendation system by incorporating the user behavior analysis. Lastly, the book discusses future research directions in this area. This book is intended for professionals involved in POI recommendation and graduate students working on problems related to location-based services. It is assumed that readers have a basic knowledge of mathematics, as well as some background in recommendation systems.

This book is an academic publication about the global development of massive open online courses (MOOCs) and major MOOC platforms worldwide in the past decade, as well as the outlook of MOOCs in the future, with an emphasis on Greater China. The book also discusses the upsurge of the demand for online learning and MOOCs during the COVID-19 pandemic.The book is divided into three main parts - Part I: Overview of MOOCs introduces the origin and history of MOOCs and the development of MOOC platforms in Greater China and the global context; Part II: Key Issues discuss the MOOC policies, innovative pedagogy, technology, and ecosystems worldwide; and Part III: Beyond MOOCs probes into the roles and benefits of MOOCs in times of crises, as well as the outlook of MOOCs in the future. In terms of topic diversity, the book contains a comprehensive investigation of the past and latest MOOC developments, extracting and elaborating on relevant information regarding platforms, policies, pedagogy, technology, and ecosystems. Subsequently, in-depth analyses of MOOC data are utilized to deduce the current trends related to the MOOC movement and to extrapolate the likeliest direction of development for MOOCs in the years to come. The book can inform policymakers, education institutions, course instructors, platform developers, investors, researchers, and individual learners of MOOCs about critical information on the present and future of MOOC development, assisting them in making crucial decisions on what initiatives can optimize their advantages in the sector.

The volume LNCS 8866 constitutes the refereed proceedings of the 11th International Symposium on Neural Networks, ISNN 2014, held in Hong Kong and Macao, China on November/ December 2014. The 71 revised full papers presented were carefully reviewed and selected from 119 submissions. These papers cover all major topics of the theoretical research, empirical study and applications of neural networks research as follows. The focus is on following topics such as analysis, modeling, and applications.

Semi-supervised learning (SSL) has grown into an important research area in machine learning, motivated by the fact that human labeling is expensive while unlabeled data are relatively easy to obtain. A basic assumption in traditional SSL is that unlabeled data and labeled data share the same distribution. However, this assumption may be incorrect when unlabeled data have a shifted covariance, or come from a related but different domain, or contain irrelevant data. With the divergence of the distribution of unlabeled data, very little academic literature exists on how to choose or adapt machine learning algorithms to different settings of unlabeled data. This book, therefore, introduces a new unified view on learning with different settings of unlabeled data. This book consists of two parts: the first part analyzes the fundamental assumptions of SSL and proposes a few efficient SSL algorithms; the second part discusses three learning frameworks to deal with other settings of unlabeled data. This book should be helpful to researchers or graduate students in areas with abundance of unlabeled data, such as computer vision, bioinformatics, web mining, and natural language processing.