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Multilayer Social Networks
This book unifies and consolidates methods for analyzing multilayer networks arising from the social and physical sciences and computing.
Large-Scale Data Analytics
This edited book collects state-of-the-art research related to large-scale data analytics that has been accomplished over the last few years. This is among the first books devoted to this important area based on contributions from diverse scientific areas such as databases, data mining, supercomputing, hardware architecture, data visualization, statistics, and privacy. There is increasing need for new approaches and technologies that can analyze and synthesize very large amounts of data, in the order of petabytes, that are generated by massively distributed data sources. This requires new distributed architectures for data analysis. Additionally, the heterogeneity of such sources imposes sig...
Scalable Uncertainty Management
This book constitutes the refereed proceedings of the Second International Conference on Scalable Uncertainty Management, SUM 2008, held in Naples, Italy, in Oktober 2008. The 27 revised full papers presented together with the extended abstracts of 3 invited talks/tutorials were carefully reviewed and selected from 42 submissions. The papers address artificial intelligence researchers, database researchers, and practitioners to demonstrate theoretical techniques required to manage the uncertainty that arises in large scale real world applications and to cope with large volumes of uncertainty and inconsistency in databases, the Web, the semantic Web, and artificial intelligence in general.
Complex Networks and Their Applications XI
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XI International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2022). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks and technological networks.
Scalable Uncertainty Management
Managing uncertainty and inconsistency has been extensively explored in - ti?cial Intelligence over a number of years. Now with the advent of massive amounts of data and knowledge from distributed heterogeneous,and potentially con?icting, sources, there is interest in developing and applying formalisms for uncertainty andinconsistency widelyin systems that need to better managethis data and knowledge. The annual International Conference on Scalable Uncertainty Management (SUM) has grown out of this wide-ranging interest in managing uncertainty and inconsistency in databases, the Web, the Semantic Web, and AI. It aims at bringing together all those interested in the management of large volume...
Flexible Databases Supporting Imprecision and Uncertainty
This volume offers the advice of selected expert contributors on the application of heterogeneous methods for managing uncertainty and imprecision in databases. It contains both survey chapters on classic topics such as "flexible querying in databases", and up to date information on "database models to represent imperfect data". Further, it includes specific contributions on uncertainty management in database integration, and in representing and querying semistructured and spatial data.
Social Informatics
The two-volume set LNCS 11185 + 11186 constitutes the proceedings of the 10th International Conference on Social Informatics, SocInfo 2018, held in Saint-Petersburg, Russia, in September 2018. The 30 full and 32 short papers presented in these proceedings were carefully reviewed and selected from 110 submissions. They deal with the applications of methods of the social sciences in the study of socio-technical systems, and computer science methods to analyze complex social processes, as well as those that make use of social concepts in the design of information systems.
The Influence of Technology on Social Network Analysis and Mining
The study of social networks was originated in social and business communities. In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging systems, which are widely analyzed using graph theory and machine learning techniques. People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution. This has led to a rising prominence of SNAM in academia, politics, homeland security and business. This follows the pattern of known entities of our society that have evolved into networks in which actors are increasingly dependent on their structural embedding General areas of interest to the book include information science and mathematics, communication studies, business and organizational studies, sociology, psychology, anthropology, applied linguistics, biology and medicine.
Database Systems for Advanced Applications
This two volume set LNCS 9049 and LNCS 9050 constitutes the refereed proceedings of the 20th International Conference on Database Systems for Advanced Applications, DASFAA 2015, held in Hanoi, Vietnam, in April 2015. The 63 full papers presented were carefully reviewed and selected from a total of 287 submissions. The papers cover the following topics: data mining; data streams and time series; database storage and index; spatio-temporal data; modern computing platform; social networks; information integration and data quality; information retrieval and summarization; security and privacy; outlier and imbalanced data analysis; probabilistic and uncertain data; query processing.
