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Database management. --- Electronic data processing --- Distributed processing.

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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 volumes of uncertainty and inconsistency, irrespective of whether they are in databases,the Web, the Semantic Web, or in AI, as well as in other areas such as information retrieval, risk analysis, and computer vision, where signi?cant computational - forts are needed. After a promising First International Conference on Scalable Uncertainty Management was held in Washington DC, USA in 2007, the c- ference series has been successfully held in Napoli, Italy, in 2008, and again in Washington DC, USA, in 2009.

Uncertainty (Information theory) --- Artificial intelligence --- Engineering & Applied Sciences --- Mechanical Engineering --- Computer Science --- Mechanical Engineering - General --- Information Technology --- Artificial Intelligence --- Computer science. --- Computer communication systems. --- Database management. --- Data mining. --- Information storage and retrieval. --- Artificial intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Computer Communication Networks. --- Data Mining and Knowledge Discovery. --- Information Systems Applications (incl. Internet). --- Information Storage and Retrieval. --- Database Management. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Informatics --- Science --- Distributed processing --- Information storage and retrieva. --- Artificial Intelligence. --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software

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Due to the growing need to process large graph and network datasets created by modern applications, recent years have witnessed a surging interest in developing big graph platforms. Tens of such big graph systems have already been developed, but there lacks a systematic categorization and comparison of these systems. This article provides a timely and comprehensive survey of existing big graph systems, and summarizes their key ideas and technical contributions from various aspects. In addition to the popular vertex-centric systems which espouse a think-like-a-vertex paradigm for developing parallel graph applications, this survey also covers other programming and computation models, contrasts those against each other, and provides a vision for the future research on big graph analytics platforms. This survey aims to help readers get a systematic picture of the landscape of recent big graph systems, focusing not just on the systems themselves, but also on the key innovations and design philosophies underlying them.

Network analysis (Planning)