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The massive volume of data generated in modern applications can overwhelm our ability to conveniently transmit, store, and index it. For many scenarios, building a compact summary of a dataset that is vastly smaller enables flexibility and efficiency in a range of queries over the data, in exchange for some approximation. This comprehensive introduction to data summarization, aimed at practitioners and students, showcases the algorithms, their behavior, and the mathematical underpinnings of their operation. The coverage starts with simple sums and approximate counts, building to more advanced probabilistic structures such as the Bloom Filter, distinct value summaries, sketches, and quantile summaries. Summaries are described for specific types of data, such as geometric data, graphs, and vectors and matrices. The authors offer detailed descriptions of and pseudocode for key algorithms that have been incorporated in systems from companies such as Google, Apple, Microsoft, Netflix and Twitter.

Big data. --- Big data

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Big data --- Big data.

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Extremely large, diverse, and complex data sets are generated from scientific instruments, sensors, social media, Internet and other applications End to end management, analysis, and visualization of these large, distributed and heterogeneous data sets has been a major challenge impeding scientific discovery and technological advancement The 2013 IEEE international Conference on Big Data will provide the scientific community a dedicated forum for discussing state of the art research, development, and deployment efforts for the end to end management, storage, sharing, analysis, and visualization of very large data sets The BigData2012 workshop will be an excellent forum to help the community define the current state, determine future goals, and present architectures and services for future data management technologies supporting Big Data and data intensive computing.

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Annotation This conference focuses on big data computing services and applications This international conference is established to address the needs for big data computing service researchers, domain specific researchers, government agencies, and practitioners The major objective is to provide a big platform for them to exchange innovation ideas and research results, and share application experiences and lessons The three major objectives of this conference include Big Data Innovation of big data computing and service models, theories, tools, solutions and technologies Big Data and Service Sharing in big data banks and resources, portals, platforms, and open sources, technology and tools Big Data Application in real world big data application service projects for major application domains, including energy and environment, medical and healthcare, library, social media and networking, and education.

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Annotation The 16th International Conference on Computer and Information Science (ICIS 2017) brings together scientists, engineers, computer users and students to exchange and share their experiences, new ideas and research results about all aspects (theory, applications and tools) of computer and information science and discuss the practical challenges encountered and the solutions adopted.

Big data