Download Big data Related Technologies, Challenges and Future by Min Chen PDF

By Min Chen

ISBN-10: 3319062441

ISBN-13: 9783319062440

This Springer short offers a accomplished assessment of the historical past and up to date advancements of huge information. the price chain of huge facts is split into 4 stages: facts new release, facts acquisition, information garage and knowledge research. for every section, the booklet introduces the overall history, discusses technical demanding situations and experiences the newest advances. applied sciences below dialogue contain cloud computing, web of items, facts facilities, Hadoop and extra. The authors additionally discover a number of consultant purposes of massive facts reminiscent of firm administration, on-line social networks, healthcare and scientific functions, collective intelligence and clever grids. This e-book concludes with a considerate dialogue of attainable study instructions and improvement tendencies within the box. gigantic information: similar applied sciences, demanding situations and destiny customers is a concise but thorough exam of this intriguing quarter. it truly is designed for researchers and execs attracted to large information or similar examine. Advanced-level scholars in computing device technological know-how and electric engineering also will locate this publication worthy.

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Big data Related Technologies, Challenges and Future Prospects

This Springer short offers a complete assessment of the history and up to date advancements of massive facts. the worth chain of massive info is split into 4 stages: information iteration, information acquisition, information garage and information research. for every part, the publication introduces the final history, discusses technical demanding situations and experiences the most recent advances.

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The digital universe decade-are you ready. External Publication of IDC (Analyse the Future) Information and Data, pages 1–16, 2010. 3. Douglas Laney. 3-d data management: Controlling data volume, velocity and variety. META Group Research Note, February, 6, 2001. 4. Kenneth Cukier. Data, data everywhere: A special report on managing information. Economist Newspaper, 2010. 5. Paul Zikopoulos, Chris Eaton, et al. Understanding big data: Analytics for enterprise class hadoop and streaming data. McGraw-Hill Osborne Media, 2011.

Web crawler is a program used by search engines for downloading and storing web pages [18]. Generally speaking, web crawler starts from the uniform resource locator (URL) of an initial web page to access other linked web pages, during which it stores and sequences all the retrieved URLs. Web crawler acquires a URL in the order of precedence through a URL queue and then downloads web pages, and identifies all URLs in the downloaded web pages, and extracts new URLs to be put in the queue. 2 Big Data Acquisition 25 process is repeated until the web crawler is stopped.

Data integration: A theoretical perspective. In Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, pages 233–246. ACM, 2002. 39. Wiki. Applications and organizations using hadoop. org/hadoop/ PoweredBy, 2013. 40. Michael J Cafarella, Alon Halevy, and Nodira Khoussainova. Data integration for the relational web. Proceedings of the VLDB Endowment, 2(1):1090–1101, 2009. 41. Jonathan I Maletic and Andrian Marcus. Data cleansing: Beyond integrity analysis.

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Big data Related Technologies, Challenges and Future Prospects by Min Chen

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