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图书名称： Big Data in Complex Systems: Challenges and Opportunities (Studies in Big Data) Hardcover – January 3, 2015, Studies in Big Data Volume 9
作者： Aboul-Ella Hassanien (Editor), Ahmad Taher Azar (Editor), Vaclav Snasel (Editor), & 2 more
出版社：Springer International Publishing
页数：314
出版时间：2014
语言：English
格式：pdf
内容简介：
Big data refers to large and complex massive amounts of data sets that it becomes
difficult to process and analyze using traditional data processing technology. Over
the past few years there has been an exponential growth in the rate of available data
sets obtained from complex systems, ranging from the interconnection of millions
of users in social media data, cheminformatics, hydroinformaticsto the information
contained in the complex biological data sets. This taking and opened new chal-
lenges and opportunities to researcher and scientists on how to acquisition, Record-
ing, store and manipulate this huge amount of data sets and how to develop new
tools, mining, study, and visualize the massive amount data sets and what insight
can we learn from systems that were previously not understood due to the lack of
information. All these aspect, coming from multiple disciples under the theme of
big data and their features.
The ultimate objectives of this volume are to provide challenges and Opportuni-
ties to the research communities with an updated, in-depth material on the applica-
tion of Big data in complex systems in order to finding solutions to the challenges
and problems facing big data sets applications. Much data today is not natively in
structured format; for example, tweets and blogs are weakly structured pieces of
text, while images and video are structured for storage and display, but not for se-
mantic content and search: transforming such content into a structured format for
later analysis is a major challenge. Data analysis, organization, retrieval, and mod-
eling are other foundational challenges. Data analysis is a clear bottleneck in many
applications, both due to lack of scalability of the underlying algorithms and due
to the complexity of the data that needs to be analyzed. Finally, presentation of the
results and its interpretation by non-technical domain experts is crucial to extract-
ing actionable knowledge. A major investment in Big Data, properly directed, can
result not only in major scientific advances, but also lay the foundation for the next
generation of advances in science, medicine, and business.
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