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Multimedia big data analytics: a survey
Pouyanfar S., Yang Y., Chen S., Shyu M., Iyengar S. ACM Computing Surveys51 (1):1-34,2018.Type:Article
Date Reviewed: Jan 16 2019

Big data continues to grow exponentially. One source of that growth--multimedia data--has not received comprehensive study. The authors correct this deficit by presenting the results of a broad multidimensional survey of the literature related to multimedia big data.

The authors present the motivation for their research: the bifurcation in big data analytics between studies of multimedia challenges and studies of their solutions. In detailing the prior research on each fork of that divide and suggesting paths for future exploration, they also present a succinct nontechnical overview of the field of big data.

Effectively employing charts and tables, the article captures the scope of the data generated by social media, smartphones, surveillance devices, and others sources, including the Internet of Things (IoT), and outlines methods for the retrieval, storage, mining, and management of the data streams. The authors identify large-scale datasets, index strategies used to manage the data, and data mining tools. They also point out developing ways of confronting the challenges posed by the burgeoning scale of multimedia big data. These include upgrading storage infrastructure; developing database algorithms that can tackle massive, highly diverse, and loosely structured datasets; devising visualizations to summarize big data; employing more robust cloud storage; improving data security; and realizing the promise of machine learning.

Technical and nontechnical readers will come away with a better understanding of multimedia big data, the current approaches to managing the data, and the road ahead.

Reviewer:  Marlin Thomas Review #: CR146381 (1904-0117)
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