![]() ![]() For instance, most traditional machine learning algorithms are designed for data that would be completely loaded into memory, which does not hold any more in the context of big data. Nevertheless, as the time for big data is coming, the collection of data sets is so large and complex that it is difficult to deal with using traditional learning methods since the established process of learning from conventional datasets was not designed to and will not work well with high volumes of data. Over the past decade, machine learning techniques have been widely adopted in a number of massive and complex data-intensive fields such as medicine, astronomy, biology, and so on, for these techniques provide possible solutions to mine the information hidden in the data. In, the authors proposed various big data processing models and algorithms from the data mining perspective. Some authors also analyzed the new characteristics of big data in wireless networks, e.g., in terms of 5G. For example, gave a brief review of the features of big data from Internet of Things (IoT). ![]() Besides describing the fundamental techniques and technologies of big data, a number of more recent studies have investigated big data under particular context. Among these surveys, a comprehensive overview of the big data from three different angles, i.e., innovation, competition, and productivity, was presented by the McKinsey Global Institute (MGI). To clarify what the big data refers to, several good surveys have been presented recently and each of them views the big data from different perspectives, including challenges and opportunities, background and research status, and analytics platforms. Therefore, the term “Big Data” was coined to capture the profound meaning of this data explosion trend. According to, in 2011, digital information has grown nine times in volume in just 5 years and its amount in the world will reach 35 trillion gigabytes by 2020. Particularly, digital data, generated from a variety of digital devices, are growing at astonishing rates. Large-scale data sets are collected and studied in numerous domains, from engineering sciences to social networks, commerce, biomolecular research, and security. It is obvious that we are living in a data deluge era, evidenced by the phenomenon that enormous amount of data have been being continually generated at unprecedented and ever increasing scales. ![]()
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