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| Big-Data-Oriented Intelligence Analysis Framework |
| Tang Mingwei1,2, Su Xinning2,3, Xiao Lianjie2,3 |
1. School of Information Engineering, Nanjing Audit University, Nanjing 211815;
2. Jiangsu Key Laboratory of Data Engineering and Knowledge Service (Nanjing University), Nanjing 210023;
3. School of Information Management, Nanjing University, Nanjing 210023 |
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Abstract This study analyzes the challenges and opportunities faced by intelligence studies in the era of big data and then organizes the status and future trends of current intelligence studies at home and abroad. It analyzes the challenges that information work faces in the big data era, arranges the big-data-oriented intelligence theories and methods, and sorts the theories and methods based on the general working process of intelligence studies. Next, according to the calculation characteristics and methods of big data, this study builds the big-data-oriented intelligence analysis framework from the overall architecture, functions, and implementation methods and verifies the framework’s validity by a keyword count experiment on the Spark platform. The study finally discusses some regulation problems of constructing the framework in diversified industries. The framework provides not only the basic query but also the decision service invocation driven by these theories and methods. The details required to build this framework could provide implementation guidance for the practical use of intelligence theories and methods in the big data environment.
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Received: 02 April 2018
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