Hossam HakeemLayered Software Patterns for Data Analysis in Big Data Environment. International Journal of Automation and Computing, vol. 14, no. 6, pp. 650-660, 2017. DOI: 10.1007/s11633-016-1043-x
Citation: Hossam HakeemLayered Software Patterns for Data Analysis in Big Data Environment. International Journal of Automation and Computing, vol. 14, no. 6, pp. 650-660, 2017. DOI: 10.1007/s11633-016-1043-x

Layered Software Patterns for Data Analysis in Big Data Environment

  • The proliferation of textual data in society currently is overwhelming, in particular, unstructured textual data is being constantly generated via call centre logs, emails, documents on the web, blogs, tweets, customer comments, customer reviews, etc. While the amount of textual data is increasing rapidly, users' ability to summarise, understand, and make sense of such data for making better business/living decisions remains challenging. This paper studies how to analyse textual data, based on layered software patterns, for extracting insightful user intelligence from a large collection of documents and for using such information to improve user operations and performance.
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