Title: A framework for combining software patterns with semantic web for unstructured data analysis

Authors: Hossam Hakeem

Addresses: Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

Abstract: Unstructured data is heterogeneous and variable in nature and comes in many formats, including text document (Word documents, e.g., can be converted to text), image, audio and video. Unstructured data is growing faster than structured data. It will account for 90% of all data created in the near future. Unstructured data analytics can reveal important interrelationships that were previously difficult or impossible to determine and is currently seeking to gain richer, deeper, and more accurate insights into the business and social life for gaining competitive advantage and serve society better. To realise the full potential of unstructured data analysis, new approaches need to be developed. This paper proposes an approach to combining software patterns with semantic web for constructing a data analysis framework for the above-mentioned unstructured data.

Keywords: patterns; unstructured data; semantic web; data analysis.

DOI: 10.1504/IJCAT.2018.095775

International Journal of Computer Applications in Technology, 2018 Vol.58 No.3, pp.225 - 240

Received: 16 Jun 2017
Accepted: 18 Sep 2017
Published online: 22 Oct 2018 *

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