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

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.