A domain-independent, ontology-agnostic approach to leveraging unstructured data sources

Abstract

The vast accumulation of unstructured data within various types of documents in recent years has escalated the need for more efficient and effective management of available data. An effective tool for unstructured data management can vastly benefit business enterprises as well as support the understanding of volumes of scientific data in academic and scholarly works. This paper presents a simple tool that would make such data more actionable by allowing for an automated mechanism to support sifting through vast amounts of data and understand simplistic correlations between the data sources. The system is designed to extract meaning from data sources in a user-directed fully automated approach. Flexibility and robustness was incorporated by allowing for the accommodation of multiple data source types and leveraging the WordNet ontology for subsequent data analysis.