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

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

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

Content Provider	ACM Digital Library
Author	Le, Christine Bayrak, Coskun Ramaswamy, Srini
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.
Starting Page	122
Ending Page	126
Page Count	5
File Format	PDF
ISBN	9781605581057
DOI	10.1145/1593105.1593137
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-03-28
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Data analysis Ontology Entity extraction Information extraction Unstructured data
Content Type	Text
Resource Type	Article

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