Ontology Enrichment by Extracting Hidden Assertional Knowledge from Text
Abstract
In this position paper we present a new approach for discovering some special classes of assertional knowledge in the text by using large RDF repositories, resulting in the extraction of new non-taxonomic ontological relations. Also we use inductive reasoning beside our approach to make it outperform. Then, we prepare a case study by applying our approach on sample data and illustrate the soundness of our proposed approach. Moreover in our point of view current LOD cloud is not a suitable base for our proposal in all informational domains. Therefore we figure out some directions based on prior works to enrich datasets of Linked Data by using web mining. The result of such enrichment can be reused for further relation extraction and ontology enrichment from unstructured free text documents.
Cite
@article{arxiv.1308.0701,
title = {Ontology Enrichment by Extracting Hidden Assertional Knowledge from Text},
author = {Meisam Booshehri and Abbas Malekpour and Peter Luksch and Kamran Zamanifar and Shahdad Shariatmadari},
journal= {arXiv preprint arXiv:1308.0701},
year = {2013}
}
Comments
9 pages, International Journal of Computer Science and Information Security