Ontologies have been known for their powerful semantic representation of knowledge. However, ontologies cannot automatically evolve to reflect updates that occur in respective domains. To address this limitation, researchers have called for automatic ontology generation from unstructured text corpus. Unfortunately, systems that aim to generate ontologies from unstructured text corpus are domain-specific and require manual intervention. In addition, they suffer from uncertainty in creating concept linkages and difficulty in finding axioms for the same concept. Knowledge Graphs (KGs) has emerged as a powerful model for the dynamic representation of knowledge. However, KGs have many quality limitations and need extensive refinement. This research aims to develop a novel domain-independent automatic ontology generation framework that converts unstructured text corpus into domain consistent ontological form. The framework generates KGs from unstructured text corpus as well as refine and correct them to be consistent with domain ontologies. The power of the proposed automatically generated ontology is that it integrates the dynamic features of KGs and the quality features of ontologies.
Government agencies rely on websites to disseminate large volumes of information to the citizens. As public information changes over time due to changes in laws and regulations, maintaining currency and consistency of the web content becomes acutely important. Government agencies have to regularly evaluate the web content (WC) to ensure high quality of information available to the citizens, businesses, and public administrators. Currently there exists no standardized approach for monitoring and maintaining WC. In this chapter, the authors propose a WC ontology for the systematic and formal representation of the concepts and functions associated with the evaluation of web content on government websites. An ontology-based evaluation tool is proposed that can be used to improve the quality of web content and efficiency of the evaluation process. The ontological approach holds promising features and benefits including information sharing, reducing time and paperwork during evaluation, assuring more accurate results, and communicating evaluation results to knowledge engineers, public administrators, evaluators, and decision makers engaged in e-government initiatives.
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