Semantic enrichment of multi-intelligence data within a net-centric environment

Hull, Richard D.; Lashine, Larry; Jenkins, Don

doi:10.1117/12.818665

Cited by 2 publications

(1 citation statement)

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“…The other framework with a complete exclusion of the impact assessment component is the semantic enrichment and fusion of multi-intelligence data framework (Hull et al 2009). This framework pertains to semantic enrichment of data extracts from criminal reports with the military ontology metadata tags for the identification of vehicle theft events (Hull et al 2009). This process is performed in three steps.…”

Section: Related Workmentioning

confidence: 99%

Ontology-Driven Semantic Enrichment Framework for Open Data Value Creation

Sebubi,

Zlotnikova,

Hlomani

2023

Data Science Journal

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The reviewed semantic enrichment frameworks lack mechanisms to assess the degree of semantic value added to flat-text resources in terms of knowledge and semantic capabilities. This complicates the tasks of driving the semantic value creation process toward the specific enrichment output and evaluating the output. In addressing this gap, we propose the semantic value creation solution, which converts flat-text resources to knowledge resources. Namely, we propose the ontology-driven semantic enrichment (ODSE) framework, with a mechanism for semantic valuation. The framework's development involved adopting the design science research methodology for information systems. The developed framework leverages linked data principles for knowledge creation. This framework was demonstrated to determine the semantic capabilities enabled by the syntax additions, as well as the knowledge enabled by the semantic additions to flat-text resources, along with its potential impact on knowledge creation, mining, and resource-usability effectiveness. The ODSE framework is reusable in semantic value creation implementations that transform a flat text to semantic formats.

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Section: Related Workmentioning

confidence: 99%