ArticleProceedings. IEEE International Conference on Semantic Computing2021
Extracting Semantics from Census-based Reference Data.
Article in Proceedings. IEEE International Conference on Semantic Computing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Collaborating with and enabling diverse communities to address health inequities: The experiences of a community engagement and outreach team.Journal of clinical and translational science · 2025Article
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2 authors.
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Abstract
We present preliminary findings in extracting semantics from reference data generated by the United States Census Bureau. US Census reference data is based upon surveys designed to collect demographics and other socioeconomic factors by geographical regions. These data sets contain thousands of variables; this complexity makes the reference data difficult to learn, query, and integrate into analyses. Researchers often avoid working directly with US Census reference data and instead work with census-derived extracts capturing a much smaller subset of records. We propose to use natural language processing to extract the semantics of census-based reference data and to map census variables to known ontologies. This semantic processing reduces the large volume of variables into more manageable sets of conceptual variables that can be organized by meaning and semantic type.
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Registered trials
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