Abstract
Much content on the World Wide Web is becoming tagged with simple words or phrases in natural language as web citizens create tags that organize information primarily to facilitate their personal retrieval and use. These tags represent, often incomplete, pieces of knowledge about concepts in a domain. Aggregated across a large number of contributors, these tags provide the potential to identify, in a bottom-up manner, key constructs in a domain. This research develops a set of heuristics that aggregate and analyze tags contributed by individual users on the web to extract and generate domain-level constructs. The heuristics infer the existence of constructs, and distinguish entities, attributes, and relationships.
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Sugumaran, V., Purao, S., Storey, V.C., Conesa, J. (2010). On-Demand Extraction of Domain Concepts and Relationships from Social Tagging Websites. In: Hopfe, C.J., Rezgui, Y., Métais, E., Preece, A., Li, H. (eds) Natural Language Processing and Information Systems. NLDB 2010. Lecture Notes in Computer Science, vol 6177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13881-2_23
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DOI: https://doi.org/10.1007/978-3-642-13881-2_23
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