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A Clustering-Based Semi Automated Technique to Build Cultural Ontologies
JASIST (2009)
  • Ramesh Srinivasan, University of California, Los Angeles
  • Alberto Pepe, UCLA
  • Marko A Rodriguez, Los Alamos National Laboratory
This article presents and validates a clustering-based method for creating cultural ontologies for community-oriented information systems. The introduced semiautomated approach merges distributed annotation techniques, or subjective assessments of similarities between cultural categories, with established clustering methods to produce cognate ontologies. This approach is validated against a locally authentic ethnographic method, involving direct work with communities for the design of fluid ontologies. The evaluation is conducted with of a set of Native American communities located in San Diego County (CA, US). The principal aim of this research is to discover whether distributing the annotation process among isolated respondents would enable ontology hierarchies to be created that are similar to those that are crafted according to collaborative ethnographic processes, found to be effective in generating continuous usage across several studies. Our findings suggest that the proposed semiautomated solution best optimizes among issues of interoperability and scalability, deemphasized in the fluid ontology approach, and sustainable usage.
Publication Date
January 1, 2009
Citation Information
A Clustering-Based Semi-Automated Technique to Build Cultural Ontologies. Ramesh Srinivasan, Alberto Pepe, Marko Rodriguez. Journal of the American Society for Information Science and Technology (JASIST), Volume 60, Number 2, Pages 1-13. doi:10.1002/asi.20998, ISSN:1532-2882, Wiley. 2009.