A clustering‐based semi‐automated technique to build cultural ontologies

Abstract

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.

Ontology Supported Information Systems: A Review

“…A clustering-based method for creating cultural ontologies for community oriented information systems has been described by Srinivasan et al (2009). This semi-automated method merges distributed annotation techniques, or subjective assessments of similarities between cultural categories, with established clustering methods to produce "cognate" ontologies.…”

Construction and Applications of Ontology: Recent Trends

“…Clustering-based method is another method useful in ontology construction. It is suitable for the construction of cultural ontologies for community-oriented information systems 10 . This semi-automated method merges distributed annotation techniques or subjective assessments of similarities between cultural categories with established clustering methods to produce "cognate" ontologies.…”

Image indexing in article component databases

“…Different approaches are used in classification systems to determine classification category labels, such that the labels may precede or follow creation of categories. Preceding the creation of the categories is the use of labels from external controlled vocabularies, controlled vocabularies made internally to reflect a particular knowledge domain, or vocabularies derived from user terms as from user annotations (for example, Srinivasan, Pepe, & Rodriguez, 2009). Alternatively, labels might be made by hand to reflect the topic of machine‐made clusters.…”