Crowd sourcing through social gaming for community driven ontology engineering, results and observations
In developing ontology, expert driven approaches lack the scalability to accommodate the vast amount of data on the web. As such, the community is being tapped to build ontologies to cope with highly dynamic data sources. Common problems (like difficulty of the task, quality of output, and incentive...
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| Main Authors: | , , , , , , |
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| Format: | text |
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Animo Repository
2010
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2839 |
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| Institution: | De La Salle University |
| Summary: | In developing ontology, expert driven approaches lack the scalability to accommodate the vast amount of data on the web. As such, the community is being tapped to build ontologies to cope with highly dynamic data sources. Common problems (like difficulty of the task, quality of output, and incentives needed to motivate the community), as discussed by other authors, are considered. In this paper, we discuss observations on our approach to improve the quality and sustain community ontology refinement though the use of social gaming and interaction. Current observations show that profile and knowledge of the concept in question, understanding and expressivity of the relationships play a key role in the quality of the result. |
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