Crowd sourcing through social gaming for community driven ontology engineering, results and observations

• Main Authors: Chua, Alloy Martin, Chua, Roland Christian, Dychiching, Arthur Vincent, Ang, Tinmon, Espiritu, Jose Lloyd, Lim, Nathalie Rose T., Cheng, Danny C.
• Format: text
• Published: Animo Repository 2010
• Subjects: Crowdsourcing; Self-organizing systems; Knowledge representation (Information theory); Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2839
• Institution: De La Salle University

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.