Towards Building Ontologies with the Wisdom of the Crowd
From International Center for Computational Logic
Towards Building Ontologies with the Wisdom of the Crowd
Paula ChocronPaula Chocron, Dagmar GromannDagmar Gromann
Paula Chocron, Dagmar Gromann
Towards Building Ontologies with the Wisdom of the Crowd
In Michael Rovatsos, Ronald Chenu-Abente, eds., International Workshop on Diversity-Aware Artificial Intelligence (DIVERSITY 2016) at ECAI 2016, 1-11, 2016
Towards Building Ontologies with the Wisdom of the Crowd
In Michael Rovatsos, Ronald Chenu-Abente, eds., International Workshop on Diversity-Aware Artificial Intelligence (DIVERSITY 2016) at ECAI 2016, 1-11, 2016
- KurzfassungAbstract
Crowdsourcing provides a valuable source of input that reflects the human diversity of domain knowledge. It has increasingly been used in ontology engineering and evaluation, however, few approaches consider different types of crowdsourcing for data acquisition. In this paper, we compare two crowdsourcing techniques - a mechanized labor-based task and a game-based approach - to acquire shared knowledge from which we semi-automatically build an ontology. This paper focuses on the first two steps of ontology engineering, the forming of concepts and their hierarchical relations. To this end, we adapt a distributional semantic and class-based word sense disambiguation approach and a knowledge-intensive tree traversal algorithm. Each step along the process and the final resources are evaluated manually and by a gold standard created from Wikipediadata. Our results show that the ontology resulting from data obtained with the mechanized labor-based approach provides a higher level of
granularity than the game-based one. However, the latter is faster and seems more enticing to participants. - Weitere Informationen unter:Further Information: Link
- Forschungsgruppe:Research Group: Computational LogicComputational Logic
@article{chocron2016towards,
title={Towards Building Ontologies with the Wisdom of the Crowd},
author={Chocron, Paula and Gromann, Dagmar and Real, Francisco Jos{\'e} Quesada},
journal={DIVERSITY@ ECAI 2016},
pages={1--11}
}