Building Hierarchies of Concepts via Crowdsourcing
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 844-852.
Abstract
Hierarchies of concepts are useful in many applications from navigation to organization of objects. Usually, a hierarchy is created in a centralized manner by employing a group of domain experts, a time-consuming and expensive process. The experts often design one single hierarchy to best explain the semantic relationships among the concepts, and ignore the natural uncertainty that may exist in the process. In this paper, we propose a crowdsourcing system to build a hierarchy and furthermore capture the underlying uncertainty. Our system maintains a distribution over possible hierarchies and actively selects questions to ask using an information gain criterion. We evaluate our methodology on simulated data and on a set of real world application domains. Experimental results show that our system is robust to noise, efficient in picking questions, cost-effective, and builds high quality hierarchies.
@inproceedings{ijcai2015p124,
title = {Building Hierarchies of Concepts via Crowdsourcing},
author = {Sun, Yuyin and Singla, Adish and Fox, Dieter and Krause, Andreas},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {844--852},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/124},
}
TY - CPAPER TI - Building Hierarchies of Concepts via Crowdsourcing AU - Sun, Yuyin AU - Singla, Adish AU - Fox, Dieter AU - Krause, Andreas T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 844 EP - 852 UR - https://ijcai.org/proceedings/2015/124 ER -Copied
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