Query generation for semantic datasets

Authors:
Jeff Z. Pan;Yuan Ren;Honghan Wu;Man Zhu
Affiliations:
University of Aberdeen, Aberdeen, United Kingdom;University of Aberdeen, Aberdeen, United Kingdom;Nanjing University of Information and Technology, Nanjing , China;Southeast University, Nanjing, China
Venue:
Proceedings of the seventh international conference on Knowledge capture
Year:
2013

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Abstract

Due to the increasing volume of and interconnections between semantic datasets, it becomes a challenging task for novice users to know what are included in a dataset, how they can make use of them, and particularly, what queries should be asked. In this paper we analyse several types of candidate insightful queries and propose a framework to generate such queries and identify their relations. To verify our approach, we implemented our framework and evaluated its performance with benchmark and real world datasets.