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.
Original language | English |
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Title of host publication | Proceedings of the 7th International Conference on Knowledge Capture |
Subtitle of host publication | "Knowledge Capture in the Age of Massive Web Data", K-CAP 2013 |
Editors | Richard Benjamins, Mathieu d'Aquin, Andrew Gordon |
Place of Publication | New York |
Publisher | ACM |
Pages | 113-116 |
Number of pages | 4 |
ISBN (Print) | 9781450321020 |
DOIs | |
Publication status | Published - 2013 |
Event | 7th International Conference on Knowledge Capture: "Knowledge Capture in the Age of Massive Web Data", K-CAP 2013 - Banff, AB, Canada Duration: 23 Jun 2013 → 26 Jun 2013 |
Conference
Conference | 7th International Conference on Knowledge Capture: "Knowledge Capture in the Age of Massive Web Data", K-CAP 2013 |
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Country/Territory | Canada |
City | Banff, AB |
Period | 23/06/13 → 26/06/13 |