Query generation for semantic datasets

Jeff Z. Pan, Yuan Ren, Honghan Wu, Man Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

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 languageEnglish
Title of host publicationProceedings of the 7th International Conference on Knowledge Capture
Subtitle of host publication"Knowledge Capture in the Age of Massive Web Data", K-CAP 2013
EditorsRichard Benjamins, Mathieu d'Aquin, Andrew Gordon
Place of PublicationNew York
PublisherACM
Pages113-116
Number of pages4
ISBN (Print)9781450321020
DOIs
Publication statusPublished - 2013
Event7th International Conference on Knowledge Capture: "Knowledge Capture in the Age of Massive Web Data", K-CAP 2013 - Banff, AB, Canada
Duration: 23 Jun 201326 Jun 2013

Conference

Conference7th International Conference on Knowledge Capture: "Knowledge Capture in the Age of Massive Web Data", K-CAP 2013
CountryCanada
CityBanff, AB
Period23/06/1326/06/13

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    Pan, J. Z., Ren, Y., Wu, H., & Zhu, M. (2013). Query generation for semantic datasets. In R. Benjamins, M. d'Aquin, & A. Gordon (Eds.), Proceedings of the 7th International Conference on Knowledge Capture: "Knowledge Capture in the Age of Massive Web Data", K-CAP 2013 (pp. 113-116). ACM. https://doi.org/10.1145/2479832.2479859