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Authors: Hrag Yoghourdjian ; Shady Elbassuoni ; Mohamad Jaber and Hiba Arnaout

Affiliation: American University of Beirut, Lebanon

Keyword(s): RDF, Knowledge Graphs, Top-k Search, Keyword Search, Ranking, Wikipedia.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Foundations of Knowledge Discovery in Databases ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

Abstract: Effective keyword search over RDF knowledge graphs is still an ongoing endeavor. Most existing techniques have their own limitations in terms of the unit of retrieval, the type of queries supported or the basis on which the results are ranked. In this paper, we develop a novel retrieval model for general keyword queries over Wikipedia-based RDF knowledge graphs. Our model retrieves the top-k scored subgraphs for a given keyword query. To do this, we develop a scoring function for RDF subgraphs and then we deploy a graph searching algorithm that only retrieves the top-k scored subgraphs for the given query based on our scoring function. We evaluate our retrieval model and compare it to state-of-the-art approaches using YAGO, a large Wikipedia-based RDF knowledge graph.

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Paper citation in several formats:
Yoghourdjian, H.; Elbassuoni, S.; Jaber, M. and Arnaout, H. (2017). Top-k Keyword Search over Wikipedia-based RDF Knowledge Graphs. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR; ISBN 978-989-758-271-4; ISSN 2184-3228, SciTePress, pages 17-26. DOI: 10.5220/0006411400170026

@conference{kdir17,
author={Hrag Yoghourdjian. and Shady Elbassuoni. and Mohamad Jaber. and Hiba Arnaout.},
title={Top-k Keyword Search over Wikipedia-based RDF Knowledge Graphs},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR},
year={2017},
pages={17-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006411400170026},
isbn={978-989-758-271-4},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR
TI - Top-k Keyword Search over Wikipedia-based RDF Knowledge Graphs
SN - 978-989-758-271-4
IS - 2184-3228
AU - Yoghourdjian, H.
AU - Elbassuoni, S.
AU - Jaber, M.
AU - Arnaout, H.
PY - 2017
SP - 17
EP - 26
DO - 10.5220/0006411400170026
PB - SciTePress