Result Diversity for RDF Search

Hiba Arnaout, Shady Elbassuoni

2016

Abstract

RDF repositories are typically searched using triple-pattern queries. Often, triple-pattern queries will return too many results, making it difficult for users to find the most relevant ones. To remedy this, some recent works have proposed relevance-based ranking-models for triple-pattern queries. However it is often the case that the top-ranked results are homogeneous. In this paper, we propose a framework to diversify the results of triple-pattern queries over RDF datasets. We first define different notions for result diversity in the setting of RDF. We then develop an approach for result diversity based on the Maximal Marginal Relevance. Finally, we develop a diversity-aware evaluation metric based on the Discounted Cumulative Gain and use it on a benchmark of 100 queries over DBPedia.

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Paper Citation


in Harvard Style

Arnaout H. and Elbassuoni S. (2016). Result Diversity for RDF Search . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016) ISBN 978-989-758-203-5, pages 249-256. DOI: 10.5220/0006046402490256


in Bibtex Style

@conference{kdir16,
author={Hiba Arnaout and Shady Elbassuoni},
title={Result Diversity for RDF Search},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)},
year={2016},
pages={249-256},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006046402490256},
isbn={978-989-758-203-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)
TI - Result Diversity for RDF Search
SN - 978-989-758-203-5
AU - Arnaout H.
AU - Elbassuoni S.
PY - 2016
SP - 249
EP - 256
DO - 10.5220/0006046402490256