Skyline Queries over Knowledge Graphs

Ilkcan Keles*, Katja Hose

*Corresponding author

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Citations (Scopus)


With the continuously growing amount of data offered in the form of knowledge graphs, users are often overwhelmed by the amount of potentially relevant information and entities. Hence, helping users find relevant data is a problem that becomes more and more important. Skyline queries are typically used in multi-criteria decision making applications to find a set of objects that are of interest to a user. This type of queries has been extensively studied over relational data in the database community. But only little attention has yet been paid to investigating if and how the skyline principle can help identifying sets of interesting entities in knowledge graphs. In this paper, we therefore show how the skyline principle can be applied to RDF knowledge graphs and help the user find interesting entities. In particular, we present algorithms using commonly used standard interfaces for accessing RDF data and a lightweight extension of existing interfaces (SkyTPF) to process skyline queries. Our experiments show that the proposed algorithms enable efficient and scalable skyline query processing over knowledge graphs.
Original languageEnglish
Title of host publicationThe Semantic Web – ISWC 2019 - 18th International Semantic Web Conference, Proceedings
EditorsChiara Ghidini, Olaf Hartig, Maria Maleshkova, Vojtech Svátek, Isabel Cruz, Aidan Hogan, Jie Song, Maxime Lefrançois, Fabien Gandon
Number of pages18
Publication date17 Oct 2019
ISBN (Print)978-3-030-30792-9
ISBN (Electronic)978-3-030-30793-6
Publication statusPublished - 17 Oct 2019
EventThe 18th International Semantic Web Conference, ISWC 2019 - Auckland, New Zealand
Duration: 26 Oct 201930 Oct 2019
Conference number: 18th


ConferenceThe 18th International Semantic Web Conference, ISWC 2019
CountryNew Zealand
Internet address
SeriesLecture Notes in Computer Science

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  • Projects

    Unleashing the Potential of Open Data

    Hose, K.


    Project: Research

    QWeb: Querying the Web of Data Easily and Efficiently

    Hose, K., Montoya, G., Prado, L. A. G. D., Rouces, J., Mathiassen, K. A. M., Zervakis, E. & Setty, V.


    Project: Research

    Cite this

    Keles, I., & Hose, K. (2019). Skyline Queries over Knowledge Graphs. In C. Ghidini, O. Hartig, M. Maleshkova, V. Svátek, I. Cruz, A. Hogan, J. Song, M. Lefrançois, & F. Gandon (Eds.), The Semantic Web – ISWC 2019 - 18th International Semantic Web Conference, Proceedings (pp. 293-310). Springer. Lecture Notes in Computer Science, Vol.. 11778