Relationship-based top-k concept retrieval for ontology search

Anila Sahar Butt*, Armin Haller, Lexing Xie

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    9 Citations (Scopus)


    With the recent growth of Linked Data on the Web there is an increased need for knowledge engineers to find ontologies to describe their data. Only limited work exists that addresses the problem of searching and ranking ontologies based on a given query term. In this paper we introduce DWRank, a two-staged bi-directional graph walk ranking algorithm for concepts in ontologies. We apply this algorithm on the task of searching and ranking concepts in ontologies and compare it with state-of-the-art ontology ranking models and traditional information retrieval algorithms such as PageRank and tf-idf. Our evaluation shows that DWRank significantly outperforms the best ranking models on a benchmark ontology collection for the majority of the sample queries defined in the benchmark.

    Original languageEnglish
    Title of host publicationKnowledge Engineering and Knowledge Management - 19th International Conference, EKAW 2014, Proceedings
    EditorsKrzysztof Janowicz, Stefan Schlobach, Patrick Lambrix, Eero Hyvönen
    PublisherSpringer Verlag
    Number of pages18
    ISBN (Electronic)9783319137032
    Publication statusPublished - 2014
    Event19th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2014 - Linköping, Sweden
    Duration: 24 Nov 201428 Nov 2014

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference19th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2014


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