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.
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