Identifying equivalent relation paths in knowledge graphs
Mohamed, Sameh K. Muñoz, Emir Nováček, Vít Vandenbussche, Pierre-Yves
Mohamed, Sameh K.
Muñoz, Emir
Nováček, Vít
Vandenbussche, Pierre-Yves
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Repository DOI
Publication Date
2017-06-19
Type
Conference Paper
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Citation
Mohamed, Sameh K., Muñoz, Emir, Nováček, Vít, & Vandenbussche, Pierre-Yves. (2017). Identifying Equivalent Relation Paths in Knowledge Graphs. In Jorge Gracia, Francis Bond, John P. McCrae, Paul Buitelaar, Christian Chiarcos & Sebastian Hellmann (Eds.), Language, Data, and Knowledge: First International Conference, LDK 2017, Galway, Ireland, June 19-20, 2017, Proceedings (pp. 299-314). Cham: Springer International Publishing.
Abstract
Relation paths are sequences of relations with inverse that allow for complete exploration of knowledge graphs in a two-way unconstrained manner. They are powerful enough to encode complex relationships between entities and are crucial in several contexts, such as knowledge base verification, rule mining, and link prediction. However, fundamental forms of reasoning such as containment and equivalence of relation paths have hitherto been ignored. Intuitively, two relation paths are equivalent if they share the same extension, i.e., set of source and target entity pairs. In this paper, we study the problem of containment as a means to find equivalent relation paths and show that it is very expensive in practice to enumerate paths between entities. We characterize the complexity of containment and equivalence of relation paths and propose a domain-independent and unsupervised method to obtain approximate equivalences ranked by a tri-criteria ranking function. We evaluate our algorithm using test cases over real-world data and show that we are able to find semantically meaningful equivalences efficiently.
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Publisher
Springer Verlag
Publisher DOI
10.1007/978-3-319-59888-8_26
Rights
Attribution-NonCommercial-NoDerivs 3.0 Ireland