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Erschienen in:
2018 | OriginalPaper | Buchkapitel
An Incremental Reasoning Algorithm for Large Scale Knowledge Graph
verfasst von : Yifei Wang, Jie Luo
Erschienen in: Knowledge Science, Engineering and Management
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Abstract
Knowledge graphs usually contain much implicit semantic information, which needs to be further mined through semantic inference. Current algorithms can effectively accomplish such task, however they often require a full re-reasoning even when only a few new triples is added to expand the knowledge graph. In this paper, we propose an incremental reasoning algorithm which can effectively avoid re-reasoning over the entire knowledge graph while keeping the relative completeness of the final deduction results. Key to our approach is the filter algorithms which reduce the scale of data that need to be considered and a delay strategy which limit the number of time-consuming iterations while still preserve relative completeness. Extensive experiments and comprehensive evaluations are conducted and experimental results prove that our methods significantly outperform re-reasoning methods.