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Message Passing for Complex Question Answering over Knowledge Graphs
2019
Proceedings of the 28th ACM International Conference on Information and Knowledge Management - CIKM '19
Polleres, A.; de Rijke, M.; Cochez, M. ABSTRACT Question answering over knowledge graphs (KGQA) has evolved from simple single-fact questions to complex questions that require graph traversal and aggregation. We propose a novel approach for complex KGQA that uses unsupervised message passing, which propagates confidence scores obtained by parsing an input question and matching terms in the knowledge graph to a set of possible answers. First, we identify entity, relationship, and class names
doi:10.1145/3357384.3358026
dblp:conf/cikm/VakulenkoGPRC19
fatcat:5geuk55lgvfvjgpo4nutrpsfv4