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Over the past few years, large knowledge bases have been constructed to storemassive amounts of knowledge. However, these knowledge bases are highlyincomplete, for example, over 70% of people in Freebase have no known place ofbirth. To solve this problem, we propose a query-driven knowledge basecompletion system with multimodal fusion of unstructured and structuredinformation. To effectively fuse unstructured information from the Web andstructured information in knowledge bases to achieve good performance, oursystem builds multimodal knowledge graphs based on question answering and ruleinference. We propose a multimodal path fusion algorithm to rank candidateanswers based on different paths in the multimodal knowledge graphs, achievingmuch better performance than question answering, rule inference and a baselinefusion algorithm. To improve system efficiency, query-driven techniques areutilized to reduce the runtime of our system, providing fast responses to userqueries. Extensive experiments have been conducted to demonstrate theeffectiveness and efficiency of our system.

Query-Driven Knowledge Base Completion using Multimodal Path Fusion over Multimodal Knowledge Graph