Over the past few years, large knowledge bases have been constructed to store massive amounts of knowledge. However, these knowledge bases are highly incomplete. To solve this problem, we propose a web-based question answering system system with multimodal fusion of unstructured and structured information, to fill in missing information for knowledge bases. To utilize unstructured information from the Web for knowledge base completion, we design a web-based question answering system using multimodal features and question templates to extract missing facts, which can achieve good performance with very few questions. To help improve extraction quality, the question answering system employs structured information from knowledge bases, such as entity types and entity-to-entity relatedness.

翻译：近年来，大规模知识库被构建用于存储海量知识。然而，这些知识库存在严重的不完整性。为解决此问题，我们提出了一种融合非结构化与结构化信息的多模态网络问答系统，用于补全知识库中的缺失信息。为利用网络上的非结构化信息进行知识库补全，我们设计了一个基于多模态特征与问题模板的网络问答系统来提取缺失事实，该系统在极少量问题的条件下即可取得良好性能。为提升提取质量，该问答系统采用了知识库中的结构化信息，例如实体类型和实体间关联度。