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，大型知识库被建立来储存海量知识。然而，这些知识库高度不完整。为解决这一问题，我们提出了一种基于 Web 问答系统和多模态融合的方法，以填补知识库中缺失的信息。为了利用来自 Web 的非结构化信息完成知识库，我们设计了一个基于多模态特征和问题模板的 Web 问答系统，用于提取缺失的事实，在极少数的问题下即可实现良好的性能。为了帮助提高提取质量，问答系统利用来自知识库的结构化信息，例如实体类型和实体之间的关联。