With the rise of knowledge graph (KG), question answering over knowledge base (KBQA) has attracted increasing attention in recent years. Despite much research has been conducted on this topic, it is still challenging to apply KBQA technology in industry because business knowledge and real-world questions can be rather complicated. In this paper, we present AliMe-KBQA, a bold attempt to apply KBQA in the E-commerce customer service field. To handle real knowledge and questions, we extend the classic "subject-predicate-object (SPO)" structure with property hierarchy, key-value structure and compound value type (CVT), and enhance traditional KBQA with constraints recognition and reasoning ability. We launch AliMe-KBQA in the Marketing Promotion scenario for merchants during the "Double 11" period in 2018 and other such promotional events afterwards. Online results suggest that AliMe-KBQA is not only able to gain better resolution and improve customer satisfaction, but also becomes the preferred knowledge management method by business knowledge staffs since it offers a more convenient and efficient management experience.
翻译:随着知识图(KG)的崛起,对知识基础(KBQA)的回答问题近年来引起了越来越多的关注。尽管对这一专题进行了许多研究,但由于商业知识和现实世界问题可能相当复杂,因此在工业中应用KBQA技术仍是一项挑战。在本文中,我们介绍了AliMe-KBQA,这是在电子商务客户服务领域应用KBQA的大胆尝试。为了处理真正的知识和问题,我们推广了典型的“主题预测对象(SPO)”结构,结构包括财产等级、关键价值结构和复合价值类型(CVT),并以认识限制和推理能力加强传统的KBQA。我们在2018年的“第11回合”期间和此后的其他类似促销活动中为商人推出了AliMe-KBQA市场促销方案。在线结果表明,AliMe-KBQA不仅能够获得更好的解答,提高客户的满意度,而且成为商业知识工作人员更方便和高效的管理经验的首选知识管理方法。