Approximate and Interactive Processing of Aggregate Queries on Knowledge Graphs: A Demonstration
Yuxiang Wang, Arijit Khan, Xiaoliang Xu, Shuzhan Ye, Shihuang Pan, Yuhan Zhou · Proceedings of the 31st ACM International Conference on Information & Knowledge Management · 2022
This paper demonstrates AGQ [26] - our system for approximate and interactive processing of aggregate queries on knowledge graphs (KGs), e.g., "what is the average price of cars produced in Germany?" One can support aggregate queries based on factoid queries, e.g., "find all cars produced in Germany", by applying an aggregate operation on factoid queries' answers. However, this straightforward method is problematic since both the accuracy and efficiency of factoid query processing would impact the performance of aggregate queries. Moreover, returning a one-time, exact result might add computation overhead and hinder users' engagement and interactivity.