%0 Journal Article
%A LU Yan-xin
%A LI Yong-feng
%A XIN Ming-quan
%A LI Xiao-ning
%A LIU Shu-bo
%T Real-time Recommendation Algorithm for Water Information Distribution Based on Long-Short-Term Memory
%D 2020
%R 10.11988/ckyyb.20181201
%J Journal of Yangtze River Scientific Research Institute
%P 137-143
%V 37
%N 3
%X The demand for real-time recommendation of water information is growing stronger with the deepening of water conservancy informatization in China. Since the data of water is highly time-sensitive, recommendation system is required to provide real-time recommendation services. User-based collaborative filtering and item-based collaborative filtering (ItemCF) are two commonly used algorithms in the recommendation field. Both, however, are offline algorithms in nature and cannot meet the requirement of real-time distribution of water information. In this paper, a real-time recommendation algorithm for water regime information distribution based on Long-Short-Term Memory (LSTM) is proposed and optimized to ensure the accuracy of water information recommendation while ensuring the real-time recommendation.
%U http://ckyyb.crsri.cn/EN/10.11988/ckyyb.20181201