文献类型：会议论文

英文题名：Design and implementation of intelligent library system based on big data

作者：Peng, Zhibin[1]; Chen, Yuefeng[1]; Luo, Xiaoying[1]; Fan, Rui[1]; Meng, JiaHui[1]

机构：[1] Faculty of Mathematics and Computer Science, Guangdong Ocean University, Zhanjiang, 524088, China

会议论文集：3rd International Symposium on Big Data and Applied Statistics

会议日期：July 10, 2020 - July 12, 2020

会议地点：Kunming, China

语种：英文

外文关键词：Machine learning - Search engines - Clustering algorithms - Learning algorithms

外文摘要：In most traditional library management systems, readers have to find their interest books through the name or search approximate content from library, which results in wasting time. With the help of big data technology, we construct the intelligent library system using SSM framework and Hadoop framework. A recommendation approach combined co-filtering with content-based recommendations, is introduced to make better recommend efficiency. The system has the intelligent ability of self-learning. For historical lending books data, it uses the Spark MLlib machine learning algorithm library to build clustering or classification models. On the other hand, the system uses Kafka and SparkStreaming to process real-time data. System simulation shows that it has high recommendation accuracy and good timeliness. ? Published under licence by IOP Publishing Ltd.