ESDRec:一种面向地球大数据平台的数据?推荐模型

ESDRec:A Data Recommendation Model for Earth Big Data Platform

【应用背景】地球大数据共享服务系统是中国科学院“地球大数据科学工程”战略性先导科技专项的数据门户窗口,为全球用户提供了一个数据、计算与服务为一体的数据共享系统,推动形成地球科学数据共享新模式。【目的】随着数据资源的持续汇交发布,用户仅通过筛选、检索等方式来获取数据资源的难度也将随之增加,如何利用推荐技术帮助用户更加高效地获取科学数据是一个值得研究的问题。【方法】因此,本文设计了一个地球科学数据推荐模型ESDRec,该模型使用双向长短时记忆网络与注意力机制对用户兴趣偏好进行建模,并对地球科学数据的元数据特征属性关联度进行计算。本文将地球科学数据的领域特征融入到推荐模型中,实现了更加准确的推荐。【结论】通过在平台真实数据集上进行对比实验,本文验证了ESDRec模型的有效性。

[Application Background]The earth big data sharing service system is the data portal for the Chinese Academy of Sciences“Earth Big Data Science Project”,a strategic pilot science and technology project.It provides global users with a data-sharing system integrating data,computing,and services,and promotes the new model for earth science data sharing.[Objective]With continuous release of data resources,it will become more difficult for users to obtain data resources through only filtering,and searching,etc.How to use recommendation technology to help users obtain scientific data more efficiently is a problem for research.[Methods]Therefore,this paper designs an earth science data recommendation model,ESDRec,which uses a bidirectional long-short-term memory network and attention mechanism to model users’interest preferences,and calculates the correlation degree of metadata feature attributes of scientific data.This work incorporates domain features of earth science data into ESDRec so that ESDRec can generate more accurate recommendation results.[Conclusions]By conducting comparative experiments on the real datasets of the platform,this paper verifies the effectiveness of the ESDRec model.