数据与计算发展前沿 ›› 2023, Vol. 5 ›› Issue (1): 55-64.

CSTR: 32002.14.jfdc.CN10-1649/TP.2023.01.005

doi: 10.11871/jfdc.issn.2096-742X.2023.01.005

• 专刊:科学数据资源、技术与政策联合专刊 • 上一篇    下一篇

ESDRec：一种面向地球大数据平台的数据推荐模型

许淞源1,2(),刘峰1,*()   

  1. 1.中国科学院计算机网络信息中心，北京 100083
    2.中国科学院大学，北京 100049
  • 收稿日期:2022-04-04 出版日期:2023-02-20 发布日期:2023-02-20
  • 通讯作者: 刘峰
  • 作者简介:许淞源，中国科学院计算机网络信息中心，硕士研究生，主要研究领域为数据共享服务技术、推荐系统等。
    在本文中负责数据处理、模型构建、实验和论文撰写。
    XU Songyuan is a graduate student in the Computer Network Information Center of Chinese Academy of Sciences. His res-earch interests cover data sharing service technology, recom-mendation system, etc.
    In this paper, he is responsible for data processing, model con-struction, experiment design and, paper writing.
    E-mail: xusongyuan@cnic.cn|刘峰，中国科学院计算机网络信息中心，博士，项目研究员，长期从事科学数据管理与共享服务技术研究及平台建设。主要研究方向为数据融合管理与语义关联技术。
    本文中负责文章框架组织和重点内容修订。
    LIU Feng, Ph.D., is a project researcher at the Computer Net-work Information Center of Chinese Academy of Sciences. He has long been engaged in scientific data management, sharing service technology research, and platform construction. His main research directions are data fusion management and sem-antic association technology.
    In this paper, he is mainly responsible for the organization of the article framework and the revision of key content.
    E-mail: liufeng@cnic.cn
  • 基金资助:
    中国科学院A类战略性先导科技专项(XDA19020104)

ESDRec: A Data Recommendation Model for Earth Big Data Platform

XU Songyuan1,2(),LIU Feng1,*()   

  1. 1. Computer Network Information Center, Chinese Academy of Sciences, Beijing 100083, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2022-04-04 Online:2023-02-20 Published:2023-02-20
  • Contact: LIU Feng

RichHTML

22

PDF

109

摘要：

【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。

关键词: 推荐系统, 科学数据共享, 地球大数据, 深度学习, 循环神经网络

Abstract:

[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.

Key words: recommendation system, scientific data sharing, earth big data, deep learning, recurrent neural network