地图学与地理信息

用户模型驱动的遥感信息智能服务方法

  • 杨晓霞 ,
  • 徐婷 ,
  • 李少达 ,
  • 杨容浩 ,
  • 丁雨淋 ,
  • 曹振宇
展开
  • 1. 成都理工大学地球科学学院, 四川 成都 610059;
    2. 四川省应急测绘与防灾减灾工程技术研究中心, 四川 成都 610041;
    3. 成都理工大学地学空间信息技术国土资源部重点实验室, 四川 成都 610059;
    4. 高速铁路运营安全空间信息技术国家地方联合工程实验室, 四川 成都 611756;
    5. 西南交通大学地球科学与环境工程学院, 四川 成都 611756
杨晓霞(1977-),女,博士,讲师,研究方向为地理信息服务和虚拟地理环境。E-mail:yangxx2003@126.com

收稿日期: 2014-08-05

  修回日期: 2015-08-10

  网络出版日期: 2015-11-25

基金资助

国家自然科学基金(41201440;41471332;41101354);教育部博士点基金(20125122120014);2014年度国家测绘地理信息局基础测绘科技项目;四川省应急测绘与防灾减灾工程技术研究中心开放基金(K2015B002);国家级大学生创新训练项目(201410616037);四川省教育厅理科重点项目(15ZA0078)

A User Profile-driven Intelligent Service of Remote Sensing Information

  • YANG Xiaoxia ,
  • XU Ting ,
  • LI Shaoda ,
  • YANG Ronghao ,
  • DING Yulin ,
  • CAO Zhenyu
Expand
  • 1. College of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China;
    2. Sichuan Engineering Research Center for Emergency Mapping & Disaster Reduction, Chengdu 610041, China;
    3. Key Laboratory of Geoscience Spatial Information Technology, Ministry of Land and Resources of the P. R. China, Chengdu 610059, China;
    4. State-Province Joint Engineering Laboratory of Spatial Information Technology of High-Speed Rail Safety, Chengdu 611756, China;
    5. Faculty of Geosciences and Enviromental Engineering, Southwest Jiaotong University, Chengdu 611756, ChinaAbstract

Received date: 2014-08-05

  Revised date: 2015-08-10

  Online published: 2015-11-25

Supported by

The National Natural Science Foundation of China(Nos. 412014404147133241101354) Ph.D. Programs Foundation of Ministry of Education of China(No. 20125122120014) Basic Surveying and Mapping Science and Technology Program of National Administration of Surveying, Mapping and Geoinformation Open Research Fund by Sichuan Engineering Research Center for Emergency Mapping & Disaster Reduction(No. K2015B002) National Undergraduate Training Programs for Innovation(No. 201410616037) Foundation of Sichuan Educational Committee(No.15ZA0078)

摘要

传统的浏览下载的遥感信息服务模式存在被动性、同一性等缺点,如何主动、准确地满足用户的个性化需求已成为遥感信息服务的焦点问题。本文针对遥感信息在空间和波谱上的覆盖特性,引入区间数学的方法建立了用户模型,描述用户兴趣在遥感信息核心元数据上的分布特征。提出关联度和兴趣度概念用来评价遥感信息对用户兴趣的满足程度,设计了基于拓扑关系的关联函数定量计算关联度。通过将待分发遥感信息作为备选方案构建了决策矩阵,从而将遥感信息的智能服务问题转化为多属性决策问题,实现了面向用户兴趣的遥感信息主动推荐。

本文引用格式

杨晓霞 , 徐婷 , 李少达 , 杨容浩 , 丁雨淋 , 曹振宇 . 用户模型驱动的遥感信息智能服务方法[J]. 测绘学报, 2015 , 44(11) : 1285 -1294 . DOI: 10.11947/j.AGCS.2015.20140413

Abstract

To overcome limits of traditional passive remote sensing data distribution methods, personalization is an inevitable trend of spatial information service. User profile is the basic foundation for personalized, active and accurate spatial information dissemination service, which can be used in the definition of users' preferences or interests of remote sensing data. In view of the coverage characteristics of remote sensing data in spatial and spectrum, this paper adopted the interval mathematics method into the representation of user profiles. Based on user profiles, the concepts of the correlation degree and interest degree are introduced. In addition, by the construction of decision matrixes, the solutions of the generations of intelligent services can be converted into the solutions of multiple attribute decision problems. Finally, an instance is given to show the usability of the presented method.

参考文献

[1] LI Deren, ZHANG Liangpei, XIA Guisong. Automatic Analysis and Mining of Remote Sensing Big Data[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(12):1211-1216.(李德仁, 张良培, 夏桂松. 遥感大数据自动分析与数据挖掘[J]. 测绘学报, 2014, 43(12):1211-1216.)
[2] XU Hailing, WU Xiao, LI Xiaodong, et al. Comparison Study of Internet Recommendation System[J]. Journal of Software, 2009, 20(2):350-362.(许海玲, 吴潇, 李晓东, 等. 互联网推荐系统比较研究[J]. 软件学报, 2009, 20(2):350-362.)
[3] LIU Lin, LI Deren, LI Wanwu, et al. Thoughts on Smarter Planet from the View of Geomatics[J]. Geomatics and Information Science of Wuhan University, 2012, 37(10):1248-1251.(柳林, 李德仁, 李万武, 等. 从地球空间信息学的角度对智慧地球的若干思考[J]. 武汉大学学报:信息科学版, 2012, 37(10):1248-1251.)
[4] WU Lihua, LIU Lu. User Profiling for Personalized Recommending Systems:A Review[J]. Journal of the China Society for Scientific and Technical Information, 2006, 25(1):55-62.(吴丽花, 刘鲁. 个性化推荐系统用户建模技术综述[J]. 情报学报, 2006, 25(1):55-62.)
[5] ZENG Chun, XING Chunxiao, ZHOU Lizhu. A Survey of Personalization Technology[J]. Journal of Software, 2002, 13(10):1952-1961.(曾春, 邢春晓, 周立柱. 个性化服务技术综述[J]. 软件学报, 2002, 13(10):1952-1961.)
[6] LIU Jianguo, ZHOU Tao, WANG Binghong. Progress of the Personalized Recommendation Systems[J]. Progress of Nature and Science, 2009, 19(1):1-15.(刘建国, 周涛, 汪秉宏. 个性化推荐系统的研究进展[J]. 自然科学进展, 2009, 19(1):1-15.)
[7] LINDEN G, SMITH B, YORK J. Amazon. com Recommendations:Item-to-item Collaborative Filtering[J]. IEEE Internet Computing, 2003, 7(1):76-80.
[8] WANG Zegen, HUA Yixin. Research on Technology of Active Spatial Information Service[J]. Acta Geodaetica et Cartographica Sinica, 2006, 35(4):379-384, 389.(王泽根, 华一新. 主动空间信息服务技术研究[J]. 测绘学报, 2006, 35(4):379-384, 389.)
[9] MOU Naixia, LIU Wenbao, ZHANG Lingxian, et al. Personalized Recommendations on Spatial Information Services[J]. Science of Surveying and Mapping, 2011, 36(3):104-106.(牟乃夏, 刘文宝, 张灵先, 等. 空间信息服务的个性化问题[J]. 测绘科学, 2011, 36(3):104-106.)
[10] XIA Yu, ZHU Xinyan. Intelligent Spatial Information Delivery Decision-making by Using Interval Analysis[J]. Geomatics and Information Science of Wuhan University, 2013, 38(9):1103-1107.(夏宇, 朱欣焰. 利用区间分析的空间信息智能分发决策[J]. 武汉大学学报:信息科学版, 2013, 38(9):1103-1107.)
[11] XIA Yu. The User Profile Model for Intelligent Delivery of Spatial Information[D]. Wuhan:Wuhan University, 2009.(夏宇. 面向空间信息智能分发的用户偏好模型研究[D]. 武汉:武汉大学, 2009.)
[12] LI Xinguang, FAN Minghu, DU Wu. Research on Dynamic User Profile Model for Intelligent Distribution of Spatial Information[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(5):646-654.(李新广, 范明虎, 杜武. 面向空间信息智能分发的动态化用户偏好模型研究[J]. 测绘学报, 2011, 40(5):646-654.)
[13] HAWALAH A, FASLI M. Utilizing Contextual Ontological User Profiles for Personalized Recommendations[J]. Expert Systems with Applications, 2014, 41(10):4777-4797.
[14] HAWALAH A, FASLI M. Dynamic User Profiles for Web Personalisation[J]. Expert Systems with Applications, 2015, 42(5):2547-2569.
[15] COVER T M, THOMAS J A. Elements of Information Theory[M]. New York:Wiley-Interscience, 2006.
[16] GIOVE S. Interval TOPSIS for Multicriteria Decision Making[C]//MARINARO M, TAGLIAFERRI R.Proceedings of the 13th Italian Workshop on Neural Nets-Revised Papers. Lecture Notes in Computer Science. Berlin:Springer,2002:56-63.
[17] CAI Wen. Extension Theory and Its Application[J]. Chinese Science Bulletin, 1999, 44(17):1538-1548.(蔡文. 可拓论及其应用[J]. 科学通报, 1999, 44(7):673-681.)
[18] EGENHOFER M J. Deriving the Composition of Binary Topological Relations[J]. Journal of Visual Languages and Computing, 1994, 5(2):133-149.
[19] YOONK P. System Selection by Multiple Attribute Decision Making[D]. Manhattan:Kansas State University, 1980.
[20] TZENG G H, HUANG J J. Multiple Attributes Decision Making:Methods and Applications[M]. Boca Raton:CRC Press, 2011.
文章导航

/