Please wait a minute...
New Technology of Library and Information Service  2009, Vol. 25 Issue (11): 34-39    DOI: 10.11925/infotech.1003-3513.2009.11.07
article Current Issue | Archive | Adv Search |
Design and Realization of Agricultural Scientific Information User Modeling System Based on Ontology
Zhang Yu1,2   Su Xiaolu1,2   Liu Shihong1,2   Li Jing3,4    Hu Haiyan1,2
1(Institute of Agriculture Information, Chinese Academy of Agricultural Sciences, Beijing 100081, China)
2(Key Laboratory of Digital Agricultural Early-warning Technology Ministry of Agriculture of  the People’s Republic of China, Beijing 100081, China)
3(Mobile Postdoctoral Center, Institute of Agriculture Information, Chinese Academy of
Agricultural Sciences, Beijing 100081, China)
4(National Library of Standards, China National Institute of Standardization, Beijing 100088, China)
Download: PDF (711 KB)  
Export: BibTeX | EndNote (RIS)      

This paper adopts the method of building user modeling and domain Ontology approach, and extracts the user information through studying and analyzing the user search history. Then the user modeling that consists of user Ontology and user concept vectors is constructed. The experiment shows that this study improves the order of the user retrieval results.

Key wordsUser modeling      Ontology      TF×IDF     
Received: 27 September 2009      Published: 25 November 2009



Corresponding Authors: Zhang Yu     E-mail:
About author:: Zhang Yu,Su Xiaolu,Liu Shihong,Li Jing,Hu Haiyan

Cite this article:

Zhang Yu,Su Xiaolu,Liu Shihong,Li Jing,Hu Haiyan. Design and Realization of Agricultural Scientific Information User Modeling System Based on Ontology. New Technology of Library and Information Service, 2009, 25(11): 34-39.

URL:     OR

[1] 杨建林.基于文献集相似度的分类方法[J].情报学报,1999,18(3):87-89.
[2] Bruno Errico,Luigia Carlucci Aiello.Intelligent Agents in the Situation Calculus:An Application to User Modeling[J].Lecture Notes in Computer Science,1996(1085):126-140.
[3] Razmerita L, Angehrn A, Maedche A. Ontology-based User Modeling for Knowledge Management Systems[J].Integrated Series in Information Systems, 2007(14):635-664.
[4] Heckmann D, Schwartz T, Brandherm B, et al. Gumo-The General User Model Ontology[J]. Lecture Notes in Computer Science, 2005(3538):428-432.
[5] Vincent Schickel-Zuber,Boi Faltings.Overcoming Incomplete User Models in Recommendation Systems via an Ontology[J].Advances in Web Mining and Web Usage Analysis,2006(4198):39-57.
[6] Célia da Costa Pereira, Andrea G B Tettamanzi.An Ontology-based Method for User Model Acquisition[J].Soft Computing in Ontologies and Semantic Web,2006(204):211-229.
[7] 关庆珍.基于本体的个性化信息搜索的用户模型研究[D].重庆:西南大学,2008.
[8] 许琳.基于本体的个性化信息服务用户模型构建研究[D].长春:吉林大学,2008.
[9] Zhang H, Song Y, Song H T.Construction of Ontology-based User Model for Web Personalization[C].In:Proceedings of the 11th International Conference for User Modeling,Corfu, Greece.Berlin, Heidelberg: Springer-Verlag,2007:67-76.
[10] 张炜.个性化推荐系统中基于本体的用户建模研究[D].南京:南京理工大学,2007.
[11] 黄海江.基于本体的学习内容个性化推荐[D].长沙:湖南大学, 2007.
[12] 耿科明.基于本体的个性化信息服务研究[D].保定:河北大学, 2006.
[13] 吴军. 数学之美系列九——如何确定网页和查询的相关性[EB/OL]. (2006-06-27). [2009-05-10].
[14] 徐文海,温有奎. 一种基于TFIDF方法的中文关键词抽取算法[J].情报理论与实践,2008,31(2):298-302.

[1] Shaohua Qiang,Yunlu Luo,Yupeng Li,Peng Wu. Ontology Reasoning for Financial Affairs with RBR and CBR[J]. 数据分析与知识发现, 2019, 3(8): 94-104.
[2] Shiqi Deng,Liang Hong. Constructing Domain Ontology for Intelligent Applications: Case Study of Anti Tele-Fraud[J]. 数据分析与知识发现, 2019, 3(7): 73-84.
[3] Zhu Fu,Yuefen Wang,Xuhui Ding. Semantic Representation of Design Process Knowledge Reuse[J]. 数据分析与知识发现, 2019, 3(6): 21-29.
[4] Guangshang Gao. A Survey of User Profiles Methods[J]. 数据分析与知识发现, 2019, 3(3): 25-35.
[5] Hui Nie. Modeling Users with Word Vector and Term-Graph Algorithm[J]. 数据分析与知识发现, 2019, 3(12): 30-40.
[6] Ying Wang,Li Qian,Jing Xie,Zhijun Chang,Beibei Kong. Building Knowledge Graph with Sci-Tech Big Data[J]. 数据分析与知识发现, 2019, 3(1): 15-26.
[7] He Youshi,He Shufang. Sentiment Mining of Online Product Reviews Based on Domain Ontology[J]. 数据分析与知识发现, 2018, 2(8): 60-68.
[8] Tang Huihui,Wang Hao,Zhang Zixuan,Wang Xueying. Extracting Names of Historical Events Based on Chinese Character Tags[J]. 数据分析与知识发现, 2018, 2(7): 89-100.
[9] Pang Beibei,Gou Juanqiong,Mu Wenxin. Extracting Topics and Their Relationship from College Student Mentoring[J]. 数据分析与知识发现, 2018, 2(6): 92-101.
[10] Ding Shengchun,Liu Menglu,Fu Zhu. Unified Multidimensional Model Based on Knowledge Flow in Conceptual Design[J]. 数据分析与知识发现, 2018, 2(2): 11-19.
[11] Tu Haili,Tang Xiaobo. Building Product Recommendation Model Based on Tags[J]. 数据分析与知识发现, 2017, 1(9): 28-39.
[12] Chen Erjing,Jiang Enbo. Review of Studies on Text Similarity Measures[J]. 数据分析与知识发现, 2017, 1(6): 1-11.
[13] Bai Rujiang,Leng Fuhai,Liao Junhua. An Improved Cosine Text Similarity Computing Method Based on Semantic Chunk Feature[J]. 数据分析与知识发现, 2017, 1(6): 56-64.
[14] Wu Dan,Liu Chang,Li Yi. Changing Sentiments of Pedestrian Navigation System Users[J]. 数据分析与知识发现, 2017, 1(5): 42-51.
[15] Wang Qiangbing,Zhang Chengzhi. Constructing Users Profiles with Content and Gesture Behaviors[J]. 数据分析与知识发现, 2017, 1(2): 80-86.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938