Please wait a minute...
New Technology of Library and Information Service  2005, Vol. 21 Issue (4): 45-47    DOI: 10.11925/infotech.1003-3513.2005.04.12
Current Issue | Archive | Adv Search |
A Ontology-based Personalized Retrieval Method
Qin Chunxiu   Zhao Pengwei   Dou Yongxiang
 (School of Economics Management, Xidian University,Xi'  an 710071,China)
Download: PDF (0 KB)  
Export: BibTeX | EndNote (RIS)      

Current search tools are designed for all users, no considering of the special needs of individual user. A way of personalized retrieval based on ontology is proposed in this paper,in which individual user search intention can be deduced by the user interest model which is constructed by learning user search history automatically. This way can be used in intelligent information retrieval such as Internet on special domains or special user groups and Intranet.

Key wordsOntology      User search history      User interest model      Personalized retrieval     
Received: 25 November 2004      Published: 25 April 2005


Corresponding Authors: Qin Chunxiu     E-mail:
About author:: Qin Chunxiu,Zhao Pengwei,Dou Yongxiang

Cite this article:

Qin Chunxiu,Zhao Pengwei,Dou Yongxiang. A Ontology-based Personalized Retrieval Method. New Technology of Library and Information Service, 2005, 21(4): 45-47.

URL:     OR

1A.E. Howe and D. Dreilinger.SavvySearch: A Meta-Search Engine that Learns with Search Engines to Query.AI Maganize,1997,18(2):19-25
2A.L. Powell, J.C. French, J.P. Callan, M.E. Connell, and C.L. Viles. The Impact of Database Selection on Distributed Searching.proc.23rd Ann. int'l ACM SIGIR Conf. Research and Development in Information Retrival, 2000: 232-239
3C.T.Yu, W.Meng, W. Wu,and K.-L.Liu. Efficient and Effective Metasearch for Text Database Incorporating Linkages among Documents. ACM SIGMOD,2001:187-198
5D.H. Widyantoro, T.R. Ioerger,and J.Yen.An Adaptive Algorithm for Learning Changes in User Interest s.Proc. Eighth ACM Int’l Conf. Information and Knowledge Management(CIKM), 1999:254-261
6U.Cetintemel, M.J.Franklin,and C.L.Giles. Self-Adaptive User Profiles for Large-Scale Data Delivery.Proc.16th Int'l Conf.Data Eng.(ICDE),2000:622-633
7T.Joachims,D.Freitage,and T.Mitchell. Webwatcher: A Tour Guide for the World Wide Wed.Proc,15th Int'l Joint Conf. Artificial Intelligence(IJCAI),1997:770-777
8Fang Liu, Clement Yu, Senior Member. Personalized web search for improving retrieval effectiveness. IEEE transactions on Knowledge and Data engineering IEEE, 2004(1):28-40
10 Aug.8,2004)

[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] 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.
[6] 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.
[7] 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.
[8] 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.
[9] 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.
[10] 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.
[11] 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.
[12] 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.
[13] 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.
[14] Zeng Jin,Lu Wei,Ding Heng,Chen Haihua. Modeling User’s Interests Based on Image Semantics[J]. 数据分析与知识发现, 2017, 1(4): 76-83.
[15] Liu Jian,Bi Qiang,Liu Qingxu,Wang Fu. New Content Recommendation Service of Digital Literature[J]. 现代图书情报技术, 2016, 32(9): 70-77.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938