Please wait a minute...
New Technology of Library and Information Service  2008, Vol. 24 Issue (2): 69-75    DOI: 10.11925/infotech.1003-3513.2008.02.13
Current Issue | Archive | Adv Search |
A Research on Retrieval Results Clustering and Relevant Recommendation in Digital Library
Ji Yonghui
(Department of Information Management, Nanjing University, Nanjing 210093, China)
Download: PDF(651 KB)   HTML  
Export: BibTeX | EndNote (RIS)      

This paper discusses how to implement the clustering of document retrieval results, the relevant recommendation of related documents, related authors & organizations and related key-words. The author presents how to visualize the results of clustering and recommendation in graph on the documents retrieval platform of digital library, which can increase the users’ satisfaction.

Key wordsDigital library      Documents retrieval      Clustering      Rrelevant recommendation      Visualization      GDI+      K-Means algorithm     
Received: 30 October 2007      Published: 25 February 2008


Corresponding Authors: Ji Yonghui     E-mail:
About author:: Ji Yonghui

Cite this article:

Ji Yonghui. A Research on Retrieval Results Clustering and Relevant Recommendation in Digital Library. New Technology of Library and Information Service, 2008, 24(2): 69-75.

URL:     OR

[1] Vivísimo. Inc - Enterprise Search, Federated Search and Clustering[EB/OL].[2007-11-08].
[2] Computer and Information Science Papers CiteSeer Publications Research Index[EB/OL].[2007-11-08].
[3] CNKI知识网络知识服务平台[EB/OL].[2007-11-08].
[4] C J  van Rijsbergen. Information Retrieval[M]. Second edition. London: Buttersworth, 1989.
[5] Jiawei Han, Micheline Kamber. 数据挖掘:概念与技术[M]. 孟晓峰,范明(译). 北京:机械工业出版社,2001.
[6] Salton G, Wong A, Yang C S. A Vector Space Model for Automatic Indexing[J]. Communications of the ACM, 1975(18):613 -620.
[7] Jain A K, Murty M N, Flynn P J. Data Clustering: A Review[J]. ACM Computing Surveys, 1999,31(3), 264-323.
[8] 行小帅,潘进,焦李成.基于免疫规划的K-Means聚类算法[J].计算机学报,2003,26(5):605-610.
[9] 周昭涛.文本聚类分析效果评价及文本表示研究[D].北京:中国科学院研究生院,2005.
[10] 刘远超,王晓龙,刘秉权.一种改进的K-Means文档聚类初值选择算法[J].高科技通讯,2006,16(1):11-15.
[11] 万小军,杨建武,陈晓鸥.文档聚类中K-means算法的一种改进算法[J].计算机工程,2003,29(2):102-103.
[12] 马文峰,高凤荣,王珊.论数字图书馆个性化信息推荐系统[J].现代图书情报技术,2003(2):16-18.
[13] Sarwar B M, Karypis S G, Konstan J A, et al. Analysis of Recommendation Algorithms for E-commerce[C]. Proceedings of the ACM EC’00 Conference. Minneapolis, MN.,2000:158-167.
[14] Nahum D Gershon, Stephen G Eick. Information Visualization[J]. IEEE Computer Graphics and Applications. 1997, 17(4):29-31.
[15] Mahesh Chand. GDI+图形程序设计[M]. 韩江(译).北京:电子工业出版社,2005.

[1] Haici Yang,Jun Wang. Visualizing Knowledge Graph of Academic Inheritance in Song Dynasty[J]. 数据分析与知识发现, 2019, 3(6): 109-116.
[2] Yanan Yang,Wenhui Zhao,Jian Zhang,Shen Tan,Beibei Zhang. Visualizing Policy Texts Based on Multi-View Collaboration[J]. 数据分析与知识发现, 2019, 3(6): 30-41.
[3] Cheng Zhou,Hongqin Wei. Evaluating and Classifying Patent Values Based on Self-Organizing Maps and Support Vector Machine[J]. 数据分析与知识发现, 2019, 3(5): 117-124.
[4] Jiang Wu,Guanjun Liu,Xian Hu. An Overview of Online Medical and Health Research: Hot Topics, Theme Evolution and Research Content[J]. 数据分析与知识发现, 2019, 3(4): 2-12.
[5] Quan Lu,Anqi Zhu,Jiyue Zhang,Jing Chen. Research on User Information Requirement in Chinese Network Health Community: Taking Tumor-forum Data of Qiuyi as an Example[J]. 数据分析与知识发现, 2019, 3(4): 22-32.
[6] Jiang Wu,Yinghui Zhao,Jiahui Gao. Research on Weibo Opinion Leaders Identification and Analysis in Medical Public Opinion Incidents[J]. 数据分析与知识发现, 2019, 3(4): 53-62.
[7] Lianjie Xiao,Mengrui Gao,Xinning Su. An Under-sampling Ensemble Classification Algorithm Based on Fuzzy C-Means Clustering for Imbalanced Data[J]. 数据分析与知识发现, 2019, 3(4): 90-96.
[8] Tingxin Wen,Yangzi Li,Jingshuang Sun. News Hotspots Discovery Method Based on Multi Factor Feature Selection and AFOA/K-means[J]. 数据分析与知识发现, 2019, 3(4): 97-106.
[9] Zhiqiang Wu,Zhongming Zhu,Wei Liu,Sili Wang. Research and Practice on the Extension of Knowledge Analysis and Visualization Function in CSpace[J]. 数据分析与知识发现, 2019, 3(3): 112-119.
[10] Jiaxin Ye,Huixiang Xiong. Recommending Personalized Contents from Cross-Domain Resources Based on Tags[J]. 数据分析与知识发现, 2019, 3(2): 21-32.
[11] Tao Zhang,Haiqun Ma. Clustering Policy Texts Based on LDA Topic Model[J]. 数据分析与知识发现, 2018, 2(9): 59-65.
[12] Xiangdong Li,Fan Gao,Youhai Li. Categorizing Documents Automatically within Common Semantic Space[J]. 数据分析与知识发现, 2018, 2(9): 66-73.
[13] Ting Chen,Guopeng Li,Xiaomei Wang. Visualizing Appropriation of Research Funding with t-SNE Algorithm[J]. 数据分析与知识发现, 2018, 2(8): 1-9.
[14] Xiufang Wang,Shu Sheng,Yan Lu. Analyzing Public Opinion from Microblog with Topic Clustering and Sentiment Intensity[J]. 数据分析与知识发现, 2018, 2(6): 37-47.
[15] Sinan Yang,Jian Xu,Pingping Ye. Review of Online Sentiment Visualization Techniques[J]. 数据分析与知识发现, 2018, 2(5): 77-87.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938