Please wait a minute...
New Technology of Library and Information Service  2013, Vol. 29 Issue (11): 81-85    DOI: 10.11925/infotech.1003-3513.2013.11.12
Current Issue | Archive | Adv Search |
A Method of Information Retrieval Results Visualization Based on Social Network Analysis
Zhou Shanshan, Bi Qiang, Gao Junfeng
School of Management, Jilin University, Changchun 130022, China
Export: BibTeX | EndNote (RIS)      
Abstract  This paper analyzes the two defects of traditional presentation methods for retrieval results, and proposes a method of information retrieval results visualization based on social network. Starting from the medium dimension of scientific research authors and with the purpose of figuring out the relationships among the document authors, the paper builds an adjacent matrix based on the authors' research network structure and explores the invisible knowledge retrieval problem under the academic information aggregation and association. The re-aggregation of the retrieval results in form of a graph are directly shown to the users in order to achieve the purpose of improving digital library knowledge service.
Key wordsDigital library      Social network analysis      Information retrieval      Visualization      Knowledge converge     
Received: 07 August 2013      Published: 29 November 2013
:  G250  

Cite this article:

Zhou Shanshan, Bi Qiang, Gao Junfeng. A Method of Information Retrieval Results Visualization Based on Social Network Analysis. New Technology of Library and Information Service, 2013, 29(11): 81-85.

URL:     OR

[1] TileBars: Visualization of Term Distribution Information in Full Text Information Access [EB/OL]. [2013-07-05].
[2] Reexamining the Cluster Hypothesis: Scatter/Gather on Retrieval Results [EB/OL]. [2013-07-05].
[3] Chen T T, Yen D C. CociteSeer:A System to Visualize Large Cocitation Networks[J]. The Electronic Library, 2010, 28(4): 477-491.
[4] Sokhn M, Mugellini E, Khaled O A. Knowledge Modeling for Enhanced Information Retrieval and Visualization[J]. Advances in Intelligent and Soft Computing, 2010, 67: 199-208.
[5] ConceptLink:Visual Exploration of Medical Concepts[EB/OL]. [2013-11-03].
[6] Wong B L W,Choudhury S,Rooney C, et al. INVISQUE: Technology and Methodologies for Interactive Information Visualization and Analytics in Large Library Collections[C]. In: Proceedings of the 15th International Conference on Theory and Practice of Digital Libraries: Research and Advanced Technology for Digital Libraries (TPDL'11), Berlin, Germany. Berlin, Heidelberg: Springer-Verlag,2011: 227-235.
[7] Groxis [EB/OL]. [2013-07-18].
[8] AquaBrowser [EB/OL]. [2013 -07-22].
[9] 王畅. 可视化信息检索技术的应用——以EBSCOhost2.0为例[J]. 图书馆学刊,2010(6):87-89. (Wang Chang. An Application of Visual Information Retrieval Techniques——Case in EBSCOhost2.0 [J]. Journal of Library Science, 2010(6): 87-89.)
[10] 许德山,张智雄, 邢美凤. 面向本体知识库的可视化检索研究[J]. 情报理论与实践,2010,33(8):114-117.(Xu Deshan,Zhang Zhixiong, Xing Meifeng.Research on Visual Retrieval Oriented to Ontology Knowledge Base [J].Information Studies: Theory & Application, 2010, 33(8): 114-117.)
[11] Shen R, Wang J, Fox E A. A Lightweight Protocol Between Digital Libraries and Visualization System[C]. In: Proceedings of JCDL Workshop on Visual Interfaces to Digital Libraries. London:Springer-Verlag, 2002:217-225.
[12] Ha I, Oh K, Hong M, et al. Ontology-driven Visualization System for Semantic Searching[C]. In: Proceedings of International Conference on Information Science and Applications (ICISA'11), Jeju Island,South Korea. 2011: 1-6.
[13] 许德山,张智雄. 面向本体知识库的可视化检索研究[J]. 情报理论与实践,2010,33(8):114-117.(Xu Deshan,Zhang Zhixiong.Research on Visual Retrieval Oriented to Onology Knowledge Base[J].Information Studies:Theory & Application,2010,33(8):114-117.)
[14] 戴维.诺克, 杨松.社会网络分析[M]. 李兰译.上海:格致出版社,2012:17-23. (David Knoke, Yang Song. Social Network Analysis[M]. Translated by Li Lan. Shanghai: Truth & Wisdom Press, 2012:17-23. )
[1] Huang Mingxuan,Jiang Caoqing,Lu Shoudong. Expanding Queries Based on Word Embedding and Expansion Terms[J]. 数据分析与知识发现, 2021, 5(6): 115-125.
[2] Gao Yilin,Min Chao. Comparing Technology Diffusion Structure of China and the U.S. to Countries Along the Belt and Road[J]. 数据分析与知识发现, 2021, 5(6): 80-92.
[3] Meng Zhen,Wang Hao,Yu Wei,Deng Sanhong,Zhang Baolong. Vocal Music Classification Based on Multi-category Feature Fusion[J]. 数据分析与知识发现, 2021, 5(5): 59-70.
[4] Li Yueyan,Wang Hao,Deng Sanhong,Wang Wei. Research Trends of Information Retrieval——Case Study of SIGIR Conference Papers[J]. 数据分析与知识发现, 2021, 5(4): 13-24.
[5] Chen Ting,Wang Haiming,Wang Xiaomei. Detecting Funding Topics Evolutions with Visualization[J]. 数据分析与知识发现, 2020, 4(2/3): 60-67.
[6] Peng Guan,Yuefen Wang. Advances in Patent Network[J]. 数据分析与知识发现, 2020, 4(1): 26-39.
[7] Mingxuan Huang,Shoudong Lu,Hui Xu. Cross-Language Information Retrieval Based on Weighted Association Patterns and Rule Consequent Expansion[J]. 数据分析与知识发现, 2019, 3(9): 77-87.
[8] 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.
[9] 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.
[10] 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.
[11] 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.
[12] Chen Ting,Li Guopeng,Wang Xiaomei. Visualizing Appropriation of Research Funding with t-SNE Algorithm[J]. 数据分析与知识发现, 2018, 2(8): 1-9.
[13] Sun Haixia,Wang Lei,Wu Yingjie,Hua Weina,Li Junlian. Matching Strategies for Institution Names in Literature Database[J]. 数据分析与知识发现, 2018, 2(8): 88-97.
[14] Yang Sinan,Xu Jian,Ye Pingping. Review of Online Sentiment Visualization Techniques[J]. 数据分析与知识发现, 2018, 2(5): 77-87.
[15] Wang Li,Zou Lixue,Liu Xiwen. Visualizing Document Correlation Based on LDA Model[J]. 数据分析与知识发现, 2018, 2(3): 98-106.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938