Study on Self-Organization of Community Knowledge Based on "User-Tag" Relationship

  • Teng Guangqing ,
  • He Defang ,
  • Peng Jie ,
  • Zhao Hui
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  • 1. Institute of Scientific and Technical Information of China, Beijing 100038;
    2. School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117

Received date: 2014-08-29

  Revised date: 2014-09-09

  Online published: 2014-10-30

Abstract

As the large-scale application of network analysis theory in the field of knowledge organization, the role of human factors in knowledge organization has gradually attracted academic attention. From the "user-tag" relationship in folksonomy community view, based on the idea of poststructuralist network analysis, the organization structure of community knowledge is identified and analyzed using traditional 1-mode network analysis methods. On this basis, further building the "user-tag" 2-mode network, the issues of "self-organizing" of community knowledge is deeply analyzed based on the interaction between the users and tags in the 2-mode network. The research reveals the influence of subjective perception of the user group on the organization structure of community knowledge, and the shaping of organization structure of the community knowledge on user's subjective perception. The "self-organizing" of community knowledge is tried and explored.

Cite this article

Teng Guangqing , He Defang , Peng Jie , Zhao Hui . Study on Self-Organization of Community Knowledge Based on "User-Tag" Relationship[J]. Library and Information Service, 2014 , 58(20) : 106 -111 . DOI: 10.13266/j.issn.0252-3116.2014.20.016

References

[1] Peters I, Stock G W. Folksonomy and information retreval[J]. Proceedings of the American Society for Information Science and Technology, 2007, 44(1): 1-28.

[2] Andrieu C, de Freitas N, Doucet A, et al. An introduction to MCMC for machine learning[J]. Machine Learning, 2003, 50(1-2): 5-43.

[3] Specia L, Motta E. Integrating folksonomies with the semantic Web[C]//Franconi E, Kifer M, May W. The Semantic Web: Research and Applications.Berlin: Springer-Verlag, 2007:624-639.

[4] Gemmell J, Shepitsen A, Mobasher B, et al. Personalizing navigation in folksonomies using hierarchical tag clustering[C]//Song I-Y, Eder J, Nguyen T M. Data Warehousing and Knowledge Discovery.Berlin: Springer-Verlag, 2008: 196-205.

[5] Schmitz C, Hotho A, Jäschke R, et al. Mining association rules in folksonomies[C]//Batagelj V, Bock H-H, Ferligoj A, et al. Data Science and Classification.Berlin: Springer-Verlag, 2006: 261-270.

[6] Jäschkea R, Hotho A, Schmitz C, et al. Discovering shared conceptualizations in folksonomies[J]. Web Semantics: Science, Services and Agents on the World Wide Web, 2008, 6(1): 38-53.

[7] 路易斯. 网络科学:原理与应用[M].陈向阳,巨修练,译.北京: 机械工业出版社, 2011.

[8] Solskinnsbakk G, Gulla J A, Haderlein V, et al. Quality of hierarchies in ontologies and folksonomies[J]. Data & Knowledge Engineering, 2012, 74: 13-25.

[9] Mas M D. Intelligent interface architectures for folksonomy driven structure network[C]//Barolli L, Xhafa F, Vitabile S, et al. Complex, Intelligent and Software Intensive Systems.Los Angeles: IEEE Computer Society, 2012: 519-525.

[10] Liebowitz J. Linking social network analysis with the analytic hierarchy process for knowledge mapping in organizations[J]. Journal of Knowledge Management, 2005, 9(1): 76-86.

[11] Casillas L. Estimating time between creation and achievement of knowledge objects in learning groups through social network analysis[J]. eLC Research Paper Series, 2011(3): 16-25.

[12] Buraphadeja V. An assessment of critical thinking in an online discussion forum: The use of content analysis and social network analysis[D].Gainesville:University of Florida, 2010.

[13] 奇达夫, 蔡文彬. 社会网络与组织[M].王凤彬,朱超威,译.北京: 中国人民大学出版社, 2007.

[14] Borgatti S P, Everett M G. Network analysis of 2-mode data[J]. Social Networks, 1997, 19(3): 243-269.

[15] Hotho A, Jäschke R, Schmitz C, et al. FolkRank: A ranking algorithm for folksonomies[EB/OL].[2014-08-03]. http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006folkrank.pdf.

[16] Cox T F, Cox M A A. Multidimensional Scaling(2nd Edition)[M]. Boca Raton: CRC Press, 2001.

[17] 波普尔. 客观的知识:一个进化论的研究[M].舒炜光,卓如飞,梁咏新,等译.杭州: 中国美术学院出版社, 2003.

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