图书情报工作

图书情报工作 >

2016 , Vol. 60 >Issue 17: 130 - 135

DOI: https://doi.org/10.13266/j.issn.0252-3116.2016.17.019

知识组织

基于相对频次的标签相关性判断优化研究

  • 林鑫 ,
  • 石宇 ,
  • 周知
展开
  • 1. 华中师范大学信息管理学院 武汉 430079;
    2. 武汉大学信息管理学院 武汉 430072
林鑫(ORCID:0000-0003-0318-8160),讲师,E-mail:wenqi0426@qq.com;石宇(ORCID:0000-0001-6741-5487),硕士研究生;周知(ORCID:0000-0002-5530-2968),博士研究生。

收稿日期: 2016-02-15

  修回日期: 2016-05-10

  网络出版日期: 2016-09-05

收起

Study on Social Tags Relevance Judgment Optimization Based on Relative Frequency

  • Lin Xin ,
  • Shi Yu ,
  • Zhou Zhi
Expand
  • 1. School of information management of Central China Normal University, Wuhan 430079;
    2. School of Information Management of Wuhan University, Wuhan 430072

Received date: 2016-02-15

  Revised date: 2016-05-10

  Online published: 2016-09-05

Fold

摘要

[目的/意义] 针对笔者此前提出的标签相关性判断策略进行优化，以提升策略的召回率，从而更好地支持标签应用研究与实践。[方法/过程] 为提升策略的召回率，以标签与认知的基本关系为基础，提出一种基于相对频次的改进策略，并以社会化标注社区"豆瓣电影"的675 351位用户的标签数据为例进行实验，以验证策略的效果。[结果/结论] 结果显示，该策略使得标签相关性判断的效果得到了显著改善。其中，对于频次不小于5的标签，策略的召回率大幅提升，由79.63%升至89.36%；准确率虽有略微下滑，由93.33%降至92.02%，但仍保持在较高水平。

关键词： 社会化标签; 标签相关性; 相对频次

本文引用格式

林鑫 , 石宇 , 周知 . 基于相对频次的标签相关性判断优化研究[J]. 图书情报工作, 2016 , 60(17) : 130 -135 . DOI: 10.13266/j.issn.0252-3116.2016.17.019

Abstract

[Purpose/significance] To improve the recall and support the tag application research and practice, this paper optimizes the tactic proposed in our previous paper for social tags relevance judgment. [Method/process] To improve the recall, this paper took the relationship between social tags and cognition as the basis, and proposed an optimization algorithm based on relative frequency, and verified by experiments based on 675 351 Douban Movie users' social tagging data. [Result/conclusion] The results show that the effect of tag relevance judgment for tags whose frequencies are at least 5 has been improved significantly, for the recall rises sharply from 79.63% to 89.36%, and the accuracy rate falls slightly from 93.33% to 92.02%, but remains at a high level.

Key words： social tagging; tag relevance; relative frequency

参考文献

[1] JI A T, YEON C, KIM H N, et al. Collaborative tagging in recommender systems[C]//Ai 2007: Advances in artificial intelligence, Australian joint conference on artificial intelligence, Gold Coast, Australia.Berlin:Springer, 2007:377-386.
[2] XU H, WANG J, HUA X S, et al. Tag refinement by regularized LDA[C]//International conference on multimedia 2009, Vancouver, British Columbia.New York:ACM, 2009:573-576.
[3] 林鑫,周知. 基于活跃度指数的标签相关性判断研究[J].图书情报工作,2015,59(9):97-103.
[4] SINHA R. A cognitive analysis of tagging [EB/OL]. [2015-11-06]. http://rashmisinha.com /2005/09/27/a-cognitive-analysis-of-tagging/.
[5] 易明,曹高辉,毛进,等.基于Tag的知识主题网络构建与Web知识推送研究[J].中国图书馆学报,2011,37(4):4-12.
[6] 马费成,张斌.图书标注环境下用户的认知特征[J].中国图书馆学报,2014,40(1):4-14.
[7] VERES C. Concept modeling by the masses: folksonomy structure and interoperability[C]//Conceptual modeling-ER 2006. Berlin heidelberg:Springer, 2006: 325-338.
[8] 李枫林,张景.基于用户标注行为的相关性分析及重排序[J].情报理论与实践,2010(10):57-61.
[9] 林鑫,周知. 用户认知对标签使用行为的影响分析[J].情报理论与实践,2015,38(10):85-88.
[10] 查先进, 吕彬. 知识共享视角下的大众标注行为研究——基于标签的实证分析[J]. 图书馆论坛,2010,30(6):76-81.
[11] GOLDER S A, HUBERMAN B A. Usage patterns of collaborative tagging systems[J]. Journal of information science, 2006, 32(2): 198-208.
[12] Wikipedia. Cohen's kappa[EB/OL].[2015-02-10]. http://en.wikipedia.org/wiki/Cohen%27 s_kappa.
[13] WASH R, RADER E. Public bookmarks and private benefits: an analysis of incentives in social computing[J]. Proceedings of the american society for information science and technology, 2007, 44(1): 1-13.
[14] SEN S, LAM S K, RASHID A M, et al. Tagging, communities, vocabulary, evolution[C]//Proceedings of the 2006 20th anniversary conference on computer supported cooperative work. New York:ACM, 2006: 181-190.

Options
文章导航

/

〈 〉