Please wait a minute...
Advanced Search
现代图书情报技术  2008, Vol. 24 Issue (10): 6-10     https://doi.org/10.11925/infotech.1003-3513.2008.10.02
  数字图书馆 本期目录 | 过刊浏览 | 高级检索 |
基于概念外延的Folksonomy语义关系挖掘方法
周鑫 王军
(北京大学信息管理系 北京 100871)
Semantic Relations Mining in Folksonomy Based on Extensions of Concepts
Zhou Xin  Wang Jun
(Department of Information Management, Peking University, Beijing 100871, China)
全文: PDF (390 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 

为改善Folksonomy中的资源利用效率,对Tag间的语义关系挖掘进行研究,提出一种利用大众标引关系、通过界定概念外延挖掘Tag间语义关系的方法。在del.icio.us真实数据上所进行的实验验证该方法是可行的。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
周鑫
王军
关键词 语义关系挖掘Folksonomydel.icio.us    
Abstract

In order to improve the performance of Folksonomy, the authors study how to find out the relations between Tags. A method of mining semantic relations, based on the folk-tagging and extensions of concepts, is proposed in this paper. An experiment on the data set of del.icio.us is also conducted, and it indicates that the method is practicable, but more improvement is needed.

Key wordsSemantic relations mining    Folksonomy    del.icio.us
收稿日期: 2008-09-02      出版日期: 2008-10-25
ZTFLH: 

TP393

 
通讯作者: 周鑫     E-mail: sydjoule@gmail.com
作者简介: 周鑫,王军
引用本文:   
周鑫,王军. 基于概念外延的Folksonomy语义关系挖掘方法[J]. 现代图书情报技术, 2008, 24(10): 6-10.
Zhou Xin,Wang Jun. Semantic Relations Mining in Folksonomy Based on Extensions of Concepts. New Technology of Library and Information Service, 2008, 24(10): 6-10.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2008.10.02      或      http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2008/V24/I10/6

[1] Wikipedia. Folksonomy: From Wikipedia, the Free Encyclopedia[EB/OL]. (2008-05-17). [2008-05-22]. http://en.wikipedia.org/wiki/Folksonomy.
[2] Damme C V, Hepp M, Siorpaes K. FolksOntology: An Integrated Approach for Turning Folksonomies to Ontologies[EB/OL]. [2008-05-22]. http://members.deri.at/~katharinas/files/publications/VanDammeHeppSiorpaes_final.pdf.
[3] Begelman G, Keller P, Smadja F. Automated Tag Clustering: Improving Search and Exploration in the Tag space[C/OL]. (2006-05-22). [2008-05-24]. http://www.pui.ch/phred/automated_Tag_clustering/automated_Tag_clustering.pdf.
[4] Schmitz C, Hotho A, Jaschke R, et al. Mining Association Rules in Folksonomies[EB/OL]. [2008-05-24]. http://www.kde.cs.uni-kassel.de/hotho/pub/2006/schmitz2006asso_ifcs.pdf.
[5] Mika P. Ontologies Are Us: A Unified Model of Social Networks and Semantics[C/OL]. [2008-05-24]. http://www.cs.vu.nl/~pmika/research/papers/ISWC-Folksonomy.pdf.
[6] Specia L, Motta E. Integrating Folksonomies with the Semantic Web[C]. In: Proceeding of 4th European Semantic Web Conference (ESWC2007). Innsbruck Austria, 2007: 625.
[7] Angeletou S, Sabou M, Specia L, et al. Bridging the Gap between Folksonomies and the Semantic Web: An Experience Report[EB/OL]. [2008-05-23]. http://kmi.open.ac.uk/people/marta/papers/semnet2007.pdf.
[8] Zhang L, Wu X, Yu Y. Emergent Semantics from Folksonomies: A Quantitative Study[J]. Journal on Data Semantics, 2006(6): 168-186.
[9] Wikipedia. Extension (Semantics): From Wikipedia, the free encyclopedia[EB/OL]. (2008-05-22). [2008-05-25]. http://en.wikipedia.org/wiki/Extension_(semantics).
[10] Schmitz P. Inducing Ontology from Flickr Tags[C]. In: Proceeding of Collaborative Web Tagging Workshop, at 15th International World Wide Web Conference (WWW2006). Edinburgh UK, 2006: 2-3.

[1] 毕强, 周姗姗, 马志强, 滕广青. 面向知识关联的标签云优化机理研究*[J]. 现代图书情报技术, 2014, 30(5): 33-40.
[2] 余本功, 顾佳伟. 基于Folksonomy和RDF的信息组织与表示[J]. 现代图书情报技术, 2014, 30(11): 24-30.
[3] 毕强, 王雨. 国外Folksonomy应用研究的前沿进展及热点分析[J]. 现代图书情报技术, 2013, 29(7/8): 36-42.
[4] 滕广青, 毕达天, 任晶, 陈晓美. Folksonomy中用户标签的语义紧密性研究[J]. 现代图书情报技术, 2013, (12): 48-54.
[5] 滕广青, 毕强, 高娅. 基于概念格的Folksonomy知识组织研究——关联标签的结构特征分析[J]. 现代图书情报技术, 2012, 28(6): 22-28.
[6] 王翠英. 基于Folksonomies的用户偏好挖掘研究[J]. 现代图书情报技术, 2009, 25(6): 37-43.
[7] 王翠英(编译). 标签的聚类分析研究[J]. 现代图书情报技术, 2008, 24(5): 67-71.
[8] 张玫,张晓林. Connotea中Social Tagging机制研究[J]. 现代图书情报技术, 2007, 2(7): 1-4.
[9] 刘峥. 基于folksonomy的数字资源服务系统研究[J]. 现代图书情报技术, 2006, 1(2): 40-42.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 2015 《数据分析与知识发现》编辑部
地址:北京市海淀区中关村北四环西路33号 邮编:100190
电话/传真:(010)82626611-6626,82624938
E-mail:jishu@mail.las.ac.cn