Improved Search in Tag-Based Systems

被引:2
|
作者
Awawdeh, Ruba [1 ]
Anderson, Terry [1 ]
机构
[1] Univ Ulster, Sch Comp & Math, Newtownabbey BT37 0QB, North Ireland
来源
2009 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS | 2009年
关键词
D O I
10.1109/ISDA.2009.170
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Social bookmarking systems are used by millions of web users to tag, save and share items. User-defined tags, however, are so variable in quality that searching on these tags alone is ineffective. One way to improve search in bookmarking systems is by adding more metadata to the user-defined tags to enhance tag quality. Such an approach would add value by incorporating information about the content of the resource while retaining the original user-defined tag. Tags automatically extracted from the resource could be the main source for tag enhancement. This paper describes how users' tags can be enhanced with metadata in the form of additional tags automatically extracted from the original document. An evaluation study shows how the enhanced tag set improved user searching in comparison to using only user-defined tags.
引用
收藏
页码:288 / 293
页数:6
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