Improving Search in Tag-Based Systems with Automatically Extracted Keywords

被引:0
|
作者
Awawdeh, Ruba [1 ]
Anderson, Terry [1 ]
机构
[1] Univ Ulster, Sch Comp & Math, Newtownabbey BT37 0QB, North Ireland
来源
KNOWLEDGE SCIENCE, ENGINEERING AND MANAGEMENT | 2010年 / 6291卷
关键词
Tagging; Folksonomy; Searching; INFORMATION-RETRIEVAL;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Tag-based 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 unsatisfactory. One way to improve search in book-marking systems is by adding more metadata to the user-created tags to enhance tag quality. The additional metadata we have used is based on document content and largely avoids the idiosyncratic and ambiguous terms too often evident in user-created tags. Such an approach adds value by incorporating information about the content of the resource while retaining the original user-created tags. This paper describes how users' tags can be enhanced with metadata automatically extracted from the original document. An experiment comparing search based only on user-created tags with search using an automatically enhanced tag set, demonstrates how incorporating the extra tags can offer significant benefits.
引用
收藏
页码:378 / 387
页数:10
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