Evolving semantic web with social navigation

被引:17
作者
Beydoun, Ghassan [1 ]
Kultchitsky, Roman
Manasseh, Grace
机构
[1] Univ Wollongong, Sch Informat Syst & Econ, Wollongong, NSW 2500, Australia
[2] Amer Univ Beirut, Dept Comp Sci, Beirut, Lebanon
关键词
cooperative systems; intelligent searching; semantic web; E-learning application; interactive knowledge acquisition; formal concept analysis application; machine learning application;
D O I
10.1016/j.eswa.2005.11.035
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
The Semantic Web (SW) is a meta-web built on the existing WWW to facilitate its access. SW expresses and exploits dependencies between web pages to yield focused search results. Manual annotation of web pages towards building a SW is hindered by at least two user dependent factors: users do not agree on an annotation standard, which can be used to extricate their pages inter-dependencies; and they are simply too lazy to use, undertake and maintain annotation of pages. In this paper, we present an alternative to exploit web pages dependencies: as users surf the net, they create a virtual surfing trail which can be shared with other users, this parallels social navigation for knowledge. We capture and use these trails to allow subsequent intelligent search of the web. People surfing the net with different interests and objectives do not leave similar and mutually beneficial trails. However, individuals in a given interest group produce trails that are of interest to the whole group. Moreover, special interest groups will be higher motivated than casual users to rate utility of pages they browse. In this paper, we introduce our system KAPUST1.2 (Keeper And Processor of User Surfing Trails). It captures user trails as they search the internet. It constructs a semantic web structure from the trails. The semantic web structure is expressed as a conceptual lattice guiding future searches. KAPUST is deployed as an E-learning software for an undergraduate class. First results indicated that indeed it is possible to process surfing trails into useful knowledge structures which can later be used to produce intelligent searching. (C) 2006 Published by Elsevier Ltd.
引用
收藏
页码:265 / 276
页数:12
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