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Web Structure Mining for Usability Analysis

Authors: Chun-hung Li; Chun Kit Chui;

Web Structure Mining for Usability Analysis

Abstract

The interaction between usability and how a Web site is structured is a complicated issue. In this paper, we discuss a Web structure mining algorithm which allows the automatic extraction of navigational structures in a Web site without performing hypertext analysis. We perform several usability experiments to correlate the usability of Web sites and the structural design of the Web site. Experimental results show that the structure mining algorithm gives reasonable prediction about several design issues in Web structure. The analysis serves as building block in the complex issue of web usability and structure mining.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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