NDLI: An improved approach for web page quality assessment

Content Provider	IEEE Xplore Digital Library
Author	Naw Lay Wah
Copyright Year	2011
Description	Author affiliation: University of Computer Studies Mandalay, Myanmar (Naw Lay Wah)
Abstract	Internet websites need to be measured and evaluated for quality and better understanding. Several Metrics were proposed to correspond with items that Web usability guideline associate with good design such as word count, total page size in bytes, body text percentage, average link text count and others. This study investigates empirically the web page quality on the basis of the 16 assessed metrics. Support Vector Machine (SVM) model is proposed to predict the good web pages and not good web pages. Web sites are collected from Webby Awards data (2001–2010) and Top Ten PC Magazines. The findings of quantitative analysis of web page attributes are expressed and how these attributes are calculated. The metrics captured in SVM model can be used to predict the website designs the good and the bad.
Starting Page	315
Ending Page	320
File Size	1301180
Page Count	6
File Format	PDF
ISBN	9781467300995
e-ISBN	9781467301022
DOI	10.1109/SCOReD.2011.6148757
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-19
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Support vector machines Accuracy Web pages Predictive models Support Vector Machine Web Interface Metrics Mathematical model Usability Guidelines Guidelines
Content Type	Text
Resource Type	Article

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