Deriving and verifying statistical distribution of a hyperlink-based Web page quality metric

  • Authors:

  • Devanshu Dhyani;Sourav S. Bhowmick;Wee-Keong Ng

  • Affiliations:

  • School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2003

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Abstract

The significance of modeling and measuring various attributes of the Web in part or as a whole is undeniable. Modeling information phenomena on the Web constitutes fundamental research towards an understanding that will contribute to the goal of increasing its utility. Although Web related metrics have become increasingly sophisticated, few employ models to explain their measurements. In this paper, we discuss issues related to metrics for Web page significance. These metrics are used for ranking the quality and relevance of Web pages in response to user needs. We focus on the problem of ascertaining the statistical distribution of some well-known hyperlink-based Web page quality metrics. Based on empirical distributions of Web page degrees, we derived analytically the probability distribution for the PageRank metric. We found out that it follows the familiar inverse polynomial law reported for Web page degrees. We verified the theoretical exercise with experimental results that suggest a highly concentrated distribution of the metric.