Ranking search results by web quality dimensions

  • Authors:
  • Joshua C. C. Pun;Frederick H. Lochovsky

  • Affiliations:
  • Hong Kong University of Science and Technology;Hong Kong University of Science and Technology

  • Venue:
  • Journal of Web Engineering
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

Currently, search engines rank search results using mainly link-based metrics. While usually most of the search results are relevant to a user's query, due to how the results are ranked, users often are still not totally satisfied with them. Using a proposed framework of web data quality, it is found that current search engines usually only consider a very small number of the dimensions of web data quality in their ranking algorithms. In this paper, a newly identified web data-quality dimension, appropriateness, which is based on the linguistic and visual complexity of a web page, is studied. It is computed using new metrics that classify web pages into three main appropriateness genres: scholarly, news/general interest and popular. Experiments have shown the effectiveness of the metrics in ranking web pages by whether they are appropriate to a user's task and information needs.