Refining search results using a mining framework

  • Authors:

  • Ok-Ran Jeong;Eunseok Lee;Won Kim

  • Affiliations:

  • School of Information and Communication Engineering, Sungkyunkwan University, Suwon 440-746, South Korea;School of Information and Communication Engineering, Sungkyunkwan University, Suwon 440-746, South Korea;School of Information and Communication Engineering, Sungkyunkwan University, Suwon 440-746, South Korea

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2009

Quantified Score

Hi-index 12.05

Visualization

Abstract

Today's major search engines return ranked search results that match the keywords the user specifies. There have been many proposals to rank the search results such that they match the user's intentions and needs more closely. Despite good advances during the past decade, this problem still requires considerable research, as the number of search results has become ever larger. We define the collection of each search result and all the Web pages that are linked to the result as a search-result drilldown. We hypothesize that by mining and analyzing the top terms in the search-result drilldown of search results, it may be possible to make each search result more meaningful to the user, so that the user may select the desired search results with higher confidence. In this paper, we describe this technique, and show the results of preliminary validation work that we have done.