A coherent measurement of web-search Relevance

William R. Mahoney, Peter Hospodka, William Sousan, Ryan Nickell, Qiuming Zhu

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

We present a metric for quantitatively assessing the quality of Web searches. The Relevance-of-Searching-on-Target index measures how relevant a search result is with respect to the searcher's interest and intention. The measurement is established on the basis of the cognitive characteristics of common user's online Web-browsing behavior and processes. We evaluated the accuracy of the index function with respect to a set of surveys conducted on several groups of our college students. While the index is primarily intended to be used to compare the Web-search results and tell which is more relevant, it can be extended to other applications. For example, it can be used to evaluate the techniques that people apply to improve the Web-search quality (including the quality of search engines), as well as other factors such as the expressiveness of search queries and the effectiveness of result-filtering processes.

Original languageEnglish (US)
Pages (from-to)1176-1187
Number of pages12
JournalIEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
Volume39
Issue number6
DOIs
StatePublished - Nov 2009

Keywords

  • Human factors
  • Network interfaces
  • Search methods

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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