Skip to content
akaturk Academic measurement

Article detail · 2010

Expected browsing utility for web search evaluation

OpenAlex Citations 90 Top 10% Percentile 96.9% FWCI 6.13
Year
2010
Type
conference-paper

Data source split

  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

Most information retrieval evaluation metrics are designed to measure the satisfaction of the user given the results returned by a search engine. In order to evaluate user satisfaction, most of these metrics have underlying user models, which aim at modeling how users interact with search engine results. Hence, the quality of an evaluation metric is a direct function of the quality of its underlying user model. This paper proposes EBU, a new evaluation metric that uses a sophisticated user model tuned by observations over many thousands of real search sessions. We compare EBU with a number of state of the art evaluation metrics and show that it is more correlated with real user behavior captured by clicks.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

90 citations

OpenAlex cited_by_count (cache / database)

6 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).

  1. Simulating simple user behavior for system effectiveness evaluation 2011 Citations 72 · OpenAlex
  2. Incorporating variability in user behavior into systems based evaluation 2012 Citations 29 · OpenAlex
  3. Report on the SIGIR 2013 workshop on modeling user behavior for information retrieval evaluation (MUBE 2013) 2013 Citations 11 · OpenAlex
  4. Chapter 5 Evaluating Web Retrieval Effectiveness 2012 Citations 6 · OpenAlex
  5. IR Evaluation 2015 Citations 3 · OpenAlex
  6. IR Evaluation 2015 Citations 1 · OpenAlex

Authors

No author information.