Paper Info
Title
Automated evaluation of search engine performance via implicit user feedback
Abstract
Measuring the information retrieval effectiveness of Web search engines can be expensive if human relevance judgments are required to evaluate search results. Using implicit user feedback for search engine evaluation provides a cost and time effective manner of addressing this problem. Web search engines can use human evaluation of search results without the expense of human evaluators. An additional advantage of this approach is the availability of real time data regarding system performance. Wecapture user relevance judgments actions such as print, save and bookmark, sending these actions and the corresponding document identifiers to a central server via a client application. We use this implicit feedback to calculate performance metrics, such as precision. We can calculate an overall system performance metric based on a collection of weighted metrics.
Year
DOI
Venue
2005
10.1145/1076034.1076172
SIGIR
Keywords
Field
DocType
automated evaluation,search engine evaluation,wecapture user relevance judgment,search engine performance,implicit user feedback,system performance,web search engine,human evaluation,human evaluator,performance metrics,overall system performance,human relevance judgment,search result,real time data,information retrieval,search engine
Data mining,Metasearch engine,Search engine,Information retrieval,Real-time data,Identifier,Computer science,Performance metric,Search engine indexing,Search analytics
Conference
ISBN
Citations 
PageRank 
1-59593-034-5
14
0.64
References 
Authors
4
2
Name
Order
Citations
PageRank
Himanshu Sharma1202.58
Bernard J. Jansen24753394.06