Predicting query difficulty on the web by learning visual clues

SIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2005, Pages 615-616

  Jensen, Eric C ^a   Beitzel, Steven M ^a   Grossman, David ^a   Frieder, Ophir ^a   Chowdhury, Abdur ^b  

^a ILLINOIS INSTITUTE OF TECHNOLOGY   (United States)

^b America Online Inc   (United States)

Author keywords

query difficulty; web search

Indexed keywords

DOCUMENT REPRESENTATION; ENGINE PERFORMANCE; MAXIMUM CORRELATIONS; QUERY DIFFICULTY; RELEVANCE JUDGMENT; RETRIEVAL EFFECTIVENESS; SUPERVISED MACHINE LEARNING; WEB SEARCHES;

FORECASTING; SEARCH ENGINES; WEBSITES;

INFORMATION RETRIEVAL;

EID: 84455201514     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1076034.1076155     Document Type: Conference Paper

References (3)

1. E. C. Jensen, et al. A Framework for Determining Necessary Query Set Sizes to Evaluate Web Search Effectiveness. In Proceedings of WWW'05.
2. S. Cronen-Townsend, et al. Predicting Query Performance. In Proceedings of SIGIR'02.
3. B. He and I. Ounis. Inferring Query Performance Using Pre-Retrieval Predictors. In Proceedings of SPIRE'04.