Searching distributed collections with inference networks
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Finding information on the World Wide Web: the retrieval effectiveness of search engines
Information Processing and Management: an International Journal
User interactions with everyday applications as context for just-in-time information access
Proceedings of the 5th international conference on Intelligent user interfaces
IR evaluation methods for retrieving highly relevant documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Why batch and user evaluations do not give the same results
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Approaches to collection selection and results merging for distributed information retrieval
Proceedings of the tenth international conference on Information and knowledge management
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Measuring Search Engine Quality
Information Retrieval
A semisupervised learning method to merge search engine results
ACM Transactions on Information Systems (TOIS)
Learning and reasoning about interruption
Proceedings of the 5th international conference on Multimodal interfaces
Competition between Internet Search Engines
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 8 - Volume 8
A diary study of task switching and interruptions
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
An analysis of search engine switching behavior using click streams
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Investigating behavioral variability in web search
Proceedings of the 16th international conference on World Wide Web
Web projections: learning from contextual subgraphs of the web
Proceedings of the 16th international conference on World Wide Web
Mining longest repeating subsequences to predict world wide web surfing
USITS'99 Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2
The influence of caption features on clickthrough patterns in web search
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Defection detection: predicting search engine switching
Proceedings of the 17th international conference on World Wide Web
Characterizing and predicting search engine switching behavior
Proceedings of the 18th ACM conference on Information and knowledge management
Why searchers switch: understanding and predicting engine switching rationales
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
A Specialized Search Assistant for Learning Objects
ACM Transactions on the Web (TWEB)
Effects of search success on search engine re-use
Proceedings of the 20th ACM international conference on Information and knowledge management
Modeling long-term search engine usage
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
Slow Search: Information Retrieval without Time Constraints
Proceedings of the Symposium on Human-Computer Interaction and Information Retrieval
Multimedia search reranking: A literature survey
ACM Computing Surveys (CSUR)
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Any given Web search engine may provide higher quality results than others for certain queries. Therefore, it is in users' best interest to utilize multiple search engines. In this paper, we propose and evaluate a framework that maximizes users' search effective-ness by directing them to the engine that yields the best results for the current query. In contrast to prior work on meta-search, we do not advocate for replacement of multiple engines with an aggregate one, but rather facilitate simultaneous use of individual engines. We describe a machine learning approach to supporting switching between search engines and demonstrate its viability at tolerable interruption levels. Our findings have implications for fluid competition between search engines.