Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Improving pseudo-relevance feedback in web information retrieval using web page segmentation
WWW '03 Proceedings of the 12th international conference on World Wide Web
Mining anchor text for query refinement
Proceedings of the 13th international conference on World Wide Web
The NRRC reliable information access (RIA) workshop
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
The TREC robust retrieval track
ACM SIGIR Forum
An improved error model for noisy channel spelling correction
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Queries as anchors: selection by association
Proceedings of the sixteenth ACM conference on Hypertext and hypermedia
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Using annotations in enterprise search
Proceedings of the 15th international conference on World Wide Web
On GMAP: and other transformations
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Random walks on the click graph
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Retrieval and feedback models for blog feed search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
A unified and discriminative model for query refinement
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Query dependent pseudo-relevance feedback based on wikipedia
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Reducing the risk of query expansion via robust constrained optimization
Proceedings of the 18th ACM conference on Information and knowledge management
Query reformulation using anchor text
Proceedings of the third ACM international conference on Web search and data mining
Exploring web scale language models for search query processing
Proceedings of the 19th international conference on World wide web
On the choice of effectiveness measures for learning to rank
Information Retrieval
Modeling reformulation using passage analysis
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
In The Plex: How Google Thinks, Works, and Shapes Our Lives
In The Plex: How Google Thinks, Works, and Shapes Our Lives
Parameterized concept weighting in verbose queries
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Synthesizing high utility suggestions for rare web search queries
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Effective query formulation with multiple information sources
Proceedings of the fifth ACM international conference on Web search and data mining
Predicting the impact of expansion terms using semantic and user interaction features
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Query rewriting algorithms can be used as a form of query expansion, by combining the user's original query with automatically generated rewrites. Rewriting algorithms bring linguistic datasets to bear without the need for iterative relevance feedback, but most studies of rewriting have used proprietary datasets such as large-scale search logs. By contrast this paper uses readily available data, particularly ClueWeb09 link text with over 1.2 billion anchor phrases, to generate rewrites. To avoid overfitting, our initial analysis is performed using Million Query Track queries, leading us to identify three algorithms which perform well. We then test the algorithms on Web and newswire data. Results show good properties in terms of robustness and early precision.