Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
An Efficient Boosting Algorithm for Combining Preferences
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Using temporal profiles of queries for precision prediction
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Personalizing search via automated analysis of interests and activities
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
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
A regression framework for learning ranking functions using relative relevance judgments
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Leveraging temporal dynamics of document content in relevance ranking
Proceedings of the third ACM international conference on Web search and data mining
Towards recency ranking in web search
Proceedings of the third ACM international conference on Web search and data mining
Learning recurrent event queries for web search
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Temporal query log profiling to improve web search ranking
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
An integrated approach for medical image retrieval through combining textual and visual features
CLEF'09 Proceedings of the 10th international conference on Cross-language evaluation forum: multimedia experiments
An extended vector space model for content-based image retrieval
CLEF'09 Proceedings of the 10th international conference on Cross-language evaluation forum: multimedia experiments
Understanding temporal query dynamics
Proceedings of the fourth ACM international conference on Web search and data mining
Expert Systems with Applications: An International Journal
Question temporality: identification and uses
Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work
Time-sensitive query auto-completion
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Learning-based time-sensitive re-ranking for web search
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Labeling documents with timestamps: learning from their time expressions
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Multi-session re-search: in pursuit of repetition and diversification
Proceedings of the 21st ACM international conference on Information and knowledge management
Survival analysis for freshness in microblogging search
Proceedings of the 21st ACM international conference on Information and knowledge management
Predicting event-relatedness of popular queries
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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We propose a new method to rank a special category of time-sensitive queries that are year qualified. The method adjusts the retrieval scores of a base ranking function according to time-stamps of web documents so that the freshest documents are ranked higher. Our method, which is based on feedback control theory, uses ranking errors to adjust the search engine behavior. For this purpose, we use a simple but effective method to extract year qualified queries by mining query logs and a time-stamp recognition method that considers titles and urls of web documents. Our method was tested on a commercial search engine. The experiments show that our approach can significantly improve relevance ranking for year qualified queries even if all the existing methods for comparison failed.