ACM Transactions on Information Systems (TOIS): Volume 30 Issue 4, November 2012
Citation Count: 5
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Traditional machine-learned ranking systems for Web search are often trained to capture stationary relevance of documents to queries, which have limited ability to track nonstationary user intention in a timely manner. In recency search, for instance, the relevance of documents to a query on breaking news often changes significantly over ...