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» Maximum Margin Ranking Algorithms for Information Retrieval
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SIGIR
2010
ACM
13 years 7 months ago
Learning to rank query reformulations
Query reformulation techniques based on query logs have recently proven to be effective for web queries. However, when initial queries have reasonably good quality, these techniqu...
Van Dang, Michael Bendersky, W. Bruce Croft
CIKM
2007
Springer
14 years 1 months ago
Effective top-k computation in retrieving structured documents with term-proximity support
Modern web search engines are expected to return top-k results efficiently given a query. Although many dynamic index pruning strategies have been proposed for efficient top-k com...
Mingjie Zhu, Shuming Shi, Mingjing Li, Ji-Rong Wen
ECIR
2009
Springer
14 years 4 months ago
Joint Ranking for Multilingual Web Search
Ranking for multilingual information retrieval (MLIR) is a task to rank documents of different languages solely based on their relevancy to the query regardless of query’s langu...
Wei Gao, Cheng Niu, Ming Zhou, Kam-Fai Wong
CIKM
2010
Springer
13 years 6 months ago
Ranking related entities: components and analyses
Related entity finding is the task of returning a ranked list of homepages of relevant entities of a specified type that need to engage in a given relationship with a given sour...
Marc Bron, Krisztian Balog, Maarten de Rijke
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 3 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...