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» Swarming to rank for information retrieval
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IR
2011
13 years 4 months ago
Learning to rank for why-question answering
In this paper, we evaluate a number of machine learning techniques for the task of ranking answers to why-questions. We use TF-IDF together with a set of 36 linguistically motivate...
Suzan Verberne, Hans van Halteren, Daphne Theijsse...
ISBRA
2011
Springer
13 years 17 days ago
Query-Adaptive Ranking with Support Vector Machines for Protein Homology Prediction
Abstract. Protein homology prediction is a crucial step in templatebased protein structure prediction. The functions that rank the proteins in a database according to their homolog...
Yan Fu, Rong Pan, Qiang Yang, Wen Gao
CIKM
2009
Springer
14 years 1 months ago
Empirical justification of the gain and discount function for nDCG
The nDCG measure has proven to be a popular measure of retrieval effectiveness utilizing graded relevance judgments. However, a number of different instantiations of nDCG exist, d...
Evangelos Kanoulas, Javed A. Aslam
WSDM
2010
ACM
210views Data Mining» more  WSDM 2010»
14 years 6 months ago
Leveraging Temporal Dynamics of Document Content in Relevance Ranking
Many web documents are dynamic, with content changing in varying amounts at varying frequencies. However, current document search algorithms have a static view of the document con...
Jonathan L. Elsas, Susan T. Dumais
WWW
2010
ACM
14 years 4 months ago
SourceRank: relevance and trust assessment for deep web sources based on inter-source agreement
We consider the problem of deep web source selection and argue that existing source selection methods are inadequate as they are based on local similarity assessment. Specificall...
Raju Balakrishnan, Subbarao Kambhampati