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» Adapting ranking SVM to document retrieval
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ISBRA
2011
Springer
12 years 11 months 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 2 months ago
Enabling multi-level relevance feedback on pubmed by integrating rank learning into DBMS
Background: Finding relevant articles from PubMed is challenging because it is hard to express the user’s specific intention in the given query interface, and a keyword query ty...
Hwanjo Yu, Taehoon Kim, Jinoh Oh, Ilhwan Ko, Sungc...
WWW
2007
ACM
14 years 8 months ago
Extraction and search of chemical formulae in text documents on the web
Often scientists seek to search for articles on the Web related to a particular chemical. When a scientist searches for a chemical formula using a search engine today, she gets ar...
Bingjun Sun, Qingzhao Tan, Prasenjit Mitra, C. Lee...
ECIR
2007
Springer
13 years 9 months ago
A Bayesian Approach for Learning Document Type Relevance
Retrieval accuracy can be improved by considering which document type should be filtered out and which should be ranked higher in the result list. Hence, document type can be used...
Peter C. K. Yeung, Stefan Büttcher, Charles L...
WWW
2008
ACM
14 years 8 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...