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» A measure theoretic approach to information retrieval
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ICML
2009
IEEE
16 years 7 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
EDBT
2009
ACM
96views Database» more  EDBT 2009»
16 years 29 days ago
Top-k dominant web services under multi-criteria matching
As we move from a Web of data to a Web of services, enhancing the capabilities of the current Web search engines with effective and efficient techniques for Web services retrieva...
Dimitrios Skoutas, Dimitris Sacharidis, Alkis Simi...
IPM
2007
156views more  IPM 2007»
15 years 6 months ago
p2pDating: Real life inspired semantic overlay networks for Web search
We consider a network of autonomous peers forming a logically global but physically distributed search engine, where every peer has its own local collection generated by independe...
Josiane Xavier Parreira, Sebastian Michel, Gerhard...
CIKM
2010
Springer
15 years 4 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
ETRA
2010
ACM
197views Biometrics» more  ETRA 2010»
16 years 1 months ago
Image ranking with implicit feedback from eye movements
In order to help users navigate an image search system, one could provide explicit information on a small set of images as to which of them are relevant or not to their task. Thes...
David R. Hardoon, Kitsuchart Pasupa