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» Learning Ranking vs. Modeling Relevance
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ICML
2009
IEEE
14 years 8 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
EMNLP
2010
13 years 5 months ago
Learning the Relative Usefulness of Questions in Community QA
We present a machine learning approach for the task of ranking previously answered questions in a question repository with respect to their relevance to a new, unanswered referenc...
Razvan C. Bunescu, Yunfeng Huang
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
WWW
2009
ACM
14 years 8 months ago
A dynamic bayesian network click model for web search ranking
As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of relevance assessments made by editors. Click logs can...
Olivier Chapelle, Ya Zhang
WSDM
2010
ACM
242views Data Mining» more  WSDM 2010»
14 years 4 months ago
Improving Ad Relevance in Sponsored Search
We describe a machine learning approach for predicting sponsored search ad relevance. Our baseline model incorporates basic features of text overlap and we then extend the model t...
Dustin Hillard, Stefan Schroedl, Eren Manavoglu, H...