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» Learning to Select a Ranking Function
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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...
ICML
2004
IEEE
14 years 1 months ago
Active learning of label ranking functions
The effort necessary to construct labeled sets of examples in a supervised learning scenario is often disregarded, though in many applications, it is a time-consuming and expensi...
Klaus Brinker
SIGMOD
2007
ACM
181views Database» more  SIGMOD 2007»
14 years 8 months ago
Progressive and selective merge: computing top-k with ad-hoc ranking functions
The family of threshold algorithm (i.e., TA) has been widely studied for efficiently computing top-k queries. TA uses a sort-merge framework that assumes data lists are pre-sorted...
Dong Xin, Jiawei Han, Kevin Chen-Chuan Chang
PKDD
2004
Springer
155views Data Mining» more  PKDD 2004»
14 years 1 months ago
Ensemble Feature Ranking
A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Sele...
Kees Jong, Jérémie Mary, Antoine Cor...
WSDM
2012
ACM
214views Data Mining» more  WSDM 2012»
12 years 3 months ago
Selecting actions for resource-bounded information extraction using reinforcement learning
Given a database with missing or uncertain content, our goal is to correct and fill the database by extracting specific information from a large corpus such as the Web, and to d...
Pallika H. Kanani, Andrew K. McCallum