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» Using User Models in Music Information Retrieval Systems
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171
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SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
13 years 5 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
CIKM
2009
Springer
15 years 10 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...
155
Voted
BMCBI
2008
116views more  BMCBI 2008»
15 years 3 months ago
Gene Ontology annotations: what they mean and where they come from
To address the challenges of information integration and retrieval, the computational genomics community increasingly has come to rely on the methodology of creating annotations o...
David P. Hill, Barry Smith, Monica S. McAndrews-Hi...
106
Voted
JSW
2007
116views more  JSW 2007»
15 years 3 months ago
Security Patterns for Voice over IP Networks
—Voice over IP (VoIP) has had a strong effect on global communications by allowing human voice and fax information to travel over existing packet data networks along with traditi...
Eduardo B. Fernández, Juan C. Pelaez, Mar&i...
175
Voted
SAC
2008
ACM
15 years 3 months ago
Towards automatic feature vector optimization for multimedia applications
We systematically evaluate a recently proposed method for unsupervised discrimination power analysis for feature selection and optimization in multimedia applications. A series of...
Tobias Schreck, Dieter W. Fellner, Daniel A. Keim