Semi-supervised ensemble ranking
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance by combining the outputs from multiple ranking algorithms. Many ensemble ranking approaches employ supervised learning tec...
Saved in:
Main Authors: | HOI, Steven C. H., JIN, Rong |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2008
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/2377 https://ink.library.smu.edu.sg/context/sis_research/article/3377/viewcontent/AAAI08SSER.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Learning Bregman Distance Functions and its Application for Semi-Supervised Clustering
by: WU, Lei, et al.
Published: (2009) -
Multiview semi-supervised learning with consensus
by: LI, Guangxia, et al.
Published: (2012) -
Group-based Relevance Feedback with Support Vector Machine Ensembles
by: HOI, Steven C. H., et al.
Published: (2004) -
A Semi-Supervised Active Learning Framework for Image Retrieval
by: HOI, Steven, et al.
Published: (2005) -
Semi-supervised SVM batch mode active learning for image retrieval
by: HOI, Steven, et al.
Published: (2008)