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» Leveraging Active Learning for Relevance Feedback Using an I...
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SIGIR
2008
ACM
13 years 7 months ago
A bayesian logistic regression model for active relevance feedback
Relevance feedback, which traditionally uses the terms in the relevant documents to enrich the user's initial query, is an effective method for improving retrieval performanc...
Zuobing Xu, Ram Akella
CVPR
2008
IEEE
14 years 9 months ago
Semi-supervised SVM batch mode active learning for image retrieval
Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learni...
Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R....
SIGIR
2005
ACM
14 years 1 months ago
Personalizing search via automated analysis of interests and activities
We formulate and study search algorithms that consider a user’s prior interactions with a wide variety of content to personalize that user’s current Web search. Rather than re...
Jaime Teevan, Susan T. Dumais, Eric Horvitz
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
11 years 10 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
ICML
2003
IEEE
14 years 8 months ago
Exploration and Exploitation in Adaptive Filtering Based on Bayesian Active Learning
In the task of adaptive information filtering, a system receives a stream of documents but delivers only those that match a person's information need. As the system filters i...
Yi Zhang, Wei Xu, James P. Callan