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» Learning from Labeled and Unlabeled Data Using Random Walks
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EMNLP
2009
13 years 5 months ago
Predicting Subjectivity in Multimodal Conversations
In this research we aim to detect subjective sentences in multimodal conversations. We introduce a novel technique wherein subjective patterns are learned from both labeled and un...
Gabriel Murray, Giuseppe Carenini
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 8 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
NIPS
2008
13 years 9 months ago
Multi-Level Active Prediction of Useful Image Annotations for Recognition
We introduce a framework for actively learning visual categories from a mixture of weakly and strongly labeled image examples. We propose to allow the categorylearner to strategic...
Sudheendra Vijayanarasimhan, Kristen Grauman
IJCAI
2003
13 years 9 months ago
Integrating Background Knowledge Into Text Classification
We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of tra...
Sarah Zelikovitz, Haym Hirsh
KDD
2006
ACM
162views Data Mining» more  KDD 2006»
14 years 8 months ago
Simultaneous record detection and attribute labeling in web data extraction
Recent work has shown the feasibility and promise of templateindependent Web data extraction. However, existing approaches use decoupled strategies ? attempting to do data record ...
Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, Wei-Y...