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ACL
2009
15 years 4 hour ago
Predicting Barge-in Utterance Errors by using Implicitly-Supervised ASR Accuracy and Barge-in Rate per User
Modeling of individual users is a promising way of improving the performance of spoken dialogue systems deployed for the general public and utilized repeatedly. We define "im...
Kazunori Komatani, Alexander I. Rudnicky
132
Voted
AAAI
2008
15 years 4 months ago
Turning Web Text and Search Queries into Factual Knowledge: Hierarchical Class Attribute Extraction
A seed-based framework for textual information extraction allows for weakly supervised acquisition of open-domain class attributes over conceptual hierarchies, from a combination ...
Marius Pasca
102
Voted
IAT
2010
IEEE
15 years 4 days ago
Semi-supervised Learning for Opinion Detection
Research on opinion detection has shown that a large number of opinion-labeled data are necessary for capturing subtle opinions. However, opinion-labeled data, especially at the su...
Ning Yu, Sandra Kübler
129
Voted
KDD
2009
ACM
205views Data Mining» more  KDD 2009»
15 years 9 months ago
From active towards InterActive learning: using consideration information to improve labeling correctness
Data mining techniques have become central to many applications. Most of those applications rely on so called supervised learning algorithms, which learn from given examples in th...
Abraham Bernstein, Jiwen Li
ICML
2010
IEEE
15 years 3 months ago
Structured Output Learning with Indirect Supervision
We present a novel approach for structure prediction that addresses the difficulty of obtaining labeled structures for training. We observe that structured output problems often h...
Ming-Wei Chang, Vivek Srikumar, Dan Goldwasser, Da...