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» Coupled Semi-Supervised Learning for Information Extraction
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ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
14 years 5 days ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...
COLING
2008
13 years 7 months ago
Homotopy-Based Semi-Supervised Hidden Markov Models for Sequence Labeling
This paper explores the use of the homotopy method for training a semi-supervised Hidden Markov Model (HMM) used for sequence labeling. We provide a novel polynomial-time algorith...
Gholamreza Haffari, Anoop Sarkar
ECIR
1998
Springer
13 years 6 months ago
Coupled Hierarchical IR and Stochastic Models for Surface Information Extraction
We present in this paper a combination of Machine Learning based Information Retrieval (IR) techniques and stochastic language modelling in a hierarchical system that extracts sur...
Hugo Zaragoza, Patrick Gallinari
CIKM
2006
Springer
13 years 9 months ago
Coupling feature selection and machine learning methods for navigational query identification
It is important yet hard to identify navigational queries in Web search due to a lack of sufficient information in Web queries, which are typically very short. In this paper we st...
Yumao Lu, Fuchun Peng, Xin Li, Nawaaz Ahmed
CVPR
2012
IEEE
11 years 8 months ago
We are not contortionists: Coupled adaptive learning for head and body orientation estimation in surveillance video
In this paper, we deal with the estimation of body and head poses (i.e orientations) in surveillance videos, and we make three main contributions. First, we address this issue as ...
Cheng Chen, Jean-Marc Odobez