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SDM
2011
SIAM
269views Data Mining» more  SDM 2011»
14 years 9 days ago
Semi-Supervised Convolution Graph Kernels for Relation Extraction
Extracting semantic relations between entities is an important step towards automatic text understanding. In this paper, we propose a novel Semi-supervised Convolution Graph Kerne...
Xia Ning, Yanjun Qi
94
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ACL
2012
12 years 12 months ago
Aspect Extraction through Semi-Supervised Modeling
Aspect extraction is a central problem in sentiment analysis. Current methods either extract aspects without categorizing them, or extract and categorize them using unsupervised t...
Arjun Mukherjee, Bing Liu 0001
COLING
2008
14 years 11 months ago
Extractive Summarization Using Supervised and Semi-Supervised Learning
It is difficult to identify sentence importance from a single point of view. In this paper, we propose a learning-based approach to combine various sentence features. They are cat...
Kam-Fai Wong, Mingli Wu, Wenjie Li
ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
15 years 4 months 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 ...
ACL
2008
14 years 11 months ago
Inducing Gazetteers for Named Entity Recognition by Large-Scale Clustering of Dependency Relations
We propose using large-scale clustering of dependency relations between verbs and multiword nouns (MNs) to construct a gazetteer for named entity recognition (NER). Since dependen...
Jun'ichi Kazama, Kentaro Torisawa