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ACL
2011
14 years 1 months ago
Semi-supervised latent variable models for sentence-level sentiment analysis
We derive two variants of a semi-supervised model for fine-grained sentiment analysis. Both models leverage abundant natural supervision in the form of review ratings, as well as...
Oscar Täckström, Ryan T. McDonald
ICDAR
2011
IEEE
13 years 9 months ago
Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning
—Reading text from photographs is a challenging problem that has received a signicant amount of attention. Two key components of most systems are (i) text detection from images a...
Adam Coates, Blake Carpenter, Carl Case, Sanjeev S...
88
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EEE
2005
IEEE
15 years 3 months ago
Learning the Kernel Matrix for XML Document Clustering
The rapid growth of XML adoption has urged for the need of a proper representation for semi-structured documents, where the document structural information has to be taken into ac...
Jianwu Yang, William Kwok-Wai Cheung, Xiaoou Chen
KDD
2008
ACM
244views Data Mining» more  KDD 2008»
15 years 10 months ago
Probabilistic latent semantic visualization: topic model for visualizing documents
We propose a visualization method based on a topic model for discrete data such as documents. Unlike conventional visualization methods based on pairwise distances such as multi-d...
Tomoharu Iwata, Takeshi Yamada, Naonori Ueda
ACL
2012
12 years 12 months ago
Fine Granular Aspect Analysis using Latent Structural Models
In this paper, we present a structural learning model for joint sentiment classification and aspect analysis of text at various levels of granularity. Our model aims to identify ...
Lei Fang, Minlie Huang