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» Distributional Clustering of Words for Text Classification
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NIPS
2008
13 years 8 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell
SYNASC
2007
IEEE
136views Algorithms» more  SYNASC 2007»
14 years 1 months ago
Wikipedia-Based Kernels for Text Categorization
In recent years several models have been proposed for text categorization. Within this, one of the widely applied models is the vector space model (VSM), where independence betwee...
Zsolt Minier, Zalan Bodo, Lehel Csató
ICTAI
2007
IEEE
14 years 1 months ago
Dragon Toolkit: Incorporating Auto-Learned Semantic Knowledge into Large-Scale Text Retrieval and Mining
The majority of text retrieval and mining techniques are still based on exact feature (e.g. words) matching and unable to incorporate text semantics. Many researchers believe that...
Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu
ECCV
2006
Springer
14 years 9 months ago
Scene Classification Via pLSA
Given a set of images of scenes containing multiple object categories (e.g. grass, roads, buildings) our objective is to discover these objects in each image in an unsupervised man...
Anna Bosch, Andrew Zisserman, Xavier Muñoz
WWW
2002
ACM
14 years 8 months ago
Using web structure for classifying and describing web pages
The structure of the web is increasingly being used to improve organization, search, and analysis of information on the web. For example, Google uses the text in citing documents ...
Eric J. Glover, Kostas Tsioutsiouliklis, Steve Law...