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» Sampling the Web as Training Data for Text Classification
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PR
2006
229views more  PR 2006»
15 years 2 months ago
FS_SFS: A novel feature selection method for support vector machines
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
Yi Liu, Yuan F. Zheng
179
Voted
VLSISP
2010
254views more  VLSISP 2010»
15 years 28 days ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
135
Voted
JMLR
2010
144views more  JMLR 2010»
14 years 9 months ago
Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Sándor Szedmák, Yizhao Ni, Steve R. ...
99
Voted
LREC
2010
141views Education» more  LREC 2010»
15 years 4 months ago
Building Textual Entailment Specialized Data Sets: a Methodology for Isolating Linguistic Phenomena Relevant to Inference
This paper proposes a methodology for the creation of specialized data sets for Textual Entailment, made of monothematic Text-Hypothesis pairs (i.e. pairs in which only one lingui...
Luisa Bentivogli, Elena Cabrio, Ido Dagan, Danilo ...
CHI
2008
ACM
15 years 4 months ago
Word usage and posting behaviors: modeling blogs with unobtrusive data collection methods
We present a large-scale analysis of the content of weblogs dating back to the release of the Blogger program in 1999. Over one million blogs were analyzed from their conception t...
Adam D. I. Kramer, Kerry Rodden