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» Evaluating WordNet Features in Text Classification Models
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IS
2008
13 years 7 months ago
Mining relational data from text: From strictly supervised to weakly supervised learning
This paper approaches the relation classification problem in information extraction framework with different machine learning strategies, from strictly supervised to weakly superv...
Zhu Zhang
KDD
2009
ACM
269views Data Mining» more  KDD 2009»
14 years 8 months ago
Extracting discriminative concepts for domain adaptation in text mining
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
Bo Chen, Wai Lam, Ivor Tsang, Tak-Lam Wong
ICPR
2008
IEEE
14 years 8 months ago
Feature Fusion Hierarchies for gender classification
We present a hierarchical feature fusion model for image classification that is constructed by an evolutionary learning algorithm. The model has the ability to combine local patch...
Fabien Scalzo, George Bebis, Mircea Nicolescu, Lea...
EMNLP
2010
13 years 5 months ago
Negative Training Data Can be Harmful to Text Classification
This paper studies the effects of training data on binary text classification and postulates that negative training data is not needed and may even be harmful for the task. Tradit...
Xiaoli Li, Bing Liu, See-Kiong Ng
NAACL
2007
13 years 9 months ago
Combining Lexical and Grammatical Features to Improve Readability Measures for First and Second Language Texts
This work evaluates a system that uses interpolated predictions of reading difficulty that are based on both vocabulary and grammatical features. The combined approach is compared...
Michael Heilman, Kevyn Collins-Thompson, Jamie Cal...