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NIPS
2004
15 years 29 days ago
Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms
In the context of binary classification, we define disagreement as a measure of how often two independently-trained models differ in their classification of unlabeled data. We exp...
Omid Madani, David M. Pennock, Gary William Flake
AAAI
2008
15 years 1 months ago
Semi-Supervised Learning for Blog Classification
Blog classification (e.g., identifying bloggers' gender or age) is one of the most interesting current problems in blog analysis. Although this problem is usually solved by a...
Daisuke Ikeda, Hiroya Takamura, Manabu Okumura
AAAI
2006
15 years 1 months ago
Automatically Labeling the Inputs and Outputs of Web Services
Information integration systems combine data from multiple heterogeneous Web services to answer complex user queries, provided a user has semantically modeled the service first. T...
Kristina Lerman, Anon Plangprasopchok, Craig A. Kn...
KDD
2009
ACM
237views Data Mining» more  KDD 2009»
16 years 4 days ago
Exploring social tagging graph for web object classification
This paper studies web object classification problem with the novel exploration of social tags. Automatically classifying web objects into manageable semantic categories has long ...
Zhijun Yin, Rui Li, Qiaozhu Mei, Jiawei Han
ICDM
2003
IEEE
220views Data Mining» more  ICDM 2003»
15 years 4 months ago
Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...