Learning features through feedback for blog distillation

Dehong Gao, Renxian Zhang, Wenjie Li, Raymond Yiu-Keung Lau, Kam-Fai Wong

Abstract: The paper is focused on blogosphere research based on the TREC blog distillation task, and aims to explore unbiased and significant features automatically and efficiently. Feedback from faceted feeds is introduced to harvest relevant features and information gain is used to select discriminative features. The evaluation result shows that the selected feedback features can greatly improve the performance and adapt well to the terabyte data.