Text Classification: A Sequential Reading Approach

Details Text Classification: A Sequential Reading Approach Text Classification: A Sequential Reading Approach

2011-07-07

arxiv.org/abs/1107.1322v3

Lecture Notes in Computer Science, 2011, Volume 6611/2011, 411-423

Computer Science

Artificial Intelligence

ECIR2011

Scientific paper

10.1007/978-3-642-20161-5_41

We propose to model the text classification process as a sequential decision process. In this process, an agent learns to classify documents into topics while reading the document sentences sequentially and learns to stop as soon as enough information was read for deciding. The proposed algorithm is based on a modelisation of Text Classification as a Markov Decision Process and learns by using Reinforcement Learning. Experiments on four different classical mono-label corpora show that the proposed approach performs comparably to classical SVM approaches for large training sets, and better for small training sets. In addition, the model automatically adapts its reading process to the quantity of training information provided.

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