ICRC-HIT: A Deep Learning based Comment Sequence Labeling System for Answer Selection Challenge

Abstract

In this paper, we present a comment labeling system based on a deep learning strategy. We treat the answer selection task as a sequence labeling problem and propose recurrent convolution neural networks to recognize good comments. In the recurrent architecture of our system, our approach uses 2-dimensional convolutional neural networks to learn the distributed representation for question-comment pair, and assigns the labels to the comment sequence with a recurrent neural network over CNN. Compared with the conditional random fields based method, our approach performs better performance on Macro-F1 (53.82%), and achieves the highest accuracy (73.18%), F1-value (79.76%) on predicting the Good class in this answer selection challenge.