Chinese Questions Classification in the Law Domain
Authors:
- Guangyi XiaoGXGuangyi Xiao
- Even ChowECEven Chow
- Hao ChenHCHao Chen
- Jiqian MoJMJiqian Mo
- Jingzhi GuoJGJingzhi Guo
- Zhiguo GongZGZhiguo Gong
- 1 November 2017
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 214-219
Abstract
Question classification is an essential part of Question Answering system(QA). This paper introduces our research work on automatic question classification that depends on the sample set including questions from legal forum. We propose a taxonomy for law question, and divide questions into three main parts: civil, criminal and administrative according to Chinese legal system. We have experimented with four machine learning algorithms: Nearest Neighbors (NN), Name Bayes (NB), Logistic Regression (LR) and Support Vector Machines (SVM) using two kinds of features: TF-IDF and word2vec embeddings. Further, we used fastText and adjusted the parameters to get the better results. The research shows high accuracy in Chinese question classification in law domain. Moreover, to the best of our knowledge, our work is the first attempt in this promising domain.Keywords
This publication has 6 references indexed in Scilit:
- Question Answering over Freebase with Multi-Column Convolutional Neural Networks2015
- Question classification based on co-training style semi-supervised learningPattern Recognition Letters, 2010
- Feature Extraction for Learning to Classify Questions2004
- Learning question classifiers2002
- A re-examination of text categorization methods1999
- The Regression Analysis of Binary SequencesJournal of the Royal Statistical Society Series B: Statistical Methodology, 1959