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This paper presents a study of employing Ranking SVM and Convolutional NeuralNetwork for two missions: legal information retrieval and question answering inthe Competition on Legal Information Extraction/Entailment. For the first task,our proposed model used a triple of features (LSI, Manhattan, Jaccard), and isbased on paragraph level instead of article level as in previous studies. Infact, each single-paragraph article corresponds to a particular paragraph in ahuge multiple-paragraph article. For the legal question answering task,additional statistical features from information retrieval task integrated intoConvolutional Neural Network contribute to higher accuracy.

Legal Question Answering using Ranking SVM and Deep Convolutional Neural Network