[1]LI Jiamin,LIU Xingbo,NIE Xiushan,et al.Triplet deep Hashing learning for judicial case similarity matching method[J].CAAI Transactions on Intelligent Systems,2020,15(6):1147-1153.[doi:10.11992/tis.202006049]
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Triplet deep Hashing learning for judicial case similarity matching method

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 15 Number of periods: 2020 6 Page number: 1147-1153 Column: 学术论文—机器感知与模式识别 Public date: 2020-11-05
Title:
Triplet deep Hashing learning for judicial case similarity matching method
Author(s):
LI Jiamin1;  LIU Xingbo1;  NIE Xiushan2;  GUO Jie1;  YIN Yilong1
1. School of Software, Shandong University, Ji’nan 250101, China;
2. School of Computer Science and Technology, Shandong Jianzhu University, Ji’nan 250101, China
Keywords:
judicial cases; case matching; similarity retrieval; Hashing learning; deep learning; neural network; BERT model; triples
CLC:
TP391
DOI:
10.11992/tis.202006049
Abstract:
Matching similar cases in a large number of judicial case documents can effectively improve the efficiency of the judicial department. However, the text of judicial cases is not only lengthy, but also exhibits a certain degree of structural complexity. Therefore, the text matching of judicial cases is more difficult compared with the traditional natural language processing tasks. To solve the above problems and challenges, this paper proposes a judicial case similar matching method based on the triplet deep Hashing learning model. First, a pre-trained BERT model is used to extract the features of the documents in groups. The triplet similarity relationship of the documents is then employed to train the deep neural network model to generate the Hashing code representation of the documents. Finally, the Hamming distance based on the Hashing code of the documents is used to determine whether they are similar cases. Experimental results show that the Hashing learning method greatly reduces the storage cost of the documents’ feature representations and improves the speed of similar case matching.
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