An Efficient Approach to Learning Chinese Judgment Document Similarity Based on Knowledge Summarization

TL;DR

This paper introduces a knowledge block summarization method utilizing domain ontologies and WMD to improve the accuracy and efficiency of Chinese judgment document similarity computation.

Contribution

It proposes a novel knowledge block summarization approach combined with WMD for better semantic similarity measurement of Chinese legal documents.

Findings

Higher accuracy in similarity detection

Faster computation speed

Effective use of domain ontologies

Abstract

A previous similar case in common law systems can be used as a reference with respect to the current case such that identical situations can be treated similarly in every case. However, current approaches for judgment document similarity computation failed to capture the core semantics of judgment documents and therefore suffer from lower accuracy and higher computation complexity. In this paper, a knowledge block summarization based machine learning approach is proposed to compute the semantic similarity of Chinese judgment documents. By utilizing domain ontologies for judgment documents, the core semantics of Chinese judgment documents is summarized based on knowledge blocks. Then the WMD algorithm is used to calculate the similarity between knowledge blocks. At last, the related experiments were made to illustrate that our approach is very effective and efficient in achieving higher accuracy and faster computation speed in comparison with the traditional approaches.