Judgments recommendation method based on multi-modal feature fusion

YUAN Xu; HAN Xue-jiao; CHEN Zhi-kui; ZHONG Fang-ming; ZHAO Liang

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Judgments recommendation method based on multi-modal feature fusion

更新时间：2026-09-04

- Judgments recommendation method based on multi-modal feature fusion
- Vol. 37, Issue 12, Pages: 42-47(2020)
- 作者机构：
  
  1. 大连理工大学软件学院,辽宁,大连,116620
  2. 大连理工大学辽宁省泛在网络与服务软件重点实验室,辽宁,大连,116620
- 作者简介：
- 基金信息：
- DOI：
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- Published：2020
- 稿件说明：
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原旭, 韩雪姣, 陈志奎, 钟芳明, 赵亮. 多模态特征融合的裁判文书推荐方法[J]. 微电子学与计算机, 2020, 37(12): 42-47.

YUAN Xu, HAN Xue-jiao, CHEN Zhi-kui, et al. Judgments recommendation method based on multi-modal feature fusion[J]. 2020, 37(12): 42-47.
原旭, 韩雪姣, 陈志奎, 钟芳明, 赵亮. 多模态特征融合的裁判文书推荐方法[J]. 微电子学与计算机, 2020, 37(12): 42-47. DOI：

YUAN Xu, HAN Xue-jiao, CHEN Zhi-kui, et al. Judgments recommendation method based on multi-modal feature fusion[J]. 2020, 37(12): 42-47. DOI：

摘要

为了解决传统办案方式可能引起的“类案不同判”等问题

以及满足当事人查找预览与自身情况相似裁判文书的需求

本文提出了一种基于多模态特征融合的裁判文书推荐方法

学习高层次的裁判文书多模态融合特征表示

进而实现相似裁判文书推荐.该方法主要包括预处理、特征提取、特征融合和文书推荐四个阶段.实验结果表明

与只利用单一模态特征以及简单串联多模态特征的方法相比

利用本文方法学习到的多模态融合特征进行裁判文书推荐

推荐结果的准确率、召回率和综合评价指标(值)均有显著提高.说明本文提出的多模态特征融合方法对于推荐任务更加有效

体现了算法的优越性.

Abstract

In order to address the problems such as "different judgments in similar cases" caused by the traditional way of handling cases

and to satisfy the parties needs to search and preview the judgments which are similar to their own situation

this paper proposes a judgments recommendation method based on multi-modal feature fusion

which can learn high-level fusion feature representation from multiple modalities for the judgments. Then the judgments recommendation can be performed using the learned fusion feature. The proposed method consists of four stages

i.e.

data preprocessing

feature extraction

mult-modal feature fusion

and judgments recommendation. Extensive experiments demonstrate that

compared to the methods using only single-modal features and simple concatenation of multi-modal features

the multi-modal fusion features learned by our method achieves significant improvement in precision

recall

and F1 Value for judgments recommendation. It shows that the multi-modal feature fusion method proposed in this paper is effective for judgments recommendation.

关键词

Keywords

references

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CHUN N, FENG C S. Multi-intention recognition model with combination of syntactic feature and convolution neural network[J]. Journal of Computer Applications, 2018, 38(7):1839-1845+1852. DOI: 1839

JIA C, LIU H P, XU X Y, et al. Multi-modal information fusion based on broad learning method[J]. Transactions on Intelligent Systems, 2019, 14(1):150-157. DOI: 150

WANG N, HUANG X M, LIU Z Q, et al. Personalized Video Recommendation Strategy Bases on User's Playback Behavior Sequence[J]. Chinese Journal of Computer, 2020, 43(1):123-135. DOI: 123

CHEN Y, FU L, DAI Y X, et al. Research of Chinese resume analysis based on feature fusion[J]. Computer Engineering and Applications, 2019, 55(10):244-249. DOI: 244

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