面向随案电子卷宗的知识森林自动构建方法

Automatic construction method of knowledge forest for electronic case files

针对阅卷时由于卷宗内容繁多导致的信息过载和知识迷航的问题,提出面向随案电子卷宗的知识森林自动构建方法,以主题分面树以及主题间的认知关系作为卷宗的知识化表示。首先,对卷宗进行碎片化的预处理,从而将不同类型的文书分类并划分为多个单一主题的碎片;然后,针对不同碎片采取不同的信息抽取方法,并利用知识融合将同义信息进行合并,之后利用本体结构和规则构建主题分面树并抽取主题关系;最后,将知识森林构建的主题分面树和主题关系在数据库中存储起来,从而实现知识森林的可视化。实验结果表明,该方法可以较为完整、准确地展示卷宗信息,组织分散的知识碎片和复杂的卷宗主题,使得选择部分卷宗主题和少量卷宗碎片实现阅卷目标成为可能,减轻了通过全面浏览卷宗内容来完成阅卷任务的负担。

The read of various contents of case files suffers from information overload and knowledge disorientation.To solve this problem,an automatic construction method of knowledge forest for electronic case files was proposed with the topic facet trees and the cognitive relationships between topics as the intellectualized representation of the case files.Firstly,different types of files were classified and divided into multiple fragments of single topic by the fragmentation preprocessing of the case files.Then,different information extraction methods were adopted for different fragments,and knowledge fusion was used to merge the synonymous information.After that,the topic faceted trees were constructed by combining the ontology structures and rules and the topic relationships were extracted.Finally,the topic faceted trees and the topic relationships constructed by the knowledge forest were stored in the database to realize the visualization of the knowledge forest.Experimental results show that the proposed method can display the case file information completely and accurately,organize scattered knowledge fragments together with complex case file topics,making it possible to achieve the reading file goal by selecting some case file topics and a small number of case file fragments,and alleviate the burden of complete browsing case file contents to realize the file reading task.