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一种结合关系增强融合模型的舆情关系抽取方法OA

A Method of Public Opinion Relation Extraction Combined With Relationship Enhanced Fusion Model

中文摘要英文摘要

针对舆情信息关系种类繁多、状态空间巨大,以及舆情信息关系抽取任务中出现的关系重叠和单一模型不能完全识别出全部三元组的问题,提出一种结合关系增强的融合模型进行舆情关系抽取的方法.首先,对从中文互联网上获取的舆情信息进行初步处理,得到初步的关系表;其次,对获得的关系表引入实体类型进行关系表增强;最后,将增强关系表作为先验特征输入融合模型,提升关系分类准确性,结合两个模型的识别结果解决单一模型不能完全识别出全部三元组的问题.实验结果表明,该方法相较于单一未使用关系增强的模型,F1值提升了5.4%.

Aiming at the problems of various types of public opinion information relations and huge state space,and the problems of relation-ship overlap and single model can not completely identify all triples in the relationship extraction task of public opinion information,a method of public opinion relation extraction based on relationship enhancement fusion model was proposed.First,the public opinion information ob-tained from the Chinese Internet is preliminarily processed to obtain a preliminary relationship table;Then,entity types are introduced to en-hance the relationship table obtained;Finally,the enhanced relationship table is input into the fusion model as a priori feature to improve the accuracy of relationship classification.Combining the recognition results of the two models,the problem that a single model cannot fully recog-nize all triples is solved.The experimental results indicate that,compared with the single model without relationship enhancement,the F1 val-ue of this method is increased by 5.4%.

夏益昆;赵春一

沈阳理工大学 信息科学与工程学院,辽宁 沈阳 110159中国科学院沈阳计算技术研究所,辽宁 沈阳 110000

计算机与自动化

关系抽取关系表增强模型融合全局指针网络舆情分析

relation extractionrelational schema enhancementmodel fusionglobal pointer networkpublic opinion analysis

《软件导刊》 2024 (006)

67-74 / 8

10.11907/rjdk.231543

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