从银行文件中提取复杂关系

Berke Oral, Erdem Emekligil, S. Arslan, Gülşen Eryiğit
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引用次数: 7

摘要

为了自动化银行流程(例如支付、汇款、对外贸易),我们需要从不同类型的媒介(如传真、电子邮件和扫描仪)中提取银行交易。与关系提取研究中使用的传统数据集相比,银行订单可能被认为是复杂的文档,因为它们包含相当复杂的关系。本文提出了从银行订单中提取间隔关系、嵌套关系和复杂关系的方法,并介绍了一种基于极大团分解技术的关系提取方法。我们证明,与以前的方法相比,误差降低了11%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extracting Complex Relations from Banking Documents
In order to automate banking processes (e.g. payments, money transfers, foreign trade), we need to extract banking transactions from different types of mediums such as faxes, e-mails, and scanners. Banking orders may be considered as complex documents since they contain quite complex relations compared to traditional datasets used in relation extraction research. In this paper, we present our method to extract intersentential, nested and complex relations from banking orders, and introduce a relation extraction method based on maximal clique factorization technique. We demonstrate 11% error reduction over previous methods.
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