基于依赖解析器的SBVR格式业务规则挖掘开放信息提取

Chandan Prakash, Pavan Kumar Chittimalli, Ravindra Naik
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引用次数: 3

摘要

业务规则存在于任何业务组织的核心。为了有效地执行业务系统,所有业务规则必须采用机器可解释的格式。目前还没有这样的系统可以自动将业务规则语句转换为相应的结构化格式。我们提出了BRMiner,这是一个系统,可以自动将表示为自然语言句子的业务规则转换为相应的SBVR格式,SBVR格式是一种结构化表示,可以进一步转换为机器可解释的格式。BRMiner基于开放信息提取(OIE)的思想。我们已经证明,现有的OIE系统不适合SBVR规则的形成,这导致了新的OIE系统BRMiner的开发,具有更准确的预测和额外的功能。BRMiner使用最先进的依赖解析器将非结构化业务规则转换为相应的结构化格式。我们使用内部和公开可用的数据集进行系统评估,结果令人鼓舞,我们在论文中展示了这一点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Open Information Extraction Using Dependency Parser for Business Rule Mining in SBVR Format
Business Rules exists at the core of any Business Organization. For efficient execution of the business system, all the business rules must be in machine-interpretable format. There is an absence of such a system that can convert the business rule sentences into corresponding structured format automatically. We present BRMiner, a system which automatically converts business rules represented as Natural Language sentences to the corresponding SBVR format which is a structured representation that can be further converted to the machine-interpretable format. BRMiner is based on the idea of Open Information Extraction (OIE). We have shown that existing OIE systems are not suitable for SBVR rule formation that leads to the development of a new OIE system BRMiner, with more accurate prediction and additional capabilities. BRMiner uses the state of the art dependency parser to convert an unstructured business rule to the corresponding structured format. We have used internal as well as publically available datasets for our system evaluation and the results are encouraging which we have shown in the paper.
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