BI-style relation discovery among entities in text

Wojciech M. Barczynski, Falk Brauer, Adrian Mocan, M. Schramm, Jan Froemberg
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引用次数: 2

Abstract

Business Intelligence (BI) over unstructured text is under intense scrutiny both in industry and research. Recent work in this field includes automatic integration of unstructured text into BI systems, model recognition, and probabilistic databases to handle uncertainty of Information Extraction (IE) results. Our aim is to use analytics to discover statistically relevant and unknown relationship between entities in documents' fragments. We present a method for transforming IE results to an OLAP model and we demonstrate it in a real world scenario for the SAP Community Network.
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文本中实体之间bi风格的关系发现
非结构化文本的商业智能(BI)在工业界和研究领域都受到了严格的审查。该领域最近的工作包括将非结构化文本自动集成到BI系统、模型识别和概率数据库中以处理信息提取(IE)结果的不确定性。我们的目标是使用分析来发现文档片段中实体之间的统计相关和未知关系。我们提出了一种将IE结果转换为OLAP模型的方法,并在SAP社区网络的实际场景中进行了演示。
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