Gathering, Selecting and Preparing Unstructured Documents for Enterprise Information Extraction

Mahmoud Brahimi, Kehali Nor Elhouda
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Abstract

A large amount of unstructured documents exists on the web incorporating data of paramount importance for the enterprises that can employ them to synthesize the past, to comprehend the present and to predict the future. However, it is worth noting that the unstructured nature of these documents made the handling and the extraction of knowledge from them a very critical issue. The current contribution is three-fold. First, we collect the unstructured documents which might be useful using general enterprise ontology. Then, we select the most suitable ones using specific ontologies that describe partial enterprise activities. Finally, we transform the kept documents into parsabale and requestable XML files that can be the corpus for future data extraction.
面向企业信息提取的非结构化文档的收集、选择和准备
网络上存在着大量的非结构化文档,这些文档包含了对企业来说至关重要的数据,企业可以利用它们来综合过去、理解现在和预测未来。然而,值得注意的是,这些文件的非结构化性质使得处理和从中提取知识成为一个非常关键的问题。目前的贡献是三倍的。首先,我们收集了非结构化文档,这些文档可能对通用企业本体有用。然后,我们使用描述部分企业活动的特定本体选择最合适的本体。最后,我们将保留的文档转换为可解析和可请求的XML文件,这些文件可以作为将来数据提取的语料库。
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