Combining Advanced Information Retrieval and Text-Mining for Digital Humanities

Antoine Widlöcher, Nicolas Béchet, Jean-Marc Lecarpentier, Yann Mathet, Julia Roger
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引用次数: 4

Abstract

Digital Humanities make more and more structured and richly annotated corpora available. Most of this data rely on well known and established standards, such as TEI, which especially enable scientists to edit and publish their work. However, one of the remaining problems is to give adequate access to this rich data, in order to produce higher-order knowledge. In this paper, we present an integrated environment combining an advanced search engine and text-mining techniques for hermeneutics in Digital Humanities. Relying on semantic web technologies, the search engine uses full text as well as complex embedding structures and offers a single interface to access rich and heterogeneous data and meta-data. Text-mining possibilities enable scholars to exhibit regularities in corpora. Results obtained on the Cartesian corpus illustrate these principles and tools.
数字人文学科高级信息检索与文本挖掘的结合
数字人文使越来越多的结构化和丰富注释的语料库可用。这些数据大多依赖于众所周知的既定标准,例如TEI,这些标准特别使科学家能够编辑和发表他们的工作。然而,仍然存在的问题之一是如何充分访问这些丰富的数据,以产生高阶知识。在本文中,我们提出了一个集成的环境,结合了先进的搜索引擎和文本挖掘技术的解释学数字人文。基于语义web技术,搜索引擎使用全文以及复杂的嵌入结构,并提供单一接口来访问丰富的异构数据和元数据。文本挖掘的可能性使学者能够展示语料库中的规律。在笛卡尔语料库上得到的结果说明了这些原理和工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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