促进领域知识发现的文本挖掘

Chengbin Wang, Xiaogang Ma
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引用次数: 3

摘要

近几十年来,高精度的观测和测量技术加速了地球科学研究的快速发展,并产生了大量的研究成果。许多发现和发现被记录在地质文献中,这些文献被视为非结构化数据。对于这些数据,传统的研究方法对于整合和挖掘数据进行知识发现的作用有限。基于自然语言处理(NLP)的文本挖掘为分析非结构化地质文献提供了必要的方法和技术。在本章中,我们将回顾地球科学领域文本挖掘的最新研究,并介绍一些案例研究的结果。研究包括三个主要部分:(1)地质文献的结构化;(2)地质文献的信息提取和可视化;(3)地质文本挖掘,以辅助数据库建设和知识发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Text Mining to Facilitate Domain Knowledge Discovery
The high-precision observation and measurement techniques have accelerated the rapid development of geoscience research in the past decades and have pro-duced large amounts of research outputs. Many findings and discoveries were recorded in the geological literature, which is regarded as unstructured data. For these data, traditional research methods have limited functions for integrating and mining them to make knowledge discovery. Text mining based on natural language processing (NLP) provides the necessary method and technology to analyze unstructured geological literature. In this book chapter, we will review the latest researches of text mining in the domain of geoscience and present results from a few case studies. The research includes three major parts: (1) structuralization of geological literature, (2) information extraction and visualization for geological literature, and (3) geological text mining to assist database construction and knowledge discovery.
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