从文本中挖掘因果关系的数据采掘--以海事事故调查报告为例
Data Mining of Causal Relations from Text: Analysing Maritime Accident Investigation Reports
摘要：
文本挖掘是从文本中提取人们感兴趣的信息的过程。这种方法包括来自诸如信息检索（IR）、自然语言处理（NLP）和信息抽取（IE）的各种领域的技术。在这项研究中，应用文本挖掘方法从海事事故调查处（MAIB）收集的海事事故调查报告中提取因果关系。这些因果关系提供了关于事故背后各种机制的信息，包括与事故有关的人为因素和组织因素。本研究的目的是希望借由更可行的方式，来萃取海事事故调查报告中的致因，以利分析。对报告中的促成原因进行仔细调查，为今后提高安全性提供了机会。本研究采用两种方法来提取因果关系。它们是1）模式分类法和2）连接词法。早期的一个使用朴素贝叶斯和支持向量机（SVM）作为分类器。后者只是在句子中搜索连接原因和结果的单词。将使用这两种方法提取的因果模式与手动（人类专家）提取进行比较。模式分类方法显示出公平和合理的性能与F-测量（平均）= 65%相比，连接词的方法与F-测量（平均）= 58%。本文的研究为文本挖掘方法在海事调查报告因果关系提取中的应用提供了依据。
英文摘要：
Text mining is a process of extracting information of interest from text. Such a method includes techniques from various areas such as Information Retrieval (IR), Natural Language Processing (NLP), and Information Extraction (IE). In this study, text mining methods are applied to extract causal relations from maritime accident investigation reports collected from the Marine Accident Investigation Branch (MAIB). These causal relations provide information on various mechanisms behind accidents, including human and organizational factors relating to the accident. The objective of this study is to facilitate the analysis of the maritime accident investigation reports, by means of extracting contributory causes with more feasibility. A careful investigation of contributory causes from the reports provide opportunity to improve safety in future. Two methods have been employed in this study to extract the causal relations. They are 1) Pattern classification method and 2) Connectives method. The earlier one uses naive Bayes and Support Vector Machines (SVM) as classifiers. The latter simply searches for the words connecting cause and effect in sentences. The causal patterns extracted using these two methods are compared to the manual (human expert) extraction. The pattern classification method showed a fair and sensible performance with F-measure(average) = 65% when compared to connectives method with F-measure(average) = 58%. This study is an evidence, that text mining methods could be employed in extracting causal relations from marine accident investigation reports.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
