Text mining of bankruptcy information using formal concept analysis

S. Hirokawa, Takahiro Baba, Tetsuya Nakatoh
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引用次数: 5

Abstract

A lot of information concerning the status of companies are available on the Web. However, a simple search of documents does not explain the meaning or the cause the status. Semantical interpretation and hypotheses generation are necessary for further analysis. This paper proposes a method to analyse the cause and the situation of bankruptcy with respect to particular condition that a user can specify as a query. The method is based on the theory of formal concept analysis. The novelty of the method is in (a) that sentences are considered as objects and words are considered as attributes and (b) that a concise subgraph of the concept lattice is introduced and used to guess the cause. Two cases of interactive and iterative process are shown where a user proceeds from a simple query to a new hypothesis, which would not be able to found by a naive cross tabulation or keyword extraction.
基于形式概念分析的破产信息文本挖掘
很多关于公司状况的信息都可以在网上找到。然而,简单地搜索文件并不能解释这种状态的含义或原因。语义解释和假设生成是进一步分析的必要条件。本文提出了一种针对用户可以指定查询的特定条件来分析破产原因和破产情况的方法。该方法以形式概念分析理论为基础。该方法的新颖之处在于:(a)将句子视为对象,将单词视为属性;(b)引入概念格的简明子图并使用其来猜测原因。显示了交互和迭代过程的两个案例,其中用户从一个简单的查询继续到一个新的假设,这将无法通过简单的交叉制表或关键字提取找到。
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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