A knowledge-based model of parliamentary election

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• 作者：Jerzy Ho艂ubiec^a ; ^b ; ^{holubiec@ibspan.waw.pl} ; Gra偶yna Szkatu艂a^a ; ^{szkatulg@ibspan.waw.pl} ; Dariusz Wagner^a ; ^{wagner@ibspan.waw.pl}
• 关键词：Parliamentary election ; Electorate preferences ; Machine learning from examples ; Decision rules
• 刊名：Information Sciences
• 出版年：2012
• 期刊代码：62_00200255
• 类别：cp
• 出版时间：20 October, 2012
• 卷：202
• 期：Complete
• 页码：24-40
• 文件大小：307 K

摘要

The paper presents a new approach to the analysis of the electoral campaign based on the use of the methodology of machine learning. Attributes describing socio-political programmes of parties or individual candidates taking part in election are examined. The attributes are used to construct a knowledge-based model of parliamentary election. Parties or candidates are treated as examples. The sets of examples and their partition into disjoint classes form a starting point in the process of machine learning, which is supposed to lead to the descriptions of the considered classes. The classes are described in the form of the following decision rules: 鈥淚F certain conditions are satisfied, THEN a given example is a member of a specific class鈥? They can be used to form a set of action rules that specify the conditions of a hypothetical transfer to another class, i.e., the winners or the losers. The case study, based on the Polish Parliamentary election of 2007, illustrates the application of the proposed methodology.