多关系分类方法研究

Peng Zhen, Lifeng Wu, Xiaoju Wang
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引用次数: 3

摘要

作为多关系数据挖掘的一项重要任务,多关系分类可以直接从关系数据库中寻找涉及多个关系的模式,比命题数据挖掘方法更具优势。根据知识表示和策略的差异,研究了基于ILP、基于图和基于关系数据库的三种多关系分类方法,并详细讨论了每种关系分类技术及其特点、比较和若干研究难点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Multi-Relational Classification Approaches
As an important task of multi-relational data mining, multi-relational classification can directly look for patterns that involve multiple relations from a relational database and have more advantages than propositional data mining approaches. According to the differences in knowledge representation and strategy, the paper researched three kind of multi-relational classification approaches that are ILP based, graph-based and relational database-based classification approaches and discussed each relational classification technology, their characteristics, the comparisons and several challenging researching problems in detail.
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