文章基本信息

标题：A Hybrid Approach Based On Association Rule Mining and Rule Induction in Data Mining
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作者：Kapil Sharma ; Sheveta Vashisht ; Heena Sharma 等
期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2013
卷号：3
期号：1
页码：146-148
出版社：International Journal of Soft Computing & Engineering
摘要：Data Mining: extracting useful insights from large and detailed collections of data. With the increased possibilities in modern society for companies and institutions to gather data cheaply and efficiently, this subject has become of increasing importance. This interest has inspired a rapidly maturing research field with developments both on a theoretical, as well as on a practical level with the availability of a range of commercial tools. In this research work titled a hybrid approach based on Association Rule mining and Rule Induction in Data Mining we using induction algorithms and Association Rule mining algorithms as a hybrid approach to maximize the accurate result in fast processing time. This approach can obtain better result than previous work. This can also improves the traditional algorithms with good result. In the above section we will discuss how this approach results in a positive as compares to other approaches.
关键词：Association Rule mining; A priori algorithm; Rule;Induction; Decision list induction; Data mining