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Research on the Data Mining and Intelligent Recommendation Prediction in Electronic Business Systems

Yiqi Zhuang

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Abstract

A brief introduction to the concept of data mining is given and three algorithms are analyzed and compared,including a decision tree algorithm which has the more detailed patterns for each item and allows continuous inputs but does not expand into bigger directories,an association rule algorithm which can be fast and expandable but very sensitive to the parameters,and a clustering algorithm which can group the data according to comparability but needs to set the complex parameters and variables.

About this research paper

What this paper is about

A brief introduction to the concept of data mining is given and three algorithms are analyzed and compared,including a decision tree algorithm which has the more detailed patterns for each item and allows continuous inputs but does not expand into bigger directories,an association rule algorithm which can be fast and expandable but very sensitive to the parameters,and a clustering algorithm which can group the data according to comparability but needs to set the complex parameters and variables.

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Method / approach

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Available abstract

A brief introduction to the concept of data mining is given and three algorithms are analyzed and compared,including a decision tree algorithm which has the more detailed patterns for each item and allows continuous inputs but does not expand into bigger directories,an association rule algorithm which can be fast and expandable but very sensitive to the parameters,and a clustering algorithm which can group the data according to comparability but needs to set the complex parameters and variables.

Key concepts: Computer science, Comparability, Data mining, Association rule learning, Decision tree, Cluster analysis, Set (abstract data type), Decision tree learning

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