A fuzzy-graph-based approach to the determination of interestingness of association rules

被引：0

作者：

Shekar, B ^{[1
]}

Natarajan, R ^{[1
]}

机构：

[1] Indian Inst Management Bangalore, Quantitat Methods & Informat Syst Area, Bangalore 560076, Karnataka, India

来源：

PRACTICAL ASPECTS OF KNOWLEDGE MANAGEMENT | 2002年 / 2569卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

'Interestingness' measures are used to rank rules according to the 'interest' a particular rule is expected to evoke in a user. In this paper, we introduce an aspect of interestingness called 'item-relatedness' to determine interestingness of item-pairs occurring in association rules. We elucidate and quantify three different types of item-relatedness. Relationships corresponding to item-relatedness proposed by us are shown to be captured by paths in a 'fuzzy taxonomy' (an extension of the concept hierarchy tree). We then combine these measures of item-relatedness to arrive at a total-relatedness measure. We finally demonstrate the efficacy of this total measure on a sample taxonomy.

引用

页码：377 / 388

页数：12

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