A data mining approach for query refinement

被引：0
|
作者：
Liu, Y [1 ]
Chen, HX
Yu, JX
Ohbo, N
机构：
[1] Univ Tsukuba, Dept Elect & Informat Sci, Tsukuba, Ibaraki 305, Japan
[2] Tsukuba Int Univ, Tsuchiura, Ibaraki 300, Japan
[3] Australian Natl Univ, Dept Comp Sci, Canberra, ACT 0200, Australia
来源：
RESEARCH AND DEVELOPMENT IN KNOWLEDGE DISCOVERY AND DATA MINING | 1998年 / 1394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：
We propose a data mining approach for query refinement using Association Rules (ARs) among keywords being extracted from a document database. We are concerned with two issues in this paper. First, instead of using minimum support and minimum confidence which has Little effectiveness of screening: documents, we use maximum support and maximum confidence. Second, to further reduce the number of rules, me introduce two co-related concepts: "stem rule" and "coverage". The effectiveness of using ARs to screen is reported as well.
引用
收藏
页码：394 / 396
页数：3
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