An efficient association rule mining for XML data

被引：0

作者：

Khaing, Myint Myint ^{[1
]}

Thein, Nilar ^{[1
]}

机构：

[1] Univ Comp Studies, Yangon, Myanmar

来源：

2006 SICE-ICASE INTERNATIONAL JOINT CONFERENCE, VOLS 1-13 | 2006年

关键词：

association rules; data mining; apriori algorithm;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

XML association rule mining is an important problem in data mining domain. Currently, the problem of association rule mining on XML data has not been well studied. In this paper, we proposed an efficient association rule mining for XML data which mining association rule in large amount of XML data. The set of data is view as a binary table. The value of this itemset to one if the corresponding XML data exit in the dataset, zero for otherwise. Like Aprioi methods, the proposed efficient mining association rules with two steps: to find frequent itemsert and to generate possible association rules between XML data. Our proposed system EARM may reduce the memory storage size and it returns association rules with short response time.

引用

页码：2843 / +

页数：2

共 17 条

[1]

Agrawal R, 1994, P 20 INT C VER LARG, P207

[2]

Agrwal R., 1994, P 20 INT C VER LARG, P487

[3]

[Anonymous], 1996, Advances in Knowledge Discovery and Data Mining, DOI DOI 10.1007/978-3-319-31750-2.

[4]

ASAI T, 2002, P 2 SIAM INT C DAT M

[5]

CHEN Z, 2001, 17 INT C DAT ENG

[6]

DAS A, 2000, 10 INT C INF KNOWL M

[7] Scalable parallel data mining for association rules [J].

Han, EH ;

Karypis, G ;

Kumar, V .

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2000, 12 (03) :337-352

[8]

Jong Soo Park, 1995, SIGMOD Record, V24, P175, DOI 10.1145/568271.223813

[9]

Orlando S., 2001, Data Warehousing and Knowledge Discovery. Third International Conference, DaWaK 2001. Proceedings (Lecture Notes in Computer Science Vol.2114), P71

[10]

PARK J, 2005, EXIT B NEW APPROACH

← 1 2 →