Relational Data Mining and GUHA

被引:0
作者
Karban, Tomas [1 ]
机构
[1] Charles Univ Prague, Dept Software Engn, Fac Math & Phys, CR-11800 Prague 1, Czech Republic
来源
DATESO 2005 - DATABASES, TEXTS, SPECIFICATIONS, OBJECTS | 2005年
关键词
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
This paper presents an extension of GUHA method for relational data mining of association rules. Because ILP methods are well established in the area of relational data mining, a feature comparison with GUHA is presented. Both methods suffer from the explosion of the hypotheses space. This paper shows heuristic approach for GUHA method to deal with it, as well as other methods helping with the relational data mining experience.
引用
收藏
页码:103 / 112
页数:10
相关论文
共 14 条
[1]  
AGGRAVAL R, 1996, ADV KNOWLEDGE DISCOV, P307
[2]   Improving the efficiency of inductive logic programming through the use of query packs [J].
Blockeel, H ;
Dehaspe, L ;
Demoen, B ;
Janssens, G ;
Ramon, J ;
Vandecasteele, H .
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2002, 16 :135-166
[3]  
BLOCKEEL H, 2003, ACM SIGKDD EXPLORATI, V5, P17
[4]  
BLOCKEEL H, 2003, IJCAI 2003 WORKSH LE
[5]  
DEHASPE L, 1997, LECT NOTES ARTIF INT, V1297, P125
[6]  
DZEROSKI S, 2003, ACM SIGKDD EXPLORATI, V5, P1
[7]  
Dzeroski Saso, 2001, RELATIONAL DATA MINI
[8]  
Hajek, 1978, Mechanising Hypothesis Formation-Mathematical Foundations for a General Theory
[9]  
RAUCH J, 2005, FDN NOVEL APPROACHES
[10]  
RAUCH J, 2002, COMMUNICATIONS I INF, V5, P77