TY - GEN
T1 - Exploring the power of heuristics and links in multi-relational data mining
AU - Yin, Xiaoxin
AU - Han, Jiawei
N1 - The work was supported in part by the U.S. National Science Foundation NSF IIS-05-13678 and NSF BDI-05-15813. Any opinions, findings, and conclusions or recommendations expressed here are those of the authors and do not necessarily reflect the views of the funding agencies.
PY - 2008
Y1 - 2008
N2 - Relational databases are the most popular repository for structured data, and are thus one of the richest sources of knowledge in the world. Because of the complexity of relational data, it is a challenging task to design efficient and scalable data mining approaches in relational databases. In this paper we discuss two methodologies to address this issue. The first methodology is to use heuristics to guide the data mining procedure, in order to avoid aimless, exhaustive search in relational databases. The second methodology is to assign certain property to each object in the database, and let different objects interact with each other along the links. Experiments show that both approaches achieve high efficiency and accuracy in real applications.
AB - Relational databases are the most popular repository for structured data, and are thus one of the richest sources of knowledge in the world. Because of the complexity of relational data, it is a challenging task to design efficient and scalable data mining approaches in relational databases. In this paper we discuss two methodologies to address this issue. The first methodology is to use heuristics to guide the data mining procedure, in order to avoid aimless, exhaustive search in relational databases. The second methodology is to assign certain property to each object in the database, and let different objects interact with each other along the links. Experiments show that both approaches achieve high efficiency and accuracy in real applications.
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U2 - 10.1007/978-3-540-68123-6_2
DO - 10.1007/978-3-540-68123-6_2
M3 - Conference contribution
AN - SCOPUS:44649122147
SN - 3540681221
SN - 9783540681229
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 17
EP - 27
BT - Foundations of Intelligent Systems - 17th International Symposium, ISMIS 2008, Proceedings
T2 - 17th International Symposium on Methodologies for Intelligent Systems, ISMIS 2008
Y2 - 20 May 2008 through 23 May 2008
ER -