Frequent subtree mining–an overview
Mining frequent subtrees from databases of labeled trees is a new research field that has
many practical applications in areas such as computer networks, Web mining …
many practical applications in areas such as computer networks, Web mining …
Graph mining: A survey of graph mining techniques
SU Rehman, AU Khan, S Fong - … International Conference on …, 2012 - ieeexplore.ieee.org
Data mining is comprised of many data analysis techniques. Its basic objective is to discover
the hidden and useful data pattern from very large set of data. Graph mining, which has …
the hidden and useful data pattern from very large set of data. Graph mining, which has …
A survey of frequent subgraph mining algorithms
Graph mining is an important research area within the domain of data mining. The field of
study concentrates on the identification of frequent subgraphs within graph data sets. The …
study concentrates on the identification of frequent subgraphs within graph data sets. The …
Efficiently mining frequent trees in a forest
MJ Zaki - Proceedings of the eighth ACM SIGKDD international …, 2002 - dl.acm.org
Mining frequent trees is very useful in domains like bioinformatics, web mining, mining
semistructured data, and so on. We formulate the problem of mining (embedded) subtrees in …
semistructured data, and so on. We formulate the problem of mining (embedded) subtrees in …
Spin: mining maximal frequent subgraphs from graph databases
One fundamental challenge for mining recurring subgraphs from semi-structured data sets is
the overwhelming abundance of such patterns. In large graph databases, the total number of …
the overwhelming abundance of such patterns. In large graph databases, the total number of …
XRules: an effective structural classifier for XML data
MJ Zaki, CC Aggarwal - Proceedings of the ninth ACM SIGKDD …, 2003 - dl.acm.org
XML documents have recently become ubiquitous because of their varied applicability in a
number of applications. Classification is an important problem in the data mining domain …
number of applications. Classification is an important problem in the data mining domain …
Efficiently mining frequent embedded unordered trees
MJ Zaki - Fundamenta Informaticae, 2005 - content.iospress.com
Mining frequent trees is very useful in domains like bioinformatics, web mining, mining semi-
structured data, and so on. In this paper we introduce SLEUTH, an efficient algorithm for …
structured data, and so on. In this paper we introduce SLEUTH, an efficient algorithm for …
Mining closed and maximal frequent subtrees from databases of labeled rooted trees
Tree structures are used extensively in domains such as computational biology, pattern
recognition, XML databases, computer networks, and so on. One important problem in …
recognition, XML databases, computer networks, and so on. One important problem in …
Cmtreeminer: Mining both closed and maximal frequent subtrees
Tree structures are used extensively in domains such as computational biology, pattern
recognition, XML databases, computer networks, and so on. One important problem in …
recognition, XML databases, computer networks, and so on. One important problem in …
HybridTreeMiner: An efficient algorithm for mining frequent rooted trees and free trees using canonical forms
Tree structures are used extensively in domains such as computational biology, pattern
recognition, XML databases, computer networks, and so on. In this paper, we present …
recognition, XML databases, computer networks, and so on. In this paper, we present …