Most current work in data mining assumes that the database is static, and a database update requires rediscovering all the patterns by scanning the entire old and new database. Su...
Data mining is the process of extracting implicit, valuable, and interesting information from large sets of data. Visualization is the process of visually exploring data for patte...
In this paper, we present a new system, called GeneScout, for predicting gene structures in vertebrate genomic DNA. The system contains specially designed hidden Markov models (HM...
This paper addresses the special applications of data mining techniques in homeland defense. The problem targeted, which is frequently encountered in military/intelligence surveil...
We investigate new approaches for frequent graph-based pattern mining in graph datasets and propose a novel algorithm called gSpan (graph-based Substructure pattern mining), which...
In this paper, we propose a new framework for mining frequent patterns from large transactional databases. The core of the framework is of a novel coded prefix-path tree with two...
In this paper, we devise an efficient algorithm for clustering market-basket data. Different from those of the traditional data, the features of market-basket data are known to b...
This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...