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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 frequent subgraphs can become too large to allow a full enumeration using reasonable computational resources. In this paper, we propose a new algorithm that mines only(More)
The need to integrate several versions of a program into a common one arises frequently, but it is a tedious and time consuming task to integrate programs by hand. The main contribution of this paper is an algorithm, called <italic>integrate</italic>, that takes as input three programs <italic>A, B</italic>, and <italic>Base</italic>, where(More)
The accurate mapping of reads that span splice junctions is a critical component of all analytic techniques that work with RNA-seq data. We introduce a second generation splice detection algorithm, MapSplice, whose focus is high sensitivity and specificity in the detection of splices as well as CPU and memory efficiency. MapSplice can be applied to both(More)
Frequent itemset mining is a popular and important first step in the analysis of data arising in a broad range of applications. The traditional " exact " model for frequent itemsets requires that every item occurs in each supporting transaction. Real data is typically subject to noise and measurement error. To date, the effects of noise on exact frequent(More)
Frequent subgraph mining is an active research topic in the data mining community. A graph is a general model to represent data and has been used in many domains like cheminformatics and bioinformatics. Mining patterns from graph databases is challenging since graph related operations, such as subgraph testing, generally have higher time complexity than the(More)
This paper presents an unbalanced tree search (UTS) benchmark designed to evaluate the performance and ease of programming for parallel applications requiring dynamic load balancing. We describe algorithms for building a variety of unbalanced search trees to simulate different forms of load imbalance. We created versions of UTS in two parallel languages,(More)
Frequent subgraph mining is an active research topic in the data mining community. A graph is a general model to represent data and has been used in many domains like cheminformatics and bioinformatics. Mining patterns from graph databases is challenging since graph related operations , such as subgraph testing, generally have higher time complexity than(More)