Although there are tools to help developers understand the matching behaviors between a
regular expression and a string, regular-expression related faults are still common. Learning …

Protein–protein interaction networks are mathematical constructs where every protein is
represented as a node, with an edge signaling that two proteins interact. These constructs …

Frequent itemset mining is an important operation to return all itemsets in the transaction
table, which occur as a subset of at least a specified fraction of the transactions. The existing …

This paper presents the DIS-C approach, which is a novel method to assess the conceptual
distance between concepts within an ontology. DIS-C is graph based in the sense that the …

Clustering is one of the standard unsupervised approaches in the field of data mining.
Clustering techniques carry a long history, and an expansive number of clustering …

Cancer has been classified as a heterogeneous genetic disease comprising various
different subtypes based on gene expression data. Early stages of diagnosis and prognosis …

Issues relating to clustering today are computational techniques, optimization, and
performance of clustering algorithms. In this research, a metaheuristic grouping method of …

Abstract “Big data” as the name suggests is a collection of large and complicated data sets
which are usually hard to process with on-hand data management tools or other …

Abstract Knowledge discovery is a process of finding hidden knowledge from a large volume
of data that involves data mining. Data mining unveils interesting relationships among data …

Biclustering method is one of the most important methods of the data mining techniques.
Biclustering can be used to discover similar patterns in datasets, especially gene expression …