Analysis of biological data plays an important role in medical and bioinformatics industry.
However, uncertainty in this biological information is the most unavoidable challenge of this …

The biological databases are flooded with genomic and proteomic data which can be
analyzed to generate the information and knowledge which can be useful for understanding …

The high-throughput technology has led to exponential growth of biological data and
information in online databases. This huge data provides new opportunities and challenges …

The present technology such as privacy-preserving data mining generates data, which is
inherently uncertain in nature. There are other existing tools, which are also collecting data …

Association Rule Mining is a Data Mining technique which extracts association rules from
the given dataset. A good number of research work has been reported in Association Rule …

The massive volumes of molecular data are available in online databases. The different
types of inherent uncertainties present in this molecular data pose major challenge in the …

In the field of data mining association rule is a very popular and efficient technique while it
has different technique such as classification, clustering, sequential pattern etc to extract or …

We propose a novel frequent-pattern tree (FP-tree) structure; our performance study shows
that the FP-growth method is efficient and scalable for mining both long and short frequent …

Mining frequent patterns has always been a great field of research for investigators. Various
algorithms were developed for finding out frequent patterns in an efficient manner. But the …

Several methods are available for mining frequent patterns in web data, but mostly they
suffer from the problem of huge candidate generation and number of database scans. In …