Parallel Bifold: Large-scale parallel pattern mining with constraints

Parallel Regular-Frequent Pattern Mining in Large Databases

Mining interesting patterns in various domains is an important area in data mining and knowledge discovery process. A number of parallel and distributed frequent pattern mining algorithms have been proposed so far for the large and/or distributed databases. Occurrence frequency is not the only criteria to mine the patterns but also occurrence behavior (regularity) of a pattern may also be inclu...

Parallel and Distributed Closed Regular Pattern Mining in Large Databases

Due to huge increase in the records and dimensions of available databases pattern mining in large databases is a challenging problem. A good number of parallel and distributed FP mining algorithms have been proposed for large and distributed databases based on frequency of item set. Not only the frequency, regularity of item also can be considered as emerging factor in data mining research. Cur...

Parallel Simulation of Large-Scale Parallel Applications

Accurate and efficient simulation of large parallel applications can be facilitated with the use of direct execution and parallel discrete-event simulation. This paper describes MPI-SIM, a direct execution-driven parallel simulator designed to predict the performance of existing MPI and MPI-IO application. MPI-SIM can be used to predict the performance of these programs as a function of archite...

Writing Large - Scale Parallel

Large Scale Parallel Document Mining for Machine Translation

A distributed system is described that reliably mines parallel text from large corpora. The approach can be regarded as cross-language near-duplicate detection, enabled by an initial, low-quality batch translation. In contrast to other approaches which require specialized metadata, the system uses only the textual content of the documents. Results are presented for a corpus of over two billion ...