Big Data Knowledge Mining

Exploring Big Haystacks: Data Mining and Knowledge Management

Big Data Frequent Pattern Mining

Frequent pattern mining is an essential data mining task, with a goal of discovering knowledge in the form of repeated patterns. Many efficient pattern mining algorithms have been discovered in the last two decades, yet most do not scale to the type of data we are presented with today, the so-called “Big Data”. Scalable parallel algorithms hold the key to solving the problem in this context. In...

Onomastics and Big Data Mining

As of today, the main business application of onomastics is naming, or branding: �nding the proper name for your company or your product to stand out in the world. Meaningfully, Onoma – the Greek root for name – is also a registered trademark of Nomen, the naming agency founded by Marcel Botton in 1981. Nomen initially licensed one of Roland Moreno's inventions, the Radoteur name generator, and...

Data Mining Application for Big Data Analysis

Data mining is the application of specific algorithms for extracting patterns from data. Big Data is a new term used to identify the datasets that due to their large size and complexity, we cannot manage them with our current methodologies or data mining software tools. Big Data mining is the capability of extracting useful information from these large datasets or streams of data, that due to i...

Data Partitioning View of Mining Big Data

There are two main approximations of mining big data in memory. One is to partition a big dataset to several subsets, so as to mine each subset in memory. By this way, global patterns can be obtained by synthesizing all local patterns discovered from these subsets. Another is the statistical sampling method. This indicates that data partitioning should be an important strategy for mining big da...