Big Data Analysis: New Algorithms for a New Society by Nathalie Japkowicz, Jerzy Stefanowski

By Nathalie Japkowicz, Jerzy Stefanowski

This edited quantity is dedicated to important facts research from a computer studying viewpoint as provided through probably the most eminent researchers during this sector.

It demonstrates that enormous facts research opens up new learn difficulties that have been both by no means thought of sooner than, or have been basically thought of inside of a restricted variety. as well as supplying methodological discussions at the rules of mining vast information and the adaptation among conventional statistical info research and more moderen computing frameworks, this ebook provides lately constructed algorithms affecting such components as company, monetary forecasting, human mobility, the net of items, details networks, bioinformatics, scientific platforms and lifestyles technology. It explores, via a couple of particular examples, how the examine of huge info research has advanced and the way it has began and should probably proceed to impact society. whereas the advantages introduced upon by means of enormous info research are underlined, the e-book additionally discusses a number of the warnings which were issued about the strength hazards of huge information research in addition to its pitfalls and challenges.

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They cast this problem as one of mining data streams where the data stream consists of a succession of information networks. Within this context they describe techniques that have previously been proposed to sample from such networks, a problem that is common to all cases of large network analysis but which is compounded here by the dynamic nature of the network. They also describe visualization techniques as well as network analysis such as centrality detection and community detection, which again are different in dynamic networks.

That is obviously undesirable and needs to be addressed in the future. They illustrate their point by taking as an example a tool for grading student essays, which relies on sentence length and word sophistication that were found to correlate well with human scores. A student knowing that such a tool will be used could easily write long non-sense sentences peppered with very sophisticated words to obtain a good grade. • Big Data Analysis yields tools that lack in robustness: Because Big Data Analysis based tools are often built from shallow associations rather than provable deep theories, they are very likely to lack in robustness.

Data Lakes are the successors of Data Warehouses which have become too small given the scale of Big Data sets and cannot adapt easily to dynamic data. The chapter also touches upon Big Data platforms and Big Data Analysis software available for Business projects. It overviews virtually all aspects discussed in Tables 1 and 2, but does so with a business application in mind. It is meant to introduce company executives to the realities of dealing with Big Data in their business. The discussion on infrastructure is related to the “Data management” entry of Table 1 and it addresses some of the questions raised in Sect.

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