The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Big Data Analysis and Mining
Abstract
Big data analysis and mining aims to discover implicit, previously unknown, and potentially useful information and knowledge from big databases that contain high volumes of valuable veracious data collected or generated at a high velocity from a wide variety of data sources. Among different big data mining tasks, this chapter focuses on big data analysis and mining for frequent patterns. By relying on the MapReduce programming model, researchers only need to specify the “map” and “reduce” functions to discover frequent patterns from (1) big databases of precise data in a breadth-first manner or in a depth-first manner and/or from (2) big databases of uncertain data. Such a big data analysis and mining process can be sped up. The resulting (constrained or unconstrained) frequent patterns mined from big databases provide users with new insights and a sound understanding of users' patterns. Such knowledge is useful is many real-life information science and technology applications.
Related Content
Tapan Kumar Behera.
© 2023.
20 pages.
|
B. Narendra Kumar Rao.
© 2023.
17 pages.
|
Blendi Rrustemi, Deti Baholli, Herolind Balaj.
© 2023.
18 pages.
|
Alma Beluli.
© 2023.
11 pages.
|
Jona Ndrecaj, Shkurte Berisha, Erita Çunaku.
© 2023.
15 pages.
|
Yllka Totaj.
© 2023.
12 pages.
|
Hla Myo Tun, Devasis Pradhan.
© 2023.
31 pages.
|
|
|