Transcript Data Mining with Big data By

Data Mining with Big data
By: Pouya Otarod
Spring 2014
What is …… ?
•
Data Mining
‣
•
computational process of discovering patterns in
large data sets
Big Data
‣
it is the term for a collection of data sets so large
and complex that it becomes difficult to process
‣
data has exponential growth, both structured and
unstructured
How much Data does exist?
•
2.5 quintillion bytes of data are created
EVERY
DAY
•
IBM: 90 percent of the data in the world today were
produced with past two years
•
Forms of Data????
Big Data Examples
•
October 4th, 2012, the first presidential debate
•
Flicker and its photos
Problem…!
•
Data has grown tremendously
•
This large amount of data is beyond the of software
tools to manage
•
Exploring the large volume of data and extracting
useful information and knowledge is a challenge,
and sometimes, it is almost infeasible
HACE Theorem
•
Heterogeneous, Autonomous, Complex, Evolving
•
Big data starts with large volume, heterogeneous,
autonomous
sources
with
distributed
and
decentralized control, and seeks to explore complex
and evolving relationships among data
•
These are characteristics of Big Data
•
This is theorem to model Big Data characteristics
•
Huge Data with heterogeneous and diverse
dimensionality
‣
•
Autonomous sources with distributed and
decentralized control
‣
•
represent huge volume of data
main characteristics of Big Data
Complex and evolving relationships
Data Mining Challenges with Big
Data
•
Big Data Mining Platform
•
Dig Data Semantics and Application Knowledge
I. Information Sharing and Data Privacy
II. Domain and Application Knowledge
•
Big Data Mining Algorithm
I. Local Learning and Model Fusion for Multiple
Information Sources
II. mining from Sparse, Uncertain, and Incomplete Data
III. Mining Complex and Dynamic Data
Thanks for you attentions !