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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 !