Gregory Piatetsky-Shapiro, Data Mining: Introduction for Faculty
Hi! I am Gregory Piatetsky-Shapiro, and I am going to talk about Knowledge Discovery in Data, which is the process of finding valid, novel, useful, and potentially understandable patterns in data.
In 1989 I organized the first meeting on this topic and since then the field of Data Mining and Knowledge Discovery has grown tremendously, with over a dozen annual international conferences and thousands of active researchers.
Data Mining and Knowledge Discovery studies how to analyze the flood of information generated by businesses, science, web, and other sources. It uses methods from several fields, including databases, machine learning, statistics, and information visualization and it focuses on key tasks such as classification, clustering, market basket analysis or association rules, and link analysis.
Data mining applications are already widespread in many fields, including banking, CRM, ecommerce, genomics, investment, telecom, web analysis. Data Mining is also being applied beyond the traditional structured numeric data to more complex data such as text, multi-media, sound, images, and the web. Data mining is an active research area, with many open and interesting problems, so I hope you will be consider teaching this course and joining the data mining research community.
If you want to see the video of this intro, here is the URL:
(quicktime, 5.7 MB, ~ 1 min)