Next Generation Data Mining Thinking out of the box hyper-rectangle Michael Pazzani Division Director, Information and Intelligent System NSF 11/10/2018

Successes of Data Mining Research results in medicine, biology etc. Reducing expenses on fraud and increase revenue by recommendation systems Good interplay between theory and practice Well-defined metrics and envious collections of benchmark problems 11/10/2018

Data Mining: Looking where the light is good? classification and regression problems dominate: What about plan recognition? Learn from single record in database (or file): What about transactions, text, images, audio, video… learn single concepts in isolation learn from many examples unaware of goals of learner (or adversaries) don’t make ongoing contributions to knowledge base of agent or take advantage of it can’t explain results of learning to laypeople or scientists assume identically and independently distributed examples 11/10/2018

New problems need new metrics Plan recognition: # of steps in plan (e.g., number of transactions) Number of examples required to achieve a given accuracy vs. asymptotic Distance (or similarity) between production environment and training examples Privacy? 11/10/2018

NSF Types of proposals/awards Unsolicited Proposal Deadlines  11/18 & 3/1 Information Technology Research (ITR) Small (<$500K) Dec 12, 2002 Medium (<$4M) Feb 12, 2002 Large (<$15M) Nov 18, 2002 (Pre-proposal) Mar 24, 2003 (Full Proposal) 11/10/2018

How you can help? Submit High Quality Proposals Innovative, but achievable Well-written Address broader impacts Participate in Reviewing/Panels Keep Program Manager informed of findings CISE Newsletter Joint Press Releases PowerPoint of Conference Presentations Participate in Workshops Rotate in as a Program Manager (IPA) 11/10/2018