Jefrey Lijffijt and Tijl De Bie will give a tutorial on mining ‘Subjective Interesting’ patterns in data at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), Dublin, September 2018.
Mining Subjectively Interesting Patterns in Data
The problem of formalizing interestingness of data mining results remains an important challenge in data mining research and practice. While it is widely recognized as a challenge in frequent pattern mining, in this tutorial we will explain that it also manifests itself in other data mining tasks such as dimensionality reduction, graph mining, clustering, and more. This tutorial aims to introduce the audience to a relatively new framework for addressing these challenges in a rigorous and generic manner. This framework is the result of the ERC project FORSIED (Formalizing Subjective Interestingness in Exploratory Data Mining), which has by now resulted in a body of work of sufficient maturity to make a well-rounded tutorial possible and useful to colleague researchers as well as practitioners.
- Part 1: Introduction and motivation
- Part 2: The FORSIED framework
- Part 3: Binary matrices, graphs, and relational data
- COFFEE BREAK
- Part 4: Numeric and mixed data
- Part 5: Advanced topics, outlook & conclusions