2D5342 Knowledge Discovery and Data Mining

Graduate Course 4p

Background

Proliferation of IT and automatic surveillance applications means that vast volumes of data are gathered for operations and other purposes. In business there is an increasing awareness that data collected constitute an untapped resource of business knowledge, that can be used to commercial advantage. In sciences, data collected in large scale experiments have rapidly outgrown the communities resources to analyse data. The method of using advanced 'semiintelligent' systems to systematically 'mine' data repositories and create knowledge is known as knowledge discovery and data mining.

In this course we introduce the main methods used in the area, as supported by techniques originating in the Data Base, Artificial Intelligence, Statistics and Visualization fields. We particularly cover the theoretical and practical problems in identifying 'true and interesting' knowledge as opposed to erroneous, random and uninteresting knowledge, a problem much studied in statistics and data base practice.

Prerequisites

Graduate student standing(forskarstuderande) or undergraduate student(teknolog) with first courses passed in programming, statistics, and (recommended) data bases or information systems.

Goals

After passing this course, you will

Course Topics

Examination

Examination is individual, and can consist of discussion of texts with me, presentation in class, homeworks and/or a small project. A list of papers you read for the course, preferrably with comments, and proposals for course improvement should be turned in.
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Stefan