Main Seminars Web Tutorials

MTAT.03.251 Graph Mining

MTAT.03.251 Andmekaeve graafides

What and Why

The course aims to give a overview of basic graph mining techniques starting form the graph construction and ending with prediction of graph structures. Graph mining is relatively new research area. Although graphs are natural way to represent connections and associations between objects, they are also complex discrete objects compared to simple arrays and matrices. As a result, standard statistical techniques and machine learning algorithms have to be modified to run on top of graphs. In this course, we view basic ways how to overcome this by using graph specific methods and various ways to flatten the complex structure by feature extraction. Another reason why graph mining is relatively new is purely pragmatical. Although large network structures have been present for a long time, only recent changes in technology have made it possible to collect such kind of data. For example, only recent network-oriented applications such as instant messengers, social network websites and geo-tagging, have opened an opportunity to observe and study large-scale social interactions. Also, lack of efficient algorithms and lack of raw computing power have been hindering factors. As such the topic is highly suitable for students from computer science and statistics. In particular, note that elements of graph mining are heavily used in system biology and bioinformatics and several major projects done in cooperation between department of computer science and competence center STACC are closely related to study of social networks.

Requirements

There are no formal prerequisites to the seminar. However, basic knowledge in programming, basic math and graph theory is advisable. Also, one needs reasonable English skills to complete the course report. If the formal requirements of the ÕIS do not permit registration then write me an email or talk with me. After that we decide whether to enroll you or not.

To pass the course

Differently from the last years seminar, the course is organized as a reading group. That is, on average each student makes two presentations and some illustrative demos. The demos will be included into web tutorials. The course grade will be decided on the quality of presentations and web tutorials. Tutorials must contain explanation of theoretical concepts, their graphical illustrations, code snippets in GNU R that explain the concepts furthermore.

You must actively participate in most seminars or otherwise you do not pass the seminar. Namely, student gets grade F if he or she misses 3 or more seminars. In reasonable circumstances, it is possible to compensate missed seminars by extra work. Details are determined by individual agreements with the lecturer. You must do a project work. The project work will be graded in the scale from A to F and it will form the basic grade for the course.

Assignments

Presentations

Web Tutorials