The goal of this project is to apply the concepts and the technologies previously seen. To this end, you have to choose one of the following datasets¹⁾.

On the considered dataset, you have to either bring some insights according to an already given task or combination of tasks (e.g., clustering, pattern mining ) or define yourself the general aims and discover some knowledge from the data (produce added value from the data). To this end, you can use any data mining/machine learning method²⁾ as well as any algorithm or software (Knime, Sci-Kit Learn (Python), Web Api (Google, Bing, Yahoo, …)).

You have – using the different concepts seen during the lectures (but not uniquely) – produce added value from data (answer the a specific question, discover knowledge, …). You can use any tools/techno/algorithms. These datasets can also be the support of the development of your proper algorithms (pattern sampling approach, interactive exploration, …).

You have to:

• Write a report (pdf format) describing your work (10 pages max., appendices are possible);
• Provide an archive of your code;
• Present your work on May 11th: a 10-minute presentation followed by questions (5 minutes)

<note important> The report, presentation and source code must be sent by email (marc.plantevit-at-liris.cnrs.fr, cc: marc.plantevit@univ-lyon1.fr) before May, 22nd, 2016 (23h59) ⁴⁾. </note>

<note important> You can work in group of maximum 5 persons.

• Expected work = f(|group|) with f strictly increasing .

</note>