Modul

Siehe Teilleistung.

Goal of the lab course is to implement Data Mining Techniques in Java. Then, the students are supposed to design and conduct an empirical evaluation of their own approach against another (provided) baseline approach using data of the Sloan digital SkyServer. The implementation includes requirements engineering, modelling, test-driven implementation and integrations into an existing Open-Source project.

· We examine advanced Data Mining Approaches comparing the similarity of SQL queries.

· The course provides an overview on existing solutions to determine their strong and weak points based on a real-world case study.

Siehe Teilleistung.

In this practical course, students will gain in depth insides on advanced Data Mining Approaches in the context of Big Data. In particular, the students shall implement and evaluate an advanced approach to compare the similarly of SQL queries in order to build an on-the-fly query recommendation system. This way, students learn to tailor existing approaches to a specific application scenario and to evaluate this approach using a real-world case study. The goal of the lab course is build a software solution in small teams. To this end, the students get in-depth practical experience on agile software-development and team skills.

Advanced knowledge on Data Mining approaches, particular distance-based classifications, e.g., from the course “Analysetechniken für große Datenbestände” [24114] are a pre-condition. In addition, we require the students to have advanced experiences in Java programming.

· Einarbeitung 20h

· Eigenverantwortliches Arbeiten 80h 30 min

· Präsentationsvorbereitung 10h

Summe 122h 30 min