88-852 Project Information Systems: Data Science for Web-Applications

Instructors: Dr. Kai Brüssau; Michael David Palk

Event type: Seminar

Displayed in timetable as: WiInf-BAProjekt

Hours per week: 6

Language of instruction: German

Min. | Max. participants: - | 30

Registration group: Anmeldegruppe Projekte

Comments/contents:
In this project the students gather in groups of about 3 - 4 people, practically address a problem in the field of data science and then prepare a project report, which presents the solution for the chosen problem from both the theoretical and the practical point of view. At the beginning of the project all students learn the ropes of the field of data science, in particular data mining methods, and get to know the statistical software R. Subsequently, individual groups are formed, each of which selects a problem and tackles it in the further course. During this process, various investigations are carried out according to the KDD process (Knowledge Discovery in Databases) and a solution model is developed. Possible problems are:

• Classification of customers in order to draft customer profiles and forecast their behavior
  
• Recommender systems for recommending music, movies or other products (such as Spotify, Netflix or Amazon)
  
• Text mining within document management for identifying specific content (e.g., addresses, customer numbers, billing information, etc.)
  
• Text mining for the automated analysis of texts such as Tweets, customer reviews, etc.
  
• ...
  

• Artificial Intelligence
  
• Machine learning
  
• Ensemble learning
  
• Named Entity Recognition
  
• Artificial Neuronal Networks
  
• Random Forest, Boosting
  
• Regression Methods
  
• ...