Welcome to the INFORMATION MINING AND LEARNING research group 


Research Interests

  • Data Science in general
  • Computational Intelligence
  • Machine Learning and Applications, in particular Deep Learning
  • Emotion Detection in Texts
  • Artificial Companions

Current Projects and Publications

Current Research

  • We work on automatic solutions to recognize and to understand the content of early printed maps, mainly from the 16th to 19th century, and bring them into a computer-readable format. To reach this goal a wide range of machine learning algorithms is used, especially related to computer vision tasks. This work enhances the searchability within these historic documents and enables further research like understanding the history of a place name or examining the similarities
    and differences between maps.  Contact: Winfried Höhn, Christoph Schommer.
  • PERSEUS: We aim at discovering individualities in expressing sentiments in text. To study the diversity between individuals and the consistency in each individual, we build a personalized framework named PERSEUS. PERSEUS takes user-related text from social platforms such as Twitter and Facebook, and investigates and improves sentiment categorization by looking into the past. This project researches beyond purely understanding the meaning of text, and focuses on integrating the preference and tendency of users to provide user-sensitive predictions. Contact: Siwen Guo, Christoph Schommer.
  • Despite their remarkable value, autobiographies appear to remain one of the most under-utilised historical resources. The proposed research project in digital humanities will apply computational "distant reading" methods (natural language processing in general and topic modeling in particular) as a complement to traditional "close reading" of Indigenous Australian autobiographies,  aiming to identify meaningful language use patterns in the context of social environment and historical events.  Contact: Ekaterina Kamlovskaya, Christoph Schommer.

Current Courses

  • Database Management I (BINFO)
  • Database Management II (BINFO)
  • Natural Language Processing (BICS)
  • Data Science for Humanities (BICS)
  • Information Retrieval and Learning (MICS)
  • Knowledge Discovery and Data Mining (MICS)
  • Machine Learning (MICS)
  • Data Science (MMATH)

Former Members

  • Dr. Dimitrios Kampas: Topic Identification considering word order in Markov Chains.
  • Dr. Sviatlana Höhn: Data-driven repair models for text chat with language learners.
  • Dr. Mihail Minev (2014): Feature Detection and Classification in Financial News.
  • Dr. Jayanta Poray (2012): INACS -- An Intelligent and Adaptive Systems for Conversational Streams.
  • Dr. Sascha Kaufmann (2010): CUBA -- Artificial Conviviality and User Behaviour Analysis.
  • Dr. Maria Biryukov (2010): Methods of Extracting Meta-Information from Bibliographic Databases.
  • Dr. Michael Hilker (2008): Network Security through Artificial Immunity with SANA.
  • Dr. Alejandro Correa Bahnsen (2012-2014)
  • Dr. Patrice Caire (11/2006 - 10/2007)
  • Dipl.-Inf. Ralph Weires (04/2006 - 03/2008)
  • MSc. Ben Schroeder (10/2005 - 09/2007)
  • MSc. Fabien Bouleau

Last updated on: 24 May 2017