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People: Rasoul Karimi.
Office hour:
C37, upon request

Contact:
Phone:+49 5121/ 883-40366
Fax:+49 5121 / 883-40361
e-mail:

Personal Homepage

Teaching Assistant:
Big Data Analytics (summer semester 2014)
Business Intelligence Seminar(winter semester 2012)
Business Intelligence (summer semester 2012)
Machine Learning Practical (winter semester 2011)
Business Intelligence (summer semester 2011)
Artificial Intelligence (winter semester, 2010/2011)
Business Intelligence (summer semester 2010)
Master seminar:Artificial Intelligence and Machine Learning (winter semester, 2009/2010)

Research Projects:
RFID-Enhanced Museum for Interactive Experience (REMIX)

Books:

  • Rasoul Karimi, (2014):
    Active Learning for Recommender Systems, PhD thesis, University of Hildesheim, Cuvillier (Available in www.amazon.de )

Journal Papers:

  • Rasoul Karimi, Alexandros Nanopoulos, Lars Schmidt-Thieme (2015):
    A Supervised Active Learning Framework for Recommender Systems based on Decision Trees,User Modeling and User-Adapted Interaction (UMUAI), Springer-Verlag, 2015, Volume 25, Issue 1, pp 39-64, ISI/Thomson Impact Factor 3.037 (The final publication is available at link.springer.com ).
  • Rasoul Karimi (2014):
    Active Learning for Recommender Systems, Künstliche Intelligenz, Springer-Verlag, (The final publication is available at link.springer.com )
  • Rasoul Karimi, Mohammad Ahmadi, Other Authors (2007):
    MDA and SOA: Two New Architectures to Improve the Software Development Process, in System and Information Sciences Notes, Vol 1, No 4, Juli 2007, pp. 369-372.
  • Rasoul Karimi, Caro Lucas, Behzad Moshiri (2007):
    New Multi-Attribute Procurement Auction for Agent-Based Supply Chain Formation, in International Journal of Computer Science and Network Security, Vol. 7, No.4, pp. 255-261. PDF

Conference Papers:

  • Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme (2015):
    Comparing Prediction Models for Active Learning in Recommender systems, in Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML), Trier, Germany. PDF
  • Rasoul Karimi, Alexandros Nanopoulos, Lars Schmidt-Thieme (2014):
    Improved Questionnaire Trees for Active Learning in Recommender Systems, in Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML), Aachen, Germany. PDF
  • Rasoul Karimi, Martin Wistuba, Alexandros Nanopoulos, Lars Schmidt-Thieme (2013):
    Factorized Decision Trees for Active Learning in Recommender Systems, in 25th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Washington D.C, USA. PDF
  • Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme (2012):
    Exploiting the Characteristics of Matrix Factorization for Active Learning in Recommender Systems, in Doctoral Symposium of the 6th Annual ACM Conference on Recommender Systems (RecSys), Dublin, Irelan, pp. 317-320. PDF
  • Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Towards Optimal Active Learning for Matrix Factorization in Recommender Systems, in 23th IEEE International Conference on Tools With Artificial Intelligence (ICTAI), Florida, USA. PDF
  • Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Non-myopic Active Learning for Recommender Systems based on Matrix Factorization, in 12th IEEE International Conference on Information Reuse and Integration (IRI), Las Vegas, USA. PDF
  • Rasoul Karimi, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    RFID-Enhanced Museum for Interactive Experience, in MultiMedia for Cultural Heritage (MM4CH), Modena, Italy. PDF
  • Rasoul Karimi, Christoph Freudenthaler, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Active Learning for Aspect Model in Recommender Systems, in IEEE Symposium on Computational Intelligence and Data Mining (CIDM). PDF
  • Rasoul Karimi, Caro Lucas (2004):
    Fuzzy Model View Controller Pattern, in International Conference on Advances in Intelligent Systems, Theory and Applications in cooperation with IEEE Computer Society. PDF

Postal address:
Information Systems and Machine Learning Lab
Marienburger Platz 22
University of Hildesheim
31141 Hildesheim
Germany
Visitor address:
Information Systems and Machine Learning Lab
Samelsonplatz 1
University of Hildesheim
31141 Hildesheim
Germany



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