Dr. rer. nat. Philipp Kranen

Research associate
Room:6327
Email:kranen@informatik.rwth-aachen.de
Publications: 36 entries

Since August 2012 working at Microsoft Research.

 

Research interests

 

Classification and analysis of data and data streams

 

Research projects

  • UMIC - Ultra High-Speed Mobile Information and Communication
    • Research Area B: Mobile Applications & Services
      • Stream Data Mining
      • Anytime Algorithms
    • Research Area D: Cross Disciplinary Methods and Tool
      • Energy Efficient Data Dissemination
  • SFB 686 - Project A6 "Anytime-Verfahren zur prädiktiven Regelung mittels dynamisch adaptiver Modelle"
  • (EMD - Earth Mover's Distance)

 

The video from the One-Minute-Madness (100 Seconds about anytime algorithms) is available here (German). A presentation (English) about Anytime Clustering can be found on the bottom of this page.

 

 

Selected publications (complete list)

 

Kranen P., Assent I., Seidl T.:
An Index-inspired Algorithm for Anytime Classification on Evolving Data Streams
Datenbank-Spektrum (Springer DASP), Volume 12, Issue 1 P.43-50 (2012) DOI: 10.1007/s13222-012-0083-9
[DASP Journal - full text]

 

Kremer H., Kranen P., Jansen T., Seidl T., Bifet A., Holmes G., Pfahringer B.:
An Effective Evaluation Measure for Clustering on Evolving Data Streams
Proc. of the 17th ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD 2011), San Diego, CA, USA P.868-876 (2011)

[KDD 2011] [DOI: 10.1145/2020408.2020555
 

Kranen P., Seidl T.:
Harnessing the Strengths of Anytime Algorithms for Constant Data Streams
Data Mining and Knowledge Discovery Journal (Springer DMKD), Special Issue on Selected Papers from ECML PKDD 2009, Vol. 19, No. 2, S.245-260 (2009) [DOI 10.1007/s10618-009-0139-0]
[DMKD Journal - full text]


Kranen P., Assent I., Baldauf C., Seidl T.:
Self-Adaptive Anytime Stream Clustering
Proc. of the IEEE International Conference on Data Mining (ICDM 2009), Miami, USA S.249-258 (2009)
[ICDM 2009] [DOI: 10.1109/ICDM.2009.47]


Wichterich M., Assent I., Kranen P., Seidl T.:
Efficient EMD-based Similarity Search in Multimedia Databases via Flexible Dimensionality Reduction
Proc. of the ACM International Conference on Management of Data (SIGMOD 2008), Vancouver, BC, Canada. S.199-212 (2008)
[SIGMOD 2008] [DOI: 10.1145/1376616.1376639]

 

 

Invited presentations: 

 

National Institute of Informatics (NII), Tokyo, Japan, 2010

Siemens Corporate Research, Princeton, NJ, USA, 2011

 

 

Reviews for international conferences and journals:

  • SDM 2010, 2011 (SIAM Data Mining)
  • ACM SIGKDD 2009, 2010, 2011, 2012 (Knowledge Discovery and Data Mining)
  • EDBT 2008, 2009, 2010 (International Conference on Extending Database Technology)
  • ICDE 2008, 2009, 2010 (IEEE International Conference on Data Engineering)
  • PAKDD, SSDBM 
  • IEEE Transactions on Computers
  • IEEE Transactions on Knowledge and Data Engineering
  • IEEE Transactions on Knowledge Discovery from Data
  • Springer Datamining and Knowledge Discovery
  • ACM Computing Surveys

 

Teaching

  • Lecturer in the course 
    • Exploring Temporal and Graph Data: Mining & Retrieval
    • Ringvorlesung Medizinische Bildverarbeitung
  • Exercises in the courses 
    • Data Mining Algorithms
    • Algorithmen und Datenstrukturen
    • Technische Informatik 
  • Regular supervision of lab courses and seminar works
  • Supervision of theses (Diplom, Bachelor, Master)

  

Thesis

Dimensionsreduktion für die Earth Mover's Distanz für schnelles Multimedia-Retrieval

Tutor: Wichterich M.
Type: Diplomarbeit

Anytime Algorithms for Stream Data Mining

Tutor: Seidl T.
Type: Dissertation