Univ.-Prof. Dipl. Ing. Nikolaus Augsten, PhD

Professor

Jakob-Haringer-Str. 2 (Office 1.16)
5020 Salzburg, Austria

Tel: +43-(0)662-8044-6347
Fax: +43-(0)662-8044-172

I was previously affiliated to the Faculty of Computer Science at the Free University of Bozen-Bolzano. In 2010/2011 I visited Prof. Alfons Kemper at Technische Universität München (TUM, Munich, Germany) for 6 months (my website at Technische Universität München). In 2005/2006 I spent 6 months at Washington State University with Prof. Curtis Dyreson (now at Utah State University). I received my PhD from Aalborg University, Denmark, in 2008. My supervisor was Prof. Michael Böhlen (University of Zurich); the assessment committee was composed of Prof. Christian S. Jensen (University of Aalborg, Denmark), Prof. Peter Buneman (University of Edinburgh, UK) and Prof. Stefano Ceri (Politecnico di Milano, Italy).

Main Research Interests

My current research interests include data-centric applications in database and information systems with a particular focus on approximate matching techniques for complex data structures, efficient index structures for distance computations, and similarity search in massive data collections. My research is triggered by problems that arise in concrete applications, for example, e-government and XML search engines.

Selected Publications

  1. W. Mann, N. Augsten, P. Bouros. An Empirical Evaluation of Set Similarity Join Techniques. In The Proceedings of the VLDB Endowment (PVLDB 2016),
    PDF and source code
  2. M. Pawlik, N. Augsten. Efficient Computation of the Tree Edit Distance. In ACM Transactions on Database Systems (TODS), 40(1):1-40, 2015.
    PDF, Abstract
  3. N. Augsten, A. Miraglia, T. Neumann, A. Kemper. On-the-Fly Token Similarity Joins in Relational Databases. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD-14), Snowbird, UT, USA. June 2014. ACM.
    PDF, all downloads
  4. S. Helmer, N. Augsten, M. Böhlen. Information-theoretic approaches for measuring the structural similarity of semistructured documents. In The VLDB Journal (VLDBJ). 21(5):677-702, 2012. DOI: 10.1007/s00778-012-0263-0. (GRIN*: A)
    PDF, Abstract
  5. B. Gufler, N. Augsten, A. Reiser, A. Kemper. Load Balancing in MapReduce Based on Scalable Cardinality Estimates. In Proceedings of the International Conference on Data Engineering (ICDE-12), Washington, DC, USA. April 2012. IEEE Computer Society. (GRIN*: A)
    PDF, Abstract
  6. M. Pawlik, N. Augsten. RTED: A Robust Algorithm for the Tree Edit Distance. In PVLDB 5(4):334-345, 2011 (VLDB-12). (GRIN*: A)
    PDF, Abstract
  7. N. Augsten, M. Böhlen, C. Dyreson, and J. Gamper. Windowed pq-Grams for Approximate Joins of Data-Centric XML. In The VLDB Journal (VLDBJ). 21(4):463-488, 2012. DOI: 10.1007/s00778-011-0254-6. (GRIN*: A)
    PDF, Abstract
  8. N. Augsten, D. Barbosa, M. Böhlen, and T. Palpanas. Efficient top-k approximate subtree matching in small memory. In IEEE Transactions on Knowledge and Data Engineering (TKDE). 23(8): 1123-1137, 2011. (GRIN*: A)
    PDF, Abstract
  9. N. Augsten, D. Barbosa, M. Böhlen, and T. Palpanas. TASM: Top-k approximate subtree matching. In Proceedings of the International Conference on Data Engineering (ICDE-10), pages 353-364, Long Beach, California, USA, March 2010. IEEE Computer Society. (acceptance rate: 12.9%, GRIN*: A)
    ICDE 2010 Best Paper Award
    PDF, all downloads
  10. N. Augsten, M. Böhlen, and J. Gamper. The pq-Gram Distance between Ordered Labeled Trees. In ACM Transactions on Database Systems (TODS), 35(1):1-36, 2010. (GRIN*: A)
    PDF, all downloads
  11. N. Augsten, M. Böhlen, C. Dyreson, and J. Gamper. Approximate Joins for Data Centric XML. In Proceedings of the International Conference on Data Engineering (ICDE-08), Cancún, Mexico, April 2008. IEEE Computer Society. (acceptance rate: 12.1%, GRIN*: A)
    PDF, all downloads
  12. N. Augsten, M. Böhlen, and J. Gamper. An incrementally maintainable index for approximate lookups in hierarchical data. In Proceedings of the 32th International Conference on Very Large Databases (VLDB-06), pages 247-258, Seoul, Korea, Sep. 2006. ACM Press. (acceptance rate: 13.2%, GRIN*: A)
    PDF, all downloads
  13. N. Augsten, M. Böhlen, and J. Gamper. Approximate matching of hierarchical data using pq-grams. In Proceedings of the 31th International Conference on Very Large Databases (VLDB-05), pages 141-152, Trondheim, Norway, Aug.-Sep. 2005. ACM Press. (acceptance rate: 16.5%, GRIN*: A)
    PDF, all downloads
*GRIN: Journal and conference ranking by the Italian Association of Computer Scientists.

Source Code Downloads

Courses at other Universities

Lab Database Systems (Free University of Bozen-Bolzano, WS 2012)

Similarity Search (Free University of Bozen-Bolzano, SS 2012)
This course will discuss similarity search techniques for flat strings and hierarchical data (for example, XML). Selected methods will be presented, their effectiveness and efficiency will be discussed. Filtering techniques to improve the efficiency will be introduced. The students will implement similarity joins in a relational database management system.
(Course evaluation: WS 2009, SS 2012)

Database Management and Tuning (Free University of Bozen-Bolzano, SS 2012)
This course will give an in-depth understanding of the features that off-the-shelf database management systems offer, in particular with respect to system performance. This knowledge is used to tune the database system and its environment: dimension the hardware for the database system, write efficient queries, set effective indexes, communicate with the database efficiently, and diagnose performance problems.
(Course evaluation: SS 2010, SS 2011, SS 2012)

Scalable Similarity Search Algorithms (Technische Universität München, WS 2010)
(Course evaluation: WS 2010)

Approximation: Theory and Algorithms (Free University of Bozen-Bolzano, SS 2009)
This course will discuss approximate matching techniques for flat strings and hierarchical data. Selected methods will be presented, their effectiveness and efficiency will be discussed. Filtering techniques to improve the efficiency will be introduced. The students will implement approximate matching techniques in a relational database management system.
(Course evaluation: SS 2007, SS 2008, SS 2009)