Prof. Dr. Felix Naumann
Hasso-Plattner-Institut
für Softwaresystemtechnik
Prof.-Dr.-Helmert-Str. 2-3
D-14482 Potsdam, Germany
Paper accepted at SSDBM
Proceedings of the 24th International Conference on Scientific and Statistical Database...
JWS Article Accepted
Integrating Open Government Data with Stratosphere for more Transparency Arvid Heise and Felix...
LREC Paper Accepted
The eighth international conference on Language Resources and Evaluation (LREC), Istanbul,...
Daniel Rinser wins award for his masters thesis
IQ Best Master Degree Wettbewerb der Deutschen Gesellschaft für Informations- und Datenqualität e....
HPI TV releases video about GovWILD
See the new video about our Government Data Integration platform GovWILD.
Tool voidGen released
As part of our winning submission at the 2010 Billion Triple Challenge at the International...
ICDE Paper Accepted
28th IEEE International Conference on Data Engineering (ICDE) Washington, DC, USA Adaptive...
Similarity search refers to the task of finding objects that are similar to a given query in a set of objects. Common DBMS only provide means to efficiently find exact matches to a given query. In case of typing errors, omitted or transposed attribute values or other typical data quality problems in queries, exact search algorithms fail to find all relevant objects in the queried data set.
In this project, we survey existing and develop new algorithms for effective and efficient similarity search. Effective similarity search can be achieved by defining a similarity measure that is well-suited for the given domain. For efficient similarity search, an index structure is required that precomputes similarities of objects to answer queries as fast as possible.
This project is supported by Schufa Holding AG.
Project members:
Publications
| 1. |
Dustin Lange and Felix Naumann.
Efficient Similarity Search: Arbitrary Similarity Measures, Arbitrary Composition.
In
Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM),
Glasgow, Scotland, UK,
2011.
|
| 2. |
Dustin Lange and Felix Naumann.
Frequency-aware Similarity Measures.
In
Proceedings of the 20th ACM Conference on Information and Knowledge Management (CIKM),
pages 243–248,
Glasgow, Scotland, UK,
2011.
|