An Efficient Approach to
Similarity-Based Retrieval
on Top of Relational Databases

Jrgen Schumacher1 and Ralph Bergmann2

1 tec:inno GmbH

Sauerwiesen 2, D67661 Kaiserslautern, Germany
schurmacher@tecinno.com
2 Center for Learning Systems and Applications (LSA), University of Kaiserslautern

Postfach 3049, D-67653 Kaiserslautern, Germany
bergmann@informatik.uni-kl.de



Abstract. This paper presents an approach to realize a case retrieval
engine on top of a relational database. In a nutsheli the core idea is to
approximate a similarity-based retrieval with SQL-queries. The approach
avoids duplicating the case data or compiling index structures and is
therefore ideal for huge case bases which are often subject to changes. The
presented approach is fully implemented as part of the commercial CBR
toolbox orenge and the experimental evaluation demonstrates impressive
retrieval behaviour.
References

1.	S. Berchtold, B. Erti, D. A. Keim, H.-P. Kriegel, and T. Seidi. Fast nearest neighbor
search in high-dimensional space. In Proc. 14th Int. Conf. on Data Engineering
(ICDE98), pages 209218, 1998.
2.	S. Berchtold, D. A. Keim, and H.-P. Kriegel. The x-tree: An index structure for
high-dimensional data. In Proc. 22nd Int. Conf on Very Large Data Bases, pages
2839, 1996.
3.	R. Bergmann, S. Breen, M. Gker, M. Manago, and S. Wess. Developing Industrial
Case-Based Reasoning Applications: The INRECA Methodology. Lecture Notes in
Artificial Intelligence, State-of-the-Art-Survey, LNAI 1612. Springer Verlag, 1999.
4.	M. Donner and T. Roth-Berghofer. Architectures for integration CBR-systems with
databases for e-commerce. In 7th German Workshop on Case Based Reasoning
(GWCBR99), 1999.
5.	H. Schimazu, H. Kitano, and A. Shibata. Retrieving cases from relational
databases: Another strike toward coporate-wide case-based systems. In Proceedings
of the 13th International Joint Conference in Artificial Intelligence (IJCAI93),
1993.
6.	S. Schmitt and R. Bergmann. Applying case-based reasoning technology for product 
selection and customization in electronic commerce environments. In 12th Bled
Electronic Commerce Conference., 1999.
7.	T. Seidl and H.-P. Kriegel. Optimal multi-step k-nearest neighbor search. In Proc.
ACM SIGMOD Int. Conf. on Management of Data, pages 154165, 1998.
8.	W. Wilke. Knowledge Management for Intelligent Sales Support in Electronic
Commerce. DISKI 213. Infix Verlag, 1999.
9.	W. Wilke, M. Lenz, and S. Wess. Intelligent sales support with CBR. In M. Lenz,
B. Bartsch-Sprl, H.-D. Burkhard, and S. Wess, editors, Case-Based Reasoning
Technology: From Foundations to Applications, pages 91113. Springer Verlag,
1998.
