Abstract
This paper presents an enhanced extension of the Vague Query System (VQS) [14], [15] to solve complex vague queries more efficiently and generally. The VQS is an extension to conventional database systems and can work on top of them to return records semantically close to user’s query. It represents semantic information of arbitrary attributes by mapping them to the Euclidean space and this information is invisible to the users. Answering a complex vague query requires searching on multiple feature spaces of attributes and these spaces are usually multidimensional. The proposed approach in [15] is not general and has weaknesses lead to degenerate performance of the system. The new approach introduced in this paper overcomes all those defects and significantly improves the search performance in both concepts of CPU- and IO-cost. Our experiments on uniformly distributed data sets, which are managed by the SH-trees [6], have proven the advantages of this new approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
R. Baeza-Yates, B. Ribeiro-Neto. Modern Information Retrieval. ACM Press Books, 1999
S. Berchtold, C. Böhm, D.A. Keim, H.P. Kriegel. A Cost Model for Nearest Neighbor Search in High-Dimensional Data Space. Proc. of 6th ACM SIGACT-SIGMOD-SIGART symposium on Principles of Database Systems, 1997
K. Böhm, M. Mlivoncic, H-J. Schek, R. Weber: Fast Evaluation Techniques for Complex Similarity Queries. VLDB 2001
S. Chaudhuri, L. Gravano. Optimizing Queries over Multimedia Repositories. Proc. of ACM SIGMOD International Conference on Management of Data, 1996
S. Chaudhuri, L. Gravano. Evaluating Top-k Selection Queries. VLDB 1999
T.K. Dang, J. Kueng, R. Wagner. The SH-tree: A Super Hybrid Index Structure for Multidimensional Data. Proc. of the 12th DEXA, Springer Verlag, LNCS 2113, ISBN 3-540-42527-6, pp. 340–349, Munich, Germany, Sep. 3–7, 2001
T.K. Dang, J. Küng, R. Wagner. Efficient Processing of k-Nearest Neighbor Queries in Spatial Databases with the SH-tree. Proc. of the 3rd iiWAS, ISBN 3-85403-150-5, pp. 425–435, Linz, Austria, Sep. 10–12, 2001
R. Fagin. Combining Fuzzy Information from Multiple Systems. Proc. of the 15th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, June 1996
U. Guentzer, W.T. Balke, W. Kiessling. Optimizing Multi-Feature Queries for Image Databases. VLDB 2000
G. Graefe. Query Evaluation Techniques for Large Databases. ACM Computing Surveys (CSUR), Vol. 25, Issue 2, June 1993
A. Henrich, G. Robbert. Combining Multimedia Retrieval and Text Retrieval to Search Structured Documents in Digital Libraries. Pre-Proc. of the 1st DELOS Workshop on Information Seeking, Searching and Querying in Digital Libraries, Zürich, Switzerland, December, 2000
G.R. Hjaltason, H. Samet. Ranking in Spatial Databases. Advances in Spatial Databases-4th Symposium, SSD’95, LNCS 951, Springer-Verlag, Berlin, 1995
T. Ichikawa, M. Hirakawa. ARES: A Relational Database with the Capability of Performing Flexible Interpretation of Queries. IEEE Trans. on Software Engineering, Vol. 12, No. 5, 1986
J. Kueng, J. Palkoska. VQS-A Vague Query System Prototype. DEXA 1997. IEEE Computer Society Press, Toulouse, France, September 1997
J. Kueng, J. Palkoska. An Incremental Hypercube Approach for Finding Best Matches for Vague Queries. DEXA 1999. LNCS, ISBN 3-540-66448-3, 1999
A. Motro. VAGUE: A User Interface to Relational Database that Permits Vague Queries. ACM Trans. on Office Information Systems, Vol 6, No. 3, July 1988
S. Nepal, M.V. Ramakrishna. Query Processing Issues in Image (Multimedia) Databases. Proc. of the 15th ICDE, Sydney, Australia, 1999
M. Ortega, Y. Rui, K. Chakrabarti, S. Mehrotra, T.S. Huang. Supporting Similarity Queries in MARS. Proc. of the 5th ACM International Conference on Multimedia, 1997
U. Pfeifer, N. Fuhr. Efficient Processing of Vague Queries Using a Data Stream Approach. Proc. of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 1995
N. Roussopoulos, S. Kelley, F. Vincent. Nearest Neighbor Queries. Proc. of ACM SIGMOD International Conference on Management of Data, 1995
E.L. Wimmers, L.M. Haas, M.T. Roth, C. Braendli. Using Fagin’s Algorithm for Merging Ranked Results in Multimedia Middleware. Proc. of the 4th COOPIS, Scotland, 1999
R. Weber, H.J. Schek, S. Blott. A Quantitative Analysis and Performance Study for Similarity-Search Methods in High-Dimensional Spaces. VLDB 1998
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dang, T.K., Küng, J., Wagner, R. (2002). ISA - An Incremental Hyper-sphere Approach for Efficiently Solving Complex Vague Queries. In: Hameurlain, A., Cicchetti, R., Traunmüller, R. (eds) Database and Expert Systems Applications. DEXA 2002. Lecture Notes in Computer Science, vol 2453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46146-9_80
Download citation
DOI: https://doi.org/10.1007/3-540-46146-9_80
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44126-7
Online ISBN: 978-3-540-46146-3
eBook Packages: Springer Book Archive