Linear clustering of objects with multiple attributes
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
A comparison of spatial query processing techniques for native and parameter spaces
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
OPTICS: ordering points to identify the clustering structure
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
CLARANS: A Method for Clustering Objects for Spatial Data Mining
IEEE Transactions on Knowledge and Data Engineering
Laying Out Sparse Graphs with Provably Minimum Bandwidth
INFORMS Journal on Computing
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In the consumer market, there has been an increasing interest in portable navigation systems in the last few years. These systems usually work on digital map databases stored on SD cards. As the price for these SD cards heavily depends on their capacity and as digital map databases are rather space-consuming, relatively high hardware costs go along with digital map databases covering large areas like Europe or the USA. In this paper, we propose new techniques for the compact storage of the most important part of these databases, i.e., the road network data. Our solution applies appropriate techniques from combinatorial optimization, e.g., adapted solutions for the minimum bandwidth problem, and from data mining, e.g., clustering based on suitable distance measures. In a detailed experimental evaluation based on real-world data, we demonstrate the characteristics and benefits of our new approaches.