A fast voronoi-diagram algorithm with quaternary tree bucketing
Information Processing Letters
GeoMiner: a system prototype for spatial data mining
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Foundations of statistical natural language processing
Foundations of statistical natural language processing
ROCK: a robust clustering algorithm for categorical attributes
Information Systems
Geospatial mapping and navigation of the web
Proceedings of the 10th international conference on World Wide Web
An introduction to spatial database systems
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
Finding Aggregate Proximity Relationships and Commonalities in Spatial Data Mining
IEEE Transactions on Knowledge and Data Engineering
Incremental Clustering for Mining in a Data Warehousing Environment
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Discovery of Spatial Association Rules in Geographic Information Databases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
STING: A Statistical Information Grid Approach to Spatial Data Mining
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Navigating massive data sets via local clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Fast mining of spatial collocations
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering Colocation Patterns from Spatial Data Sets: A General Approach
IEEE Transactions on Knowledge and Data Engineering
A Joinless Approach for Mining Spatial Colocation Patterns
IEEE Transactions on Knowledge and Data Engineering
Clustering Using a Similarity Measure Based on Shared Near Neighbors
IEEE Transactions on Computers
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We considered co-location pattern mining algorithm that uses the Voronoi diagram. In general, the density of spatial objects is much higher in urban areas than in rural areas. The proposed algorithm is suitable for such unevenly distributed database. We have applied the co-location pattern mining algorithm for real spatial databases and show the capability of the proposed algorithm for a real spatial database. We also applied our methods for analysing web pages that contains spatial information. There are many web pages that contain spatial information such as addresses, postal codes, and telephone numbers. Most of the spatial information in web pages are location information and is unevenly distributed. We collected such web pages by web-crawling programs. For each page determined to contain location information, we apply geocoding techniques to compute geographic coordinates, such as latitude-longitude pairs. Next, we augment the location information with keyword descriptors extracted from the web page contents. We then apply co-location mining on the augmented location information.