Introduction to algorithms
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Mining optimized association rules for numeric attributes
Journal of Computer and System Sciences
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
ROCK: a robust clustering algorithm for categorical attributes
Information Systems
Communications of the ACM
Geospatial mapping and navigation of the web
Proceedings of the 10th international conference on World Wide Web
Data Mining with optimized two-dimensional association rules
ACM Transactions on Database Systems (TODS)
Mining frequent neighboring class sets in spatial databases
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Extracting Spatial Knowledge from the Web
SAINT '03 Proceedings of the 2003 Symposium on Applications and the Internet
Navigating massive data sets via local clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Optimized transitive association rule: mining significant stopover between events
Proceedings of the 2005 ACM symposium on Applied computing
Clustering Using a Similarity Measure Based on Shared Near Neighbors
IEEE Transactions on Computers
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We considered a spatial data mining method that extracts spatial knowledge by computing geometrical patterns from web pages and access log files of HTTP servers. There are many web pages that contain location information such as addresses, postal codes, and telephone numbers. We can collect 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 spatial data mining techniques on the augmented location information. In addition, we can use hyperlinks and access log files to find linkage between pages with location information to derive spatial knowledge.