Data mining for selective visualization of large spatial datasets
- 26 June 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 10823409,p. 41-48
- https://doi.org/10.1109/tai.2002.1180786
Abstract
Data mining is the process of extracting implicit, valuable, and interesting information from large sets of data. Visualization is the process of visually exploring data for pattern and trend analysis, and it is a common method of browsing spatial datasets to look for patterns. However the growing volume of spatial datasets make it difficult for humans to browse such datasets in their entirety, and data mining algorithms are needed to filter out large uninteresting parts of spatial datasets. We construct a web-based visualization software package for observing the summarization of spatial patterns and temporal trends. We also present data mining algorithms for filtering out vast parts of datasets for spatial outlier patterns. The algorithms were implemented and tested with a real-world set of Minneapolis-St. Paul (Twin Cities) traffic data.Keywords
This publication has 9 references indexed in Scilit:
- Detecting graph-based spatial outliersPublished by Association for Computing Machinery (ACM) ,2001
- Discovering Spatial Co-location Patterns: A Summary of ResultsPublished by Springer Nature ,2001
- Spatial databases-accomplishments and research needsIEEE Transactions on Knowledge and Data Engineering, 1999
- Maintenance of data cubes and summary tables in a warehouseACM SIGMOD Record, 1997
- The KDD process for extracting useful knowledge from volumes of dataCommunications of the ACM, 1996
- Interactive High-Dimensional Data VisualizationJournal of Computational and Graphical Statistics, 1996
- Discovery of spatial association rules in geographic information databasesPublished by Springer Nature ,1995
- VisDB: database exploration using multidimensional visualizationIEEE Computer Graphics and Applications, 1994
- Identification of OutliersPublished by Springer Nature ,1980