Back to Results
First PageMeta Content
Geostatistics / Multivariate statistics / Cluster analysis / Machine learning / Association rule learning / Spatial database / Geographic information system / Statistics / Data mining / Data analysis


Mining Regional Knowledge in Spatial Datasets Wei Ding Christoph. F. Eick Computer Science Department, University of Houston, TX {wding, ceick}@uh.edu Abstract
Add to Reading List

Document Date: 2008-07-16 17:41:23

Open Document

File Size: 599,48 KB

Share Result on Facebook

City

Grid / /

/

Event

Environmental Issue / /

Facility

University of Houston / University of California / /

IndustryTerm

agglomerative clustering algorithms / it to realworld applications / association rule mining algorithms / grid-based clustering algorithms / immediate applications / association rule mining / spatial data mining / mining / Density-based algorithms / hill climbing algorithm / /

Movie

D. 4 / /

NaturalFeature

Texas Gulf Coast / Gulf Coast / /

Organization

Regional association / F. Eick Computer Science Department / University of California / Santa Barbara / Environment Protection Agency / University of Houston / Environmental Protection Agency / /

Person

Ding Christoph / Proc / Wei Ding / /

Position

representative / /

ProvinceOrState

Texas / California / /

Region

Texas Gulf Coast / South Texas / south Gulf Coast / /

Technology

association rule mining algorithms / hill climbing algorithm / clustering algorithms / key technology / density-based algorithm / clustering algorithm / grid-based clustering algorithms / Density-Based Algorithms / data mining / four clustering algorithms / Grid-based Algorithms / agglomerative clustering algorithms / 2.4 Clustering Algorithms / /

SocialTag