DISCOVERY OF CLUSTERS IN SPATIAL DATABASES
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University of Cincinnati / OhioLINK
2003
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ndltd-OhioLink-oai-etd.ohiolink.edu-ucin10697012372021-08-03T06:09:31Z DISCOVERY OF CLUSTERS IN SPATIAL DATABASES BATRA, SHALINI Computer Science spatial data mining clustering quad-tree clusters Spatial data mining is discovery of interesting relationships and Characteristics that may exist implicitly in databases. Data mining systems aim to discover patterns, find unexpected results and correlations and extract useful information recorded in databases. The branch of data mining that deals with location of data is spatial data mining. Spatial data mining is a highly demanding field and has huge data that is collected from various applications like Remote Sensing, Geographical Information Systems (GIS), Medical Equipments, Video Images, Computer Cartography, Environmental Assessment and Planning. In this thesis we consider spatial databases and discover spatial clusters of similar characteristics. The clusters discovered are at different levels of granularity. There has been relevant work done in the area of spatial data mining and there exist algorithms for finding clusters in spatial databases. We find regions of similar characteristics in spatial databases with no prior information from the user. We use quad tree data structure to summarize spatial locality. In a quad tree, there are always four children per node and number of leaf nodes are always in power of 4. This structure allows effective information traversal in the tree. We consider each data point to be a leaf node in quad tree. We define parameters to measure similar characteristics among nodes. Each node contains interesting spatial facts discovered for the sub tree lying under it. Further, we develop an algorithm to simultaneously examine any associations across the clusters formed by different attributes in the same spatial context. 2003 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin1069701237 http://rave.ohiolink.edu/etdc/view?acc_num=ucin1069701237 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |
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NDLTD |
| language |
English |
| sources |
NDLTD |
| topic |
Computer Science spatial data mining clustering quad-tree clusters |
| spellingShingle |
Computer Science spatial data mining clustering quad-tree clusters BATRA, SHALINI DISCOVERY OF CLUSTERS IN SPATIAL DATABASES |
| author |
BATRA, SHALINI |
| author_facet |
BATRA, SHALINI |
| author_sort |
BATRA, SHALINI |
| title |
DISCOVERY OF CLUSTERS IN SPATIAL DATABASES |
| title_short |
DISCOVERY OF CLUSTERS IN SPATIAL DATABASES |
| title_full |
DISCOVERY OF CLUSTERS IN SPATIAL DATABASES |
| title_fullStr |
DISCOVERY OF CLUSTERS IN SPATIAL DATABASES |
| title_full_unstemmed |
DISCOVERY OF CLUSTERS IN SPATIAL DATABASES |
| title_sort |
discovery of clusters in spatial databases |
| publisher |
University of Cincinnati / OhioLINK |
| publishDate |
2003 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1069701237 |
| work_keys_str_mv |
AT batrashalini discoveryofclustersinspatialdatabases |
| _version_ |
1719431843599613952 |