東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Multi-Resolution Spatial Outlier Det...

He, Peng.

Linked to FindBook

Google Book

Amazon

博客來

Multi-Resolution Spatial Outlier Detection (MRSOD).

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Multi-Resolution Spatial Outlier Detection (MRSOD)./
Author:	He, Peng.
Description:	83 p.
Notes:	Source: Masters Abstracts International, Volume: 48-06, page: 3235.
Contained By:	Masters Abstracts International48-06.
Subject:	Geodesy. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1477253
ISBN:	9781124040714

Multi-Resolution Spatial Outlier Detection (MRSOD).
He, Peng.

Multi-Resolution Spatial Outlier Detection (MRSOD). - 83 p.

Source: Masters Abstracts International, Volume: 48-06, page: 3235.

Thesis (M.S.)--University of Maryland, Baltimore County, 2010.

Outlier detection focuses on identifying abnormal patterns from large data sets. In this thesis, we propose a novel approach for outlier detection called Multi-Resolution Spatial Outlier Detection (MRSOD) to identify spatial outliers by considering multiple levels of attributes in complex spatio-temporal datasets. Current spatial data mining techniques have primarily focused on single-resolution data where the data is at one level such that every attribute is simple and all records have the same number of attributes. However in reality spatio-temporal data is often complex such that an attribute may have additional levels of details associated with it and different spatial objects may have different attributes associated with them. We present detailed experimental results in Maryland Water Monitoring Sensors data from U.S. Geological Survey and simulated highway sensor data. Our results indicate that the MRSOD approach finds outliers with high accuracy in both the datasets.

ISBN: 9781124040714Subjects--Topical Terms:

550741
Geodesy.

Multi-Resolution Spatial Outlier Detection (MRSOD).
LDR:02133nam 2200349 4500 001 1393268
005 20110311132648.5
008 130515s2010 ||||||||||||||||| ||eng d
020 $a 9781124040714
035 $a (UMI)AAI1477253
035 $a AAI1477253
040 $a UMI $c UMI
100 1 $a He, Peng. $3 1671791
245 1 0 $a Multi-Resolution Spatial Outlier Detection (MRSOD).
300 $a 83 p.
500 $a Source: Masters Abstracts International, Volume: 48-06, page: 3235.
500 $a Advisers: Vandana Janeja; Aryya Gangopadhyay.
502 $a Thesis (M.S.)--University of Maryland, Baltimore County, 2010.
520 $a Outlier detection focuses on identifying abnormal patterns from large data sets. In this thesis, we propose a novel approach for outlier detection called Multi-Resolution Spatial Outlier Detection (MRSOD) to identify spatial outliers by considering multiple levels of attributes in complex spatio-temporal datasets. Current spatial data mining techniques have primarily focused on single-resolution data where the data is at one level such that every attribute is simple and all records have the same number of attributes. However in reality spatio-temporal data is often complex such that an attribute may have additional levels of details associated with it and different spatial objects may have different attributes associated with them. We present detailed experimental results in Maryland Water Monitoring Sensors data from U.S. Geological Survey and simulated highway sensor data. Our results indicate that the MRSOD approach finds outliers with high accuracy in both the datasets.
590 $a School code: 0434.
650 4 $a Geodesy. $3 550741
650 4 $a Information Technology. $3 1030799
650 4 $a Information Science. $3 1017528
690 $a 0370
690 $a 0489
690 $a 0723
710 2 $a University of Maryland, Baltimore County. $b Information Systems. $3 1034075
773 0 $t Masters Abstracts International $g 48-06.
790 1 0 $a Janeja, Vandana, $e advisor
790 1 0 $a Gangopadhyay, Aryya, $e advisor
790 1 0 $a Janeja, Vandana $e committee member
790 1 0 $a Gangopadhyay, Aryya $e committee member
790 1 0 $a Karabatis, George $e committee member
790 1 0 $a Chen, Zhiyuan $e committee member
790 $a 0434
791 $a M.S.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1477253