Accession Number : ADA556329


Title :   Mass Estimation and Its Applications


Descriptive Note : Final rept. 1 Mar 2010-1 Mar 2012


Corporate Author : MONASH UNIV CHURCHILL (AUSTRALIA) GIPPSLAND SCHOOL OF INFORMATION TECHNOLOGY


Personal Author(s) : Ting, Kai Ming


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a556329.pdf


Report Date : 23 Feb 2012


Pagination or Media Count : 113


Abstract : This project established that the new modeling mechanism--mass estimation--has a strong theoretical underpinning for prediction and data modeling. It showed that mass-based approaches have time and space complexities more favorable than existing approaches in a number of data mining tasks e.g., anomaly detection, clustering and information retrieval, and developed (i) a new density estimator based on mass, and (ii) a new generative classifier based on mass. The results have been published in top conferences and accepted for top journals.


Descriptors :   *DATA MINING , ALGORITHMS , CLASSIFICATION , CLUSTERING , MASS


Subject Categories : Information Science
      Cybernetics


Distribution Statement : APPROVED FOR PUBLIC RELEASE