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):

Report Date:

2012-02-23

Pagination or Media Count:

113.0

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.

Subject Categories:

  • Information Science
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE