An Integrated Framework to Access and Mine Distributed Heterogeneous Data Streams with Uncertainty

Abstract

In summary, this DOD agreement not only allowed us to perform a comprehensive study on data stream mining and its promising application on biomedical domains, but also foster and enrich the research experiences of the under-represented minority students at Xavier, and open opportunities for them in graduate schools or future careers in IT industries. Moreover, this support has motivated us to explore other important aspects of mining streaming data, such as anomaly or outlier detection, which is worth more years of further investigation as described in the PI s proposal submitted to the Fiscal Year 2015 Department of Defense Research and Education Program for Historically Black Colleges and Universities and Minority-Serving Institutions (HBCU/MI) . Below are the key statistics achieved by our project. Peer-reviewed publications: 11 from the PI s lab and 42 from the Co-PI's site.

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Document Details

Document Type
Technical Report
Publication Date
May 13, 2015
Accession Number
ADA625561

Entities

People

  • Kun Zhang

Organizations

  • Xavier University of Louisiana

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Anomaly Detection
  • Cell Line
  • Change Detection
  • Computer Science
  • Data Mining
  • Department Of Defense
  • Detection
  • Dimensionality Reduction
  • Education
  • Engineering
  • Feature Selection
  • Machine Learning
  • New York
  • Prostate Cancer
  • Social Networks
  • Statistical Analysis
  • Students

Readers

  • Research Science/Academic Research
  • Seismology

Technology Areas

  • Biotechnology