Deakin University
Browse

File(s) under permanent embargo

Spamcooling : a parallel heterogeneous ensemble spam filtering system based on active learning techniques

journal contribution
posted on 2010-06-01, 00:00 authored by J Wang, K Gao, Huy Quan Vu
Anti-spam technology is developing rapidly in recent years. With the emerging applications of machine learning in diverse fields, researchers as well as manufacturers around the world have attempted a large number of related algorithms to prevent spam. In this paper, we designed an effective anti-spam protection system, SpamCooling, based on the mechanism of active learning and parallel heterogeneous ensemble learning techniques. The system adopts a batch method to filter spam and can be easily incorporated with existing mail clients (MUA). It can actively obtain user feedbacks for providing users with personalized spam filtering experiences. The parallel heterogeneous ensemble method can help system achieve high spam detection rate as well as low ham misclassification rate.

History

Journal

Journal of convergence information technology

Volume

5

Issue

4

Pagination

90 - 102

Publisher

Advanced Institute of Convergence IT

Location

Korea

ISSN

1975-9320

eISSN

2233-9299

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC