An interactive hybrid system for identifying and filtering unsolicited email

Author

del Castillo, M.D. ; Serrano, J.I.

Author_Institution

Inst. de Automatica Ind., CSIC, Madrid, Spain

fYear

2005

fDate

19-22 Sept. 2005

Firstpage

814

Lastpage

815

Abstract

This paper presents a system for automatically detecting and filtering unsolicited electronic messages. The underlying filtering method is based on email origin and content. A heuristic knowledge base formed by spam words is extracted from labelled emails by a finite state automata. The processing of three parts of every email by a single Bayesian filter and the integration of the every part classification allows to achieve a maximum performance goal. The system is dynamic and interactive and evolves from the evolution of spam by incremental machine learning.

Keywords

Bayes methods; finite automata; information filtering; interactive systems; knowledge based systems; learning (artificial intelligence); unsolicited e-mail; Bayesian filter; finite state automata; heuristic knowledge base; incremental machine learning; interactive hybrid system; spam word; unsolicited electronic message; unsolicited email filtering; unsolicited email identification; Bayesian methods; Costs; Filtering; Filters; Learning automata; Machine learning; Pattern analysis; Performance analysis; Unsolicited electronic mail; Vocabulary;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on

Print_ISBN

0-7695-2415-X

Type

conf

DOI

10.1109/WI.2005.31

Filename

1517964