Title :
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
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;
Conference_Titel :
Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on
Print_ISBN :
0-7695-2415-X