Title | ||
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A spam filtering multi-objective optimization study covering parsimony maximization and three-way classification. |
Abstract | ||
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Display Omitted Advances on applications of multi-objective optimization to anti-SPAM filtering.Parsimony maximization of rule-based SPAM classifiers.Three-way classification balancing user effort and confidence level.Indicator-based/machine learning/decomposition-based evolutionary optimization. Classifier performance optimization in machine learning can be stated as a multi-objective optimization problem. In this context, recent works have shown the utility of simple evolutionary multi-objective algorithms (NSGA-II, SPEA2) to conveniently optimize the global performance of different anti-spam filters. The present work extends existing contributions in the spam filtering domain by using three novel indicator-based (SMS-EMOA, CH-EMOA) and decomposition-based (MOEA/D) evolutionary multi-objective algorithms. The proposed approaches are used to optimize the performance of a heterogeneous ensemble of classifiers into two different but complementary scenarios: parsimony maximization and e-mail classification under low confidence level. Experimental results using a publicly available standard corpus allowed us to identify interesting conclusions regarding both the utility of rule-based classification filters and the appropriateness of a three-way classification system in the spam filtering domain. |
Year | DOI | Venue |
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2016 | 10.1016/j.asoc.2016.06.043 | Appl. Soft Comput. |
Keywords | Field | DocType |
Spam filtering,Multi-objective optimization,Parsimony,Three-way classification,Rule-based classifiers,SpamAssassin | Data mining,Mathematical optimization,Computer science,Filter (signal processing),Multi-objective optimization,Artificial intelligence,Classifier (linguistics),Optimization problem,Maximization,Machine learning | Journal |
Volume | Issue | ISSN |
48 | C | 1568-4946 |
Citations | PageRank | References |
9 | 0.54 | 29 |
Authors | ||
6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Vítor Basto Fernandes | 1 | 21 | 5.60 |
Iryna Yevseyeva | 2 | 72 | 14.98 |
José Ramon Méndez | 3 | 254 | 17.69 |
Jiaqi Zhao | 4 | 117 | 15.77 |
Florentino Fdez-Riverola | 5 | 464 | 57.16 |
Michael T. M. Emmerich | 6 | 247 | 22.74 |