Name
Abstract | ||
|---|---|---|
Spam filtering is a research hotspot of information security. For the weak fault-tolerant ability of traditional filtering methods, an approach to spam filtering based on alpha - positive-region of decision-theoretic rough set (DTRS) is developed. Firstly, alpha -positive-region attribute reduction theorem is adopted to reduce email attributes. Then, according to the minimum risk Bayesian decision theory, a three-way decision, named spam, doubt and non-spam, is realized by depicting the undecided emails using boundary region of DTRS. The simulation results show that this approach is effective and helpful to improve the performance of spam filtering. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/FSKD.2013.6816180 | 2013 10TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD) |
Keywords | Field | DocType |
spam filtering, decision-theoreic rough sets, alpha - positive-region, Bayesian decision theory | Bag-of-words model,Data mining,Computer science,Artificial intelligence,Probabilistic logic,Bayes estimator,Pattern recognition,Support vector machine,Filter (signal processing),Information security,Rough set,Hotspot (Wi-Fi),Machine learning | Conference |
Citations | PageRank | References |
1 | 0.35 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chunsheng Zhao | 1 | 1 | 0.35 |
| Wei Zeng | 2 | 118 | 9.88 |
| Mai Jiang | 3 | 1 | 0.35 |
| Zhiyong He | 4 | 1 | 0.35 |