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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Enache, A.-C. Patriciu, V.V. |
| Copyright Year | 2014 |
| Description | Author affiliation: Fac. of Autom. Control & Comput. Sci., Politeh. Univ., Bucharest, Romania (Enache, A.-C.) || Comput. Sci., Mil. Tech. Acad., Bucharest, Romania (Patriciu, V.V.) |
| Abstract | Web Spam, or Spamdexing, is a form of Search Engine Optimization(SEO) spamming that hinders the efficiency of search engines. These types of exploits use unethical methods in order to place a web page into the first rank. Sabotaging the quality of the results retrieved by search engines can lead users to mistrust the search engine provider. Moreover, spam websites can be a starting point for phishing or malware attacks. Over the last decade Web Spamming has become an important problem. This paper shows a spam host detection approach that uses swarm intelligence. We test our model on two datasets (WEBSPAM-UK2011 and WEBSPAM-UK2007) and show that it can obtain a good accuracy. Moreover, we compared our approach with other popular classifiers (C4.5, SVM and Logistic Regression ) and empirically demonstrated that it can outperform them in some cases. |
| Sponsorship | IEEE Romania Sect. |
| Starting Page | 1 |
| Ending Page | 4 |
| File Size | 783355 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781479923854 |
| DOI | 10.1109/ICComm.2014.6866669 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-05-29 |
| Publisher Place | Romania |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Training Support vector machines Accuracy Ant colony classification algorithm Unsolicited electronic mail Host spam Feature extraction Swarm intelligence Data mining Particle swarm optimization |
| Content Type | Text |
| Resource Type | Article |
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