Detecting spam web pages through content analysis
Proceedings of the 15th international conference on World Wide Web
Improving web spam classifiers using link structure
AIRWeb '07 Proceedings of the 3rd international workshop on Adversarial information retrieval on the web
Know your neighbors: web spam detection using the web topology
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Boosting the Performance of Web Spam Detection with Ensemble Under-Sampling Classification
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04
Link based small sample learning for web spam detection
Proceedings of the 18th international conference on World wide web
Survey on web spam detection: principles and algorithms
ACM SIGKDD Explorations Newsletter
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Web spam detection has become one of the top challenges for the Internet search industry. Instead of using some heuristic rules, we propose a feature re-extraction strategy to optimize the detection result. Based on the predicted spamicity obtained by the preliminary detection, through the host level web graph, three types of features are extracted. Experiments on WEBSPAM-UK2006 benchmark show that with this strategy, the performance of web spam detection can be improved evidently.