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With the development of the Internet, it is vital for the security of the Internet to detect web-based anomalies. Clustering based on feature extraction by manually has been verified as a significant way to detect new anomalies. But the presentations of these features can't express semantic information of the URLs. In addition, few studies try to cluster the anomalies into specific types like SQL-injection...
Spam web pages have posed great challenges to the development of search engines. The content spam is among the commonly used. Along with the development of Internet technologies, the content spam is difficult to detect. The current detection methods for the web page using content spam technique primarily rely on the statistical features, which has obvious limitations. In this article, a spam webpage...
Internet is becoming an increasingly important platform for ordinary life and work. It is expected that keyword extraction can help people quickly find hot spots on the web, since keywords in a document provide important information about the content of the document. In this paper, we propose to use text clustering method based on semi-supervised learning to get focuses of social topics in a large...
Binary semantic relation extraction is particularly useful for various NLP and Web applications. Currently Web-based methods and Linguistic-based methods are two types of leading methods for semantic relation extraction task. With a novel view on integrating linguistic analysis on local text with Web frequent information, we propose a multi-view co-clustering approach for semantic relation extraction...
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