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As botnets continue to proliferate and grow in sophistication, so does the need for more advanced security solutions to effectively detect and defend against such attacks. In particular, botnets such as Conficker have been known to encrypt the communication packets exchanged between bots and their command-and-control server, making it costly for existing(More)
This paper introduces a new discriminative learning technique for link prediction based on the matrix alignment approach. Our algorithm automatically determines the most predictive features of the link structure by aligning the adjacency matrix of a network with weighted similarity matrices computed from node attributes and neighborhood topological(More)
Social media are becoming increasingly popular and have attracted considerable attention from spammers. Using a sample of more than ninety thousand known spam Web sites, we found between 7% to 18% of their URLs are posted on two popular social media Web sites, <b>digg.com</b> and <b>delicious.com</b>. In this paper, we present a co-classification framework(More)
—Within networks there is often a pattern to the way nodes link to one another. It has been shown that the accuracy of node classification can be improved by using the link data. One of the challenges to integrating the attribute and link data, though, is balancing the influence that each has on the classification decision. In this paper we present a matrix(More)
Social bookmarking tools enable users to save URLs forfuture reference, to create tags for annotating Web pages, and to share Web pages they found interesting with others. This paper presents a case study on the application of link mining to a social bookmarking Web site called del.icio.us. We investigated the user bookmarking and tagging behaviors and(More)
Most previous studies on active learning focused on the problem of model selection, i.e., how to identify the optimal classification model from a family of predefined models using a small, carefully selected training set. In this paper, we address the problem of active algorithm selection. The goal of this problem is to efficiently identify the optimal(More)
Allergic diseases, such as asthma and allergic rhinitis, are common. Therefore, the discovery of therapeutic drugs for these conditions is essential. Methyleugenol (ME) is a natural compound with antiallergic, antianaphylactic, antinociceptive, and anti-inflammatory effects. This study examined the antiallergic effect of ME on IgE-mediated inflammatory(More)
Traditional Chinese Medicine Preparations (TCMPs) contain massive numbers of ingredients responsible for their multiple efficacies. An absorption-based quality control method for complicated TCMPs using Hu-gan-kang-yuan Capsule (HGKYC) as an example was developed. To select proper chemical markers for quality control of HGKYC, an ultra-fast liquid(More)
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