In this paper, we focus on task-level parallelism, which is obtained by a high-level decomposition of the production system. Speed-ups obtained from task-level parallelism will multiply with che speed-ups obtained from match parallelism. Our vehicle for the investigation of task-level parallelism is SPAM, a high-level vision system, implemented in a production system architecture. SPAM is a mat...

We conducted an empirical study of the clustering behavior of spammers and explored the group-based anti-spam strategies. We propose to block spammers as groups instead of dealing with each spam individually. We empirically observe that, with a certain grouping criteria such as having the same URL in the spam mail, the relationship among the spammers has demonstrated highly clustering structure...

based spam email filters available and also in operation. Yet we are still inundated with spam emails everyday. This is not because the filters are not powerful enough, but because the filtering systems are not flexible enough to adapt the new development of spam techniques, such as HTML tagging, image based spam, and keyword obfuscating etc. In this paper, we propose to use dynamic multiple no...

Hout, Goldinger, and Ferguson (2013) critically examined the spatial arrangement method (SpAM), originally proposed by Goldstone (1994), as a fast and efficient way to collect similarity data for multidimensional scaling. We found that SpAM produced high-quality data, making it an intuitive and user-friendly alternative to the classic "pairwise" method. Verheyen, Voorspoels, Vanpaemel, and Stor...

This paper initializes a two element concentration vector as a feature vector for classification and spam detection. Negative selection algorithm proposed by the immune system in solving problems in spam detection is used to distinguish spam from non-spam (self from non-self). Self concentration and non-self concentration are generated to form two element concentration vectors. In this approach...

The massive increase of spam is posing a very serious threat to email which has become an important means of communication. Not only does it annoy users, but it also consumes much of the bandwidth of the Internet. Most spam filters in existence are based on the content of email one way or the other. While these anti-spam tools have proven very useful, they do not prevent the bandwidth from bein...

Proliferation of unrestricted Internet access has brought the community unsolicited commercial email, better known as spam. Underestimated for quite some time, spam is now recognized as a problem costing the community billions of dollars per annum. One of the direct impacts of the spam flood is the widespread deployment of anti-spam measures, such as email filters and block lists. In this paper...

Today, internet users are increases Spam mail is the major problem and big challenges for researcher to reduce it .Spam is commonly defined as unsolicited email messages and the goal of spam categorization is to distinguish between spam and legitimate email messages. This paper shows classification of spam mail and solving various problems is related to web space. Many machine learning algorith...

Unsolicited Bulk Emails (also known as Spam) are undesirable emails sent to massive number of users. Spam emails consume the network resources and cause lots of security uncertainties. As we studied, the location where the spam filter operates in is an important parameter to preserve network resources. Although there are many different methods to block spam emails, most of program developers on...

An efficient anti-spam filter that would block all unsolicited messages i.e. spam, without blocking any legitimate messages is a growing need. To address this problem, this report takes a statistically-based approach, employing a Bayesian anti-spam filter, because it is content-based and self-learning (adaptive) in nature. We train the filter, using a large corpus of legitimate messages and spa...