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The Domain Name System (DNS) resolution is increasingly relied on for replica server selection. However, the prevailing usage of remote DNS causes the source address mismatch between clients and remote resolvers, thus suboptimal performance. We propose a simple and lightweight stub-resolver-based solution, named “Name Concatenation”, which can obtain performance improvements without requiring support...
The Domain Name System (DNS) resolution is usually served by multiple geographically distant servers. In planning and optimizing DNS server number, placement, and capacity, it is important to predict server load distribution given some knowledge about the network locations and query rates of active caching resolvers. This poster proposes an analytical model for predicting the DNS server load distribution...
Traditional Web spam classifiers use only labeled data (feature/label pairs) to train. Labeled spam instances, however, are very difficult, expensive, or time consuming to obtain, as they require the efforts of experienced human annotators. Meanwhile unlabeled samples are relatively easy to collect. Semi-supervised learning addresses the classification problem by using large amount of unlabeled data,...
Cross-language Web content quality assessment plays an important role in many Web content processing applications. In the previous research, natural language processing, heuristic content and term frequency-inverse document frequency features based statistical systems have proven effective for Web content quality assessment. However, these are language-dependent features, which are not suitable for...
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