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Titlebook: Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing; Roger Lee Book 2015 Springer International P

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楼主: Hayes
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Using Word N-Grams as Features in Arabic Text Classification,st neighbor (KNN), and support vector machine (SVM)). Our results show that the use of single words as a feature provides greater classification accuracy (CA) for ATC compared to N-grams. Moreover, CA decreases by 17% on average when the number of N-grams increases. The data also show that the SVM C
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A Data Mining Based Publish/Subscribe System over Structured Peer-to-Peer Networks,usually subscribed together, e.g. frequent itemset. Then subscriptions and events are installed by frequent itemsets contained in them. If subscriptions and events don’t contain any frequent itemset, they are delivered to specified RPs (rendezvous points) for matching. The usage of frequent itemsets
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Secure Identity Management System for Federated Cloud Environment,erous benefits, these systems have certain critical weaknesses such as lack of security and privacy while disseminating identity credentials (Personally Identifiable Information (PII)) across multiple federated Cloud environments. In addition to this, FIMsystems have limitations in terms of interope
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