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The progressively scale of online social network leads to the difficulty of traditional algorithms on detecting communities. We introduce an efficient and fast algorithm to detect community structure in social networks. Instead of using the eigenvectors in spectral clustering algorithms, we...
Rapid growth in data, maximum functionality requirements and changing behavior in the database workload tends the workload management to be more complex. Organizations have complex type of workloads that are very difficult to manage by humans and even in some cases this management becomes...
This paper presents, a grammatically motivated, sentiment classification model, applied on a morphologically rich language: Urdu. The morphological complexity and flexibility in grammatical rules of this language require an improved or altogether different approach. We emphasize on the...
Name disambiguation is a very critical problem in scientific cooperation network. Ambiguous author names may occur due to the existence of multiple authors with the same name. Despite much research work has been conducted, the problem is still not resolved and becomes even more serious. In this...
The aim of this paper is to propose a new classification approach of artificial neural networks hardware. Our motivation behind this work is justified by the following two arguments: first, during the last two decades a lot of approaches have been proposed for classification of neural networks...
Ontologies are currently emerging as representation techniques for overlapping compatibility context domains. The continuing need for more effective information retrieval has lead to the creation of the notions of the semantic web and personalized information management. Subsequently, the need...
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