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In this paper, we propose a reliability based Web information ranking system which enables searching useful and reliable knowledge information. The proposed system will contain subsystems for reliability ranking, information clustering based on reliability. The reliability ranking system will estimate the likelihood that a statement on the Web can be trusted using standards developed by information...
This paper proposes a new and compact method for object image retrieval fusing Dominant Colors (DCs) and embedded Markov chain concepts. This proposed method uses combined color-texture features which are characterized in terms of their spatial interaction or interrelationship properties, modeled by means of a set of embedded Markov chains, each associated with a major spatial direction. Specifically,...
In this paper, we explore and examine a new novel approach to image ranking systems based on some special types of Markov chain along with new concepts of popularity and relevancy measures for image database. To be specific, this approach introduces a family of special Markov chain models in which serial correlations are explicitly involved so that we can use them as correlations among the images...
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