Abstract

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CONNECTIVITY IN UNCERTAIN GRAPHS (CUG) – EXAMINING USING DISTRIBUTION FUNCTION

P.Kamal Devi, G.Eswara Prasad, V.S.Mathu Suresh


The emerging network applications, querying and mining from the uncertain graphs has become increasingly important. There is a growing need for methods that can represent and query about the uncertain graphs. These uncertain graphs are often the result of an information extraction and integration system that attempts to extract an entity graph or a knowledge graph from multiple unstructured sources. Such integration typically leads to identity uncertainty, as different data sources may use different references to the same underlying real-world entities. In uncertain graphs, the existence of some edges is not predetermined. The connectivity of an uncertain graph is essentially an uncertain variable, which indicates the suitability for investigation of its distribution function. The main focus of this paper is to propose a framework to determine the distribution function of the connectivity of an uncertain graph. Initially, it focus on the discussion of the characteristics of the uncertain connectivity and the distribution function is derived. An efficient algorithm is designed based on Floyd’s algorithm that depicts the connectivity parameters can also be focused to improve the network performance.