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In view of the need for highly distributed and federated architecture, ranking ontologies from different data sources in a specific domain have great impact on the performance of web applications. Since ontologies for a same domain usually overlap, we aim to rank ontologies based on the commonality of overlapping entities and distance between each pair of ontologies. Overlapping entities are determined by considering entities and relationships between them in ontology's graph. First we find out the Common Subset of Entities (CSE) between two ontologies using the lexical and structural similarity of entities. Second, we propose a novel strategy to find the similarity between ontologies by an Entropy Based Distribution (EBD) measurement. Third, we rank some synthetic and non-synthetic ontologies based on EBD values by naive and clustering approaches. Finally, we compare our approach with an existing approach and show effectiveness of our EBD approach. Ranking ontologies has great impact in different web scenarios including the federated query expansion and knowledge searching.