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In context-aware trust evaluation, using ontology tree is a popular approachto represent the relation between contexts. Usually, similarity between twocontexts is computed using these trees. Therefore, the performance of trustevaluation highly depends on the quality of ontology trees. Fairness orgranularity consistency is one of the major limitations affecting the qualityof ontology tree. This limitation refers to inequality of semantic similarityin the most ontology trees. In other words, semantic similarity of every twoadjacent nodes is unequal in these trees. It deteriorates the performance ofcontexts similarity computation. We overcome this limitation by weighting treeedges based on their semantic similarity. Weight of each edge is computed usingNormalized Similarity Score (NSS) method. This method is based on frequenciesof concepts (words) co-occurrences in the pages indexed by search engines. Ourexperiments represent the better performance of the proposed approach incomparison with established trust evaluation approaches. The suggested approachcan enhance efficiency of any solution which models semantic relations byontology tree.

Trust Evaluation using an Improved Context Similarity Measurement