Exploring Situation-Aware Method Based on Ontology Analysis for Semantic Social Network

Abstract

Situation aware based on the situation context is important to classify context and infer further situation about context. However, the relevant applications are still difficult to deal with the inherent shortcomings of situation recognition in decision making. The existing methods of situation-aware mainly depend on situation recognition by modeling, classifying and apperceiving of context information, which is insufficient in the utilization of situation relevance. To overcome the disadvantage, situation relevance (including the trigger and dependency among situations) based on situation ontology is fully analyzed in this paper, and a situation-aware method based on ontology analysis of the semantic social network (SR-SSNOA) is also proposed. The main research lie in three aspects: (1) The situation quality, the situation relevance and the community impact are synthetically considered in the recognition and recommendation of situation by SR-SSNOA; (2) The situation ontology are converted into different figures by SR-SSNOA, which introduces semantic social network to analyze situation ontology. Extensive experiments reveal the excellent performance of SR-SSNOA at different parameter values. By conducting a questionnaire to evaluate the results, the accuracy and correctness of our method is proved.