Semantic context extraction from collaborative networks

A novel method for the automatic online extraction of contexts from collaborative explanation network is introduced. The method explore an unknown online collaborative network in order to find multiple explanatory paths between seed concepts. The exploration is driven by an online randomized walk informed by a heuristics based on semantic proximity measures. A pheromone-like model is then applied to the analysis of the relevance of concepts in multiple explanatory paths in order to extract the relevant contexts. Experiments held on the collaborative network Wikipedia and accepted datasets show that the proposed method is able to determine contexts with high degree of relevance which outperforms other methods. The methodology have general aim and it can be easily extended to other online collaborative networks and to non-textual domains.