A mining method for egocentric and polycentric queries in multi-dimensional networks is proposed. The method allows fast search for objects in sufficient proximity of other object(s) where the proximity is defined in terms of multiple relationships between objects. The method uses spreading activation technique. Other potential uses of spreading activation technique are also outlined and, in particular, include applications to collaborative filtering (community detection based on tag recommendations, expertise location, etc). Moreover, the spreading activation technique is combined with so-called ambient navigation. The advantages of such approach are high performance and high scalability in terms of size of multidimensional network. The proposed method is very practical and is implemented in IBM LanguageWare software products.