Abstract
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.
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