1. A method in a group manager of a central service node, of enabling services or media in a communication network, comprising the following steps: detecting activities and conditions of communication devices in the network, for each of a plurality of entities, collecting individual context data relating to the entity, the individual context data comprising a first data value corresponding to a first behavioral context parameter, and a second data value corresponding to a first environmental context parameter, wherein first behavioral context parameter is separate and distinct from the first environmental context parameter, for each of the plurality of said entities, creating an individual context vector for said entity from said collected individual context data related to said entity, wherein each of said plurality of context vectors identifies a point in a logical, as opposed to a physical, N-dimensional space, where N is greater than or equal to two, creating a master context vector comprising a third data value corresponding to the first behavioral context parameter, and a fourth data value corresponding to the first environmental context parameter, wherein the master context vector identifies a centroid point in the logical N-dimensional space, for each of the plurality of said individual context vectors, determining the distance between the centroid point and the point identified by said individual context vector, defining a group of correlated entities that are found to be correlated with respect to one or more features or characteristics based on the collected individual context data by including an entity in the group in response to determining that the distance between the centroid point and the point identified by said individual context vector corresponding to said entity is less than a threshold.
1. A method in a group manager of a central service node, of enabling services or media in a communication network, comprising the following steps: detecting activities and conditions of communication devices in the network, for each of a plurality of entities, collecting individual context data relating to the entity, the individual context data comprising a first data value corresponding to a first behavioral context parameter, and a second data value corresponding to a first environmental context parameter, wherein first behavioral context parameter is separate and distinct from the first environmental context parameter, for each of the plurality of said entities, creating an individual context vector for said entity from said collected individual context data related to said entity, wherein each of said plurality of context vectors identifies a point in a logical, as opposed to a physical, N-dimensional space, where N is greater than or equal to two, creating a master context vector comprising a third data value corresponding to the first behavioral context parameter, and a fourth data value corresponding to the first environmental context parameter, wherein the master context vector identifies a centroid point in the logical N-dimensional space, for each of the plurality of said individual context vectors, determining the distance between the centroid point and the point identified by said individual context vector, defining a group of correlated entities that are found to be correlated with respect to one or more features or characteristics based on the collected individual context data by including an entity in the group in response to determining that the distance between the centroid point and the point identified by said individual context vector corresponding to said entity is less than a threshold. 4. The method according to claim 1 , wherein updating the group includes changing the context parameters of relevance and/or the membership conditions.