Abstract: A message distribution apparatus and method for distribution of a message submitted by a user by a terminal connected to a communication network to a previously unknown group of receiving users has an access to a database which stores a semantic network data model with terms linked to each other by semantic relations and/or a social network data model with users linked to each other by social relations; a mapping engine which maps at least one term being associated with the submitted message to terms being associated with users of the social network data model and/or with terms of the semantic data model for generating a group of potential receiving users for the submitted message; and a distribution engine which distributes the submitted message of the submitting user via the communication network to a group of receiving users filtered from the at least one generated group of potential receiving users.

Abstract: A semantic multilayer network is established, wherein a first layer in said semantic multilayer network including tag annotations, and a second layer in said semantic multilayer network including data structured by an ontology, are established and wherein the first layer and the second layer are connected. Thus, connecting of two entirely different worlds of the dynamic, emergent “social tagging” (e.g., web applications like Web 2.0) and of the regular “ontology engineering” (e.g. Semantic Web) data, dynamic data tag annotations and ontology, seen as too opposed or conflictive, therefore being treated separately and independently so far, becomes possible. Here, by utilizing advantages of both worlds, computer aided handling of large amounts of data, including e.g. processing, management, or querying of data, becomes considerably efficient and effective, wherein said data may be distributed in different areas, locations, or systems.

Abstract: Automatic identification and prioritization of user profiles in network-based application systems are provided. When creating network-based content, references to a plurality of user profiles within the entire network system may be automatically identified by specifying a user identifier, and references to one or more of these user profiles may then be determined according to user specifications or specified guidelines. The content of a network-based application may then always be supplemented with references to user profiles according to the user profiles identified in this manner.

Abstract: A method generates tag proposals for tagging of a content, wherein the generating of said tag proposals is performed by combining at least two tag proposing procedures in dependence of a work context of a user. The method can be applied with regard to each area where tagging of contents is desired. By use of the method an effective, computing resource saving, and/or flexible tagging is enabled, by which a sufficient number of tags with high quality can be identified.

Abstract: A method for calculating at least one relationship metric of a relationship between objects has the steps of providing a multi-layered relationship network with a first relationship layer derived from potential relations between objects, a second relationship layer derived from interactions between objects, a third relationship layer derived from explicit relations between objects, and an aggregated relationship layer derived from at least two layers of the relationship layers, and wherein each layer has a graph with one vertex for every object represented in the network and at least one unidirectional and/or bidirectional edge between at least two of the objects, and calculating the edge weights based on the edge weights of at least two relationship layers, selecting at least the relationship with a highest edge weight between an object and other objects, and finally outputting the weights of the selected relationships as the calculated relationship metrics.

Abstract: A method for calculating at least one relationship metric of a relationship between objects has the steps of providing a multi-layered relationship network with a first relationship layer derived from potential relations between objects, a second relationship layer derived from interactions between objects, a third relationship layer derived from explicit relations between objects, and an aggregated relationship layer derived from at least two layers of the relationship layers, and wherein each layer has a graph with one vertex for every object represented in the network and at least one unidirectional and/or bidirectional edge between at least two of the objects, and calculating the edge weights based on the edge weights of at least two relationship layers, selecting at least the relationship with a highest edge weight between an object and other objects, and finally outputting the weights of the selected relationships as the calculated relationship metrics.

Abstract: A message distribution apparatus and method for distribution of a message submitted by a user by a terminal connected to a communication network to a previously unknown group of receiving users has an access to a database which stores a semantic network data model with terms linked to each other by semantic relations and/or a social network data model with users linked to each other by social relations; a mapping engine which maps at least one term being associated with the submitted message to terms being associated with users of the social network data model and/or with terms of the semantic data model for generating a group of potential receiving users for the submitted message; and a distribution engine which distributes the submitted message of the submitting user via the communication network to a group of receiving users filtered from the at least one generated group of potential receiving users.

Abstract: A method generates tag proposals for tagging of a content, wherein the generating of said tag proposals is performed by combining at least two tag proposing procedures in dependence of a work context of a user. The method can be applied with regard to each area where tagging of contents is desired. By use of the method an effective, computing resource saving, and/or flexible tagging is enabled, by which a sufficient number of tags with high quality can be identified.

Abstract: An adaptive content aggregation unit switches content data streams provided by content sources on aggregation channels for client applications of users. An adaptive content distribution unit switches content data streams generated by client applications on distribution channels. Switching of said content data streams is performed by said content aggregation unit and said content distribution unit depending on meta data of user-related profiles and depending on meta data of content-related data stream profiles. The apparatus allows improved information management of data content in a network environment and automatically forms social contacts between users having similar interests.

Abstract: A semantic multilayer network is established, wherein a first layer in said semantic multilayer network including tag annotations, and a second layer in said semantic multilayer network including data structured by an ontology, are established and wherein the first layer and the second layer are connected. Thus, connecting of two entirely different worlds of the dynamic, emergent “social tagging” (e.g., web applications like Web 2.0) and of the regular “ontology engineering” (e.g. Semantic Web) data, dynamic data tag annotations and ontology, seen as too opposed or conflictive, therefore being treated separately and independently so far, becomes possible. Here, by utilizing advantages of both worlds, computer aided handling of large amounts of data, including e.g. processing, management, or querying of data, becomes considerably efficient and effective, wherein said data may be distributed in different areas, locations, or systems.