Abstract: A user profile and/or the suggestions computed based thereon are obtained taking a special set of user features into account. The user features are defined to represent a typical general behaviour of an individual user in respect to the application where the user profile is used. In other words, for each application where a user profile is used a special set of user features are defined which are able to represent a typical general behaviour of an individual user. Based on these user features the weights in the list of word-weight pairs or weighted keywords which represents the user profile are computed or influenced during the creation of the user profile, and/or a mufti-user profile is split during the creation of an individual user profile from a mufti-user profile, and/or during specification of a suggestion a user history which is used to create the user profile, and/or the user profile, and/or the suggestion results are filtered.

Abstract: A Method of operating a dialogue system for serving complex user requests by appropriately controlling a network of devices (D1, . . . , Dn) and/or applications, wherein each device (D1, . . . , Dn) and/or application and its functionality are modeled by a finite state machine (FSM-1, FSM-2, FSM-3), which is using a plan language, wherein a reasoning component (1) is used in order to determine a plan (P) using said plan language for serving a received complex user request, wherein said reasoning component (1) is adapted for determining said plan (P) using said finite state machines (FSM-1, FSM-2, FSM-3), of said devices (D1, . . . , Dn) and/or applications, wherein a plan processing module (2) is used in order to perform a determined plan (P) for serving a received user request, and wherein said plan language is designed in order to enable the determination of conditional plans by said reasoning component (1), in particular by providing conditional planning commands.

Abstract: A user profile and/or the suggestions computed based thereon are obtained taking a special set of user features into account. The user features are defined to represent a typical general behaviour of an individual user in respect to the application where the user profile is used. In other words, for each application where a user profile is used a special set of user features are defined which are able to represent a typical general behaviour of an individual user. Based on these user features the weights in the list of word-weight pairs or weighted keywords which represents the user profile are computed or influenced during the creation of the user profile, and/or a mufti-user profile is split during the creation of an individual user profile from a mufti-user profile, and/or during specification of a suggestion a user history which is used to create the user profile, and/or the user profile, and/or the suggestion results are filtered.

Abstract: A user profile and/or the suggestions computed based thereon are obtained taking a special set of user features into account. The user features are defined to represent a typical general behaviour of an individual user in respect to the application where the user profile is used. In other words, for each application where a user profile is used a special set of user features are defined which are able to represent a typical general behaviour of an individual user. Based on these user features the weights in the list of word-weight pairs or weighted keywords which represents the user profile are computed or influenced during the creation of the user profile, and/or a multi-user profile is split during the creation of an individual user profile from a multi-user profile, and/or during specification of a suggestion a user history which is used to create the user profile, and/or the user profile, and/or the suggestion results are filtered.

Abstract: A user profile and/or the suggestions computed based thereon are obtained taking a special set of user features into account. The user features are defined to represent a typical general behaviour of an individual user in respect to the application where the user profile is used. In other words, for each application where a user profile is used a special set of user features are defined which are able to represent a typical general behaviour of an individual user. Based on these user features the weights in the list of word-weight pairs or weighted keywords which represents the user profile are computed or influenced during the creation of the user profile, and/or a multi-user profile is split during the creation of an individual user profile from a multi-user profile, and/or during specification of a suggestion a user history which is used to create the user profile, and/or the user profile, and/or the suggestion results are filtered.

Abstract: A Method of operating a dialogue system for serving complex user requests by appropriately controlling a network of devices (D1, . . . , Dn) and/or applications, wherein each device (D1, . . . , Dn) and/or application and its functionality are modeled by a finite state machine (FSM-1, FSM-2, FSM-3), which is using a plan language, wherein a reasoning component (1) is used in order to determine a plan (P) using said plan language for serving a received complex user request, wherein said reasoning component (1) is adapted for determining said plan (P) using said finite state machines (FSM-1, FSM-2, FSM-3) of said devices (D1, . . . , Dn) and/or applications, wherein a plan processing module (2) is used in order to perform a determined plan (P) for serving a received user request, and wherein said plan language is designed in order to enable the determination of conditional plans by said reasoning component (1), in particular by providing conditional planning commands.

Abstract: A database query set-up unit comprising a contribution stack and means for deriving a current information state from said contribution stack is described. Any search criteria provided by any user or by the system itself is pushed onto said contribution stack in the order of occurrence. The current information state, which is used for actually accessing the database, is formed from a subset of the set of search criteria contained in said contribution stack. In order to relax the search constraints, it is possible to suppress one or more of the search criteria contained in said contribution stack when forming the current information state. By implementing a contribution stack, it is possible to keep track of the order of occurrence of the various user inputs and system contributions, and to use this information for relaxing the search constraints.

Abstract: A method for serving user requests is proposed wherein for each device at least one abstract function model (33-1, . . . , 33-4) is generated. Further, a given user request is modeled and represented in an abstract way by generating an abstract task model thereof. Additionally, a plurality of abstract function models (33-1, . . . , 33-4) of distinct devices is combined and/or formally merged and/or modeled via a set of ordered external models, thereby yielding an abstract and virtual device model which models the functionalities of the combined single devices.

Abstract: To realize complex user wishes or tasks it is suggested in a method for serving user requests with respect to a network of devices to at least search for appropriate and necessary devices for fulfilling the request. Additionally, a necessary sequence of action is generated and derived to bring each of the necessary devices from the current state to a necessary initial state and then from said initial state to a final state. After the generation of said plan, the plan is executed.