1. A method to create an individual user profile for an individual user from a multi-user profile that comprises a list of word-weight pairs, comprising: at least once splitting said multi-user profile based on user features, wherein said multi-user comprises a combination of user profiles of all users of a consumer device, and wherein said user features include predetermined schemes or rules according to which said individual user of said consumer device makes selection in an application of said consumer device, wherein said at least once splitting includes: performing a tentative split according to said user features to generate a first and a second sub user profiles; calculating a relative difference between said two sub user profiles; performing said performing a tentative split and calculating said relative difference until all or a predetermined number of tentative splits are performed; and splitting said multi-user profile according to that tentative split that yields the highest relative difference in case said relative difference lies above a predetermined threshold, wherein said relative difference is calculated by calculating a difference of a first discrete probability distribution of said first sub user profile over said user features that are contained therein and of a second discrete probability distribution of said second sub user profile over said user features that are contained therein, and wherein said user feature comprise one or more of the following features: preferred channel of audio/video program consumed by said user, typical time to consume an audio/video program consumed by said user, length of consuming an audio/video program by said user in relation to said total length of said audio/video programs, time of beginning said consuming an audio/video program by said user in relation to start time of said audio/video program, typical length of consuming an audio video program by said user in relation to a time of consuming, relation between how often a particular audio/video program is consumable and how often it in consumed by said user, general audio/video program consuming behavior of said user, in particular in relation to a switch-on time and length of a used audio/video device, audio/video programs recorded by said user, time duration between recording of a particular audio/video program by said user and consuming of said audio/video program by said user, actual mood of said user, actual wish of audio/video program entered by said user, year of production of an audio/video program consumed by said user, director and/or actor and/or group of actors of an audio/video program consumed by said user, type of an audio/video program consumed by said user; and title of an audio/video program consumed by said user.
1. A method to create an individual user profile for an individual user from a multi-user profile that comprises a list of word-weight pairs, comprising: at least once splitting said multi-user profile based on user features, wherein said multi-user comprises a combination of user profiles of all users of a consumer device, and wherein said user features include predetermined schemes or rules according to which said individual user of said consumer device makes selection in an application of said consumer device, wherein said at least once splitting includes: performing a tentative split according to said user features to generate a first and a second sub user profiles; calculating a relative difference between said two sub user profiles; performing said performing a tentative split and calculating said relative difference until all or a predetermined number of tentative splits are performed; and splitting said multi-user profile according to that tentative split that yields the highest relative difference in case said relative difference lies above a predetermined threshold, wherein said relative difference is calculated by calculating a difference of a first discrete probability distribution of said first sub user profile over said user features that are contained therein and of a second discrete probability distribution of said second sub user profile over said user features that are contained therein, and wherein said user feature comprise one or more of the following features: preferred channel of audio/video program consumed by said user, typical time to consume an audio/video program consumed by said user, length of consuming an audio/video program by said user in relation to said total length of said audio/video programs, time of beginning said consuming an audio/video program by said user in relation to start time of said audio/video program, typical length of consuming an audio video program by said user in relation to a time of consuming, relation between how often a particular audio/video program is consumable and how often it in consumed by said user, general audio/video program consuming behavior of said user, in particular in relation to a switch-on time and length of a used audio/video device, audio/video programs recorded by said user, time duration between recording of a particular audio/video program by said user and consuming of said audio/video program by said user, actual mood of said user, actual wish of audio/video program entered by said user, year of production of an audio/video program consumed by said user, director and/or actor and/or group of actors of an audio/video program consumed by said user, type of an audio/video program consumed by said user; and title of an audio/video program consumed by said user. 6. The method according to claim 1 , wherein said method is used in an audio/video program suggestion engine.