Abstract: The a user interface (UI) residing in a mobile environment, which has a possibility of indicating after reading each message whether or not the message is divergent from the normal/general level as to the importance of the message. Advantageously, the user does not need to do the indication every time when reading the mail. In the interface, after a given mail has been read (or a part of the given mail has been read), there occurs a possibility to choose between two alternatives: interesting or non-interesting. Advantageously, there is not required other extra work from the user. Gradually, a mail agent collects information about what kind of mail the user prefers and does not prefer. The result will be a prearranged list by preference in the incoming mail. Any mail similar to the ones previously indicated as important will appear first to the user. The applied algorithm in the methods and systems is based on statistical analysis of the linguistic contents of the mail.

Abstract: The a user interface (UI) residing in a mobile environment, which has a possibility of indicating after reading each message whether or not the message is divergent from the normal/general level as to the importance of the message. Advantageously, the user does not need to do the indication every time when reading the mail. In the interface, after a given mail has been read (or a part of the given mail has been read), there occurs a possibility to choose between two alternatives: interesting or non-interesting. Advantageously, there is not required other extra work from the user. Gradually, a mail agent collects information about what kind of mail the user prefers and does not prefer. The result will be a prearranged list by preference in the incoming mail. Any mail similar to the ones previously indicated as important will appear first to the user. The applied algorithm in the methods and systems is based on statistical analysis of the linguistic contents of the mail.

Abstract: The a user interface (UI) residing in a mobile environment, which has a possibility of indicating after reading each message whether or not the message is divergent from the normal/general level as to the importance of the message. Advantageously, the user does not need to do the indication every time when reading the mail. In the interface, after a given mail has been read (or a part of the given mail has been read), there occurs a possibility to choose between two alternatives: interesting or non-interesting. Advantageously, there is not required other extra work from the user. Gradually, a mail agent collects information about what kind of mail the user prefers and does not prefer. The result will be a prearranged list by preference in the incoming mail. Any mail similar to the ones previously indicated as important will appear first to the user. The applied algorithm in the methods and systems is based on statistical analysis of the linguistic contents of the mail.

Abstract: The a user interface (UI) residing in a mobile environment, which has a possibility of indicating after reading each message whether or not the message is divergent from the normal/general level as to the importance of the message. Advantageously, the user does not need to do the indication every time when reading the mail. In the interface, after a given mail has been read (or a part of the given mail has been read), there occurs a possibility to choose between two alternatives: interesting or non-interesting. Advantageously, there is not required other extra work from the user. Gradually, a mail agent collects information about what kind of mail the user prefers and does not prefer. The result will be a prearranged list by preference in the incoming mail. Any mail similar to the ones previously indicated as important will appear first to the user. The applied algorithm in the methods and systems is based on statistical analysis of the linguistic contents of the mail.

Abstract: A method and a system for modeling user preferences in a high-dimensional data space (106) wherein data entities are presented as vectors the elements of which are characteristic features thereof, the data entities being clustered into a number of categories, and a set of latent vectors (110, 114) specifying directions in the data space (106). The model is updated on the basis of user feedback; if the feedback (120, 122) concerning a data entity in the data space is positive, the model adapts towards the entity, otherwise away from it. Latent vectors (110, 114) that constitute a set of global mood components are weighted with user-specific weighting factors in order to locate a user-specific mood center in the data space (106) in relation to the current category center (108, 112). The model may be exploited in a web radio computer application transmitting personalized program to the users.