Abstract: A device (D) is intended for determining potential interests of users (U1-U3) that are clients of at least one network operator, each user being associated to a profile defining at least his interests. This device (D) comprises i) a tracking means (TM) arranged for analyzing the profile of at least one user (U1) to determine new real interest(s) it contains and for storing an identifier representative of a determined new real interest of this user (U1) in correspondence with a first date at which it has been considered as a new real interest into his profile, and ii) a recommendation means (RM) arranged for analyzing the first dates of a user (U1) to determine a time ordered sequence of interests preceding a determined new real interest, and for comparing this determined user interest sequence to at least one other sequence RM of interests of at least one other user (U2) to predict at least one potential future interest for this user (U1), to be introduced into his profile.

Abstract: An event detection apparatus for a cellular communication system comprises a video upload processor (203) which receives video upload activity indications. Each video upload activity indication comprises an indication of a video upload from a remote station of the cellular communication system as well as a remote station location indication for the remote station from which a video clip is uploaded. An event processor (205) generates an event indication in response to the video upload activity indications meeting a criterion where the event indication comprises an event location indication generated in response to the remote station location indications. The event detection criterion may specifically be that more than a given number of video upload activity indications are indicative of video uploads within a given time interval and geographic area. The invention may allow improved event detection.

Abstract: A method for providing individualized recommendations to a user on a multi-user device is provided. During operation anonymous user preferences of similar program content will be grouped to form clusters of similar preferences. Context information for each cluster is determined and the clusters are grouped to form larger clusters. The grouping is based on the context information for each cluster. A current context is then determined and at least one larger cluster is found that has a similar context as the current context. The larger cluster is used to make a recommendation for the user.

Abstract: An apparatus for content item recommendation, such as a Digital Video Recorder, comprises a grouping unit (105) for grouping user ratings for content items into rating groups in response to a content item match criterion. A receiver (109) receives content item data for a plurality of content items and a first recommendation unit (107) generating a first set of content item recommendations. An association unit (111) then determines an associated rating group of the rating groups for each content item recommendation of the first set and a second recommendation unit (113) generates a second set of content item recommendations from the first set in response to a rating group distribution measure for the second set. The invention may allow improved recommendation of content items which is aligned with user preferences yet provide a desired diversity of the provided recommendation. The invention may in particular provide improved performance for multi-user devices.

Abstract: A method of generating a user profile initially comprises receiving (201, 203) characterising data, and optionally user preferences, for content items. The characterising data describes characteristics, such as content or context characteristics, of each content item. The content items are then clustered (205) into content item clusters in response to characterising data associated with each content item. For each content item cluster, cluster characterising data is determined (207) in response to characterising data and possibly user preferences associated with each content item in the content item cluster. First characterising data is then received (209) for a first content item and a first content item cluster is selected (211) in response to a comparison of the first characterising data and the cluster characterising data of each content item cluster. A user profile is then generated (211) for the first content item in response to first cluster characterising data of the first content item cluster.

Abstract: A reasoning apparatus (101) is arranged to determine device locations for user profile elements of a distributed user profile. A user profile processor (201) receives a user profile which comprises a plurality of user profile elements. Each user profile element furthermore comprises associated metadata. The apparatus (101) also comprises a device profile receiver (203) that receives device profiles for a plurality of devices. A device location processor (205) proceeds to determine device locations for the user profile elements in response to the associated metadata and the device profiles. Specifically, a user profile element may be assigned to a specific device if the device profile for that device matches the metadata for the user profile element. The reasoning apparatus (101) may furthermore comprise a user profile element synchroniser (207) which synchronises the user profile elements with the appropriate devices.

Abstract: A distributed content item recommendation system comprises a central recommendation server (101) and a plurality of remote recommendation devices (103) coupled to the central recommendation server (101) via a communication network (105). The central recommendation server (101) stores content item set correlation data for sets of content items. The correlation data is used for item based collaborative filtering in recommendation processors (303) of the recommendation devices (103). A computation task processor (207) maintains a task list of content item correlation computation tasks which can be independently executed to generate content item set correlation data. A task assignment processor (209) can assign the computation tasks to remote recommendation devices (103) which comprise a processing unit (307) that calculates the associated correlation data and returns it to the recommendation server (101).

Abstract: An access unit (107) detects a service access (201) suitable for group operation and in response transmits (203) a group formation request to a plurality of applications. The applications decide whether to join the group (205) and the access unit (107) receives a group join indication from the applications deciding to join (207). Each group join indication comprises application constraint data in response to which the access unit (107) determines group constraint data (209) indicative of the constraints of the group of applications. The access unit (107) then accesses (211) a service using the group constraint data. The access unit subsequently receives service data (213) which is forwarded (215) to the individual applications. The invention may provide group based services based on services and/or applications designed for single users.

Abstract: A user device comprises an access interface (109) for accessing a web service by exchanging information with the web service over the Internet (105). An application processor (107) executes a user application accessing the web service through the access interface (109) and the Internet (105). The application processor (107) is connected to an ontology processor (111) which determines an ontology associated with at least some of the information exchanged with the web service. For example, the ontology may relate to a data structure of data objects communicated between the application processor (107) and the web service. The user device (101) further comprises a preference detector (113) which determines a user preference indication in response to the ontology and the exchanged information. The preference detector (113) is connected to a preference processor (115) which determines a user preference in response to the user preference indication.