A recommender engine is configured to access memory and surface transmedia content items; and/or linked transmedia content subsets; and/or one or more identifications of identified users; and/or content items of the plurality of transmedia content items associated with at least one identified user. The surfaced items are presented for selection by the given user via the transmedia content linking engine as one or more user-selected transmedia content items.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An apparatus for surfacing transmedia content to a given user of a plurality of users comprising: a memory configured to store: a plurality of transmedia content items, each content item being associated with at least one of the plurality of users; and linking data which define time-ordered content links between the plurality of transmedia content items, the plurality of transmedia content items being arranged into linked transmedia content subsets comprising different groups of the transmedia content items and different content links therebetween; a transmedia content linking engine configured to receive user input indicative of a time-ordering between at least two user-selected transmedia content items and generate the content link data for storage in the memory, thereby defining a linked transmedia content subset including the at least two user-selected transmedia content items; and a recommender engine configured to access the memory and surface to the given user: one or more content items of the plurality of transmedia content items; and/or one or more of the linked transmedia content subsets of the linked transmedia content subsets; and/or one or more identifications of identified users other than the given user; and/or the content items of the plurality of transmedia content items associated with at least one identified user other than the given user, wherein the one or more surfaced content items and/or the one or more surfaced linked transmedia content subsets are surfaced for selection by the given user via the transmedia content linking engine as one or more user-selectable transmedia content items. 2. The apparatus of claim 1, wherein the memory further includes user ownership data which associates each transmedia content item to a user of the plurality of users, and each transmedia content subset of the multiple content subsets with a user of the plurality of users. 3. The apparatus of claim 2, wherein the transmedia content linking engine is configured to identify a current user-selected time-ordered location of the given user within a given linked transmedia content subset for insertion of one of the transmedia content items, and to generate corresponding content linking data therefor upon insertion by the given user of the one or more content items into the given linked transmedia content subset. 4. The apparatus of claim 3, wherein the recommender engine is further configured to surface the one or more transmedia content items and/or surface the one or more transmedia content subsets based on the current user-selected time-ordered location. 5. The apparatus of claim 1, further comprising a preference model, wherein the preference model is configured to provide a prediction of a rating for a given user for a given transmedia content data item. 6. The apparatus of claim 5, wherein the preference model is configured to: remove global effects for one or more rated items that have been previously rated by the given user to generate explicit ratings and storing the removed global effects; provide the explicit ratings and metadata associated with the given transmedia content data item to a plurality of recommender algorithms to generate a plurality of predicted ratings for the given transmedia content data item; combine the plurality of predicted ratings to build an ensemble prediction of the predicted ratings for the given transmedia content data item; add the stored global effects to the ensemble prediction to produce a predicted user rating for the given transmedia content data item; and output the predicted user rating for the given transmedia content data item. 7. The apparatus of claim 5, wherein the apparatus further comprises a user-brand match component configured to provide for a given user a prediction of a preference for a given branded content data item. 8. The apparatus of claim 7, wherein the apparatus further comprises a branded content model configured to provide for a given transmedia content item a prediction of the suitability of a given branded content data item. 9. The apparatus of claim 8, wherein the recommender engine is configured to surface transmedia content data items by querying the preference model, user-brand match component and brand model component by providing the preference model, user-brand match component and brand model with a transmedia content parameter, user data for the given user and a given branded content data item, and to maximise the sum of the output for the preference model, user-brand match component and brand model over the transmedia content parameter. 10. The apparatus of claim 9, wherein the recommender engine is configured to surface the transmedia content data item with the maximum output. 11. The apparatus of claim 1, wherein, the plurality of transmedia content items comprises items of different content types. 12. The apparatus of claim 1, wherein the transmedia content data items relate to narrative elements of the transmedia content data items. 13. The apparatus of claim 12, wherein the time-ordered content links define a narrative order of the transmedia content data items. 14. The apparatus of claim 1, wherein each time-ordered content link defines a directional link from a first transmedia content data item to a second transmedia content data item of the plurality of transmedia content data items. 15. The apparatus of claim 14, wherein the first transmedia content data item has a plurality of outgoing time-ordered content links. 16. The apparatus of claim 14, wherein the second transmedia content data item has a plurality of incoming time-ordered content links. 17. The apparatus of claim 14, wherein the memory is further configured to store a plurality of subset entry points for the plurality of transmedia content subsets. 18. The apparatus of claim 17, wherein each subset entry point is a flag indicating a transmedia content data item that has at least one outgoing time-ordered link and no incoming time-ordered links. 19. The apparatus of claim 18, wherein each linked transmedia content subset defines a linear path, wherein a linear path comprises a subset entry point, one or more transmedia content data items and one or more time ordered links between the subset entry point and the transmedia content data items. 20. The apparatus of claim 19, wherein two or more transmedia content subsets share one or more subset entry points, one or more transmedia content data items and/or one or more time ordered content links. 21. The apparatus of claim 21, wherein the recommender engine is further configured to surface one or more groups transmedia content subsets to the given user, the one or more surfaced groups being surfaced for selection by the given user via the transmedia content linking engine. 22. The apparatus of claim 1, further comprising a user model, wherein the user model is configured to provide a predictions of the state and/or behaviour of a given user to the recommender engine. 23. The apparatus of claim 22, wherein the memory is further configured to store a plurality of historical user interaction data items which define the historical interaction of a given user with the apparatus for surfacing transmedia content to a given user of a plurality of users, and wherein the user model is configured to: receive one or more historical user interaction data items associated with the given user; provide the one or more historical interaction data items to a statistical model to produce a prediction of a mental state of the user; retrieve from the statistical model the predicted mental state of the user and/or a predicted behaviour of the user; and output the predicted mental state of the user and/or predicted behaviour of the user. 24. The apparatus of claim 23, wherein the statistical model is a hidden Markov model. 25. The apparatus of claim 23, wherein the transmedia content recommender engine is further configured to surface the one or more individual content items to the given user and/or surface one or more of the linked transmedia content subsets to the given user when the output of the user model indicates the user is in mental state conducive to consuming transmedia content data items. 26. The apparatus of claim 23, wherein the transmedia content recommender engine is further configured to surface the one or more individual content items to the given user and/or surface one or more of the linked transmedia content subsets to the given user when the output of the user model indicates the predicted user behaviour is to consume transmedia content data items. 27. A system for surfacing transmedia content to a given user of a plurality of users comprising: the apparatus of claim 1; an electronic device configured to be in communication with the apparatus and receive and display to the given user: the surfaced one or more content items of the plurality of transmedia content items; and/or the surfaced one or more linked transmedia content subsets of the linked transmedia content subsets; and/or the surfaced one or more identifications of identified users other than the given user; and/or the surfaced content items of the plurality of transmedia content items associated with at least one identified user other than the given user. 28. A method for surfacing transmedia content to a given user of a plurality of users from a memory configured to store a plurality of transmedia content items, each content item being associated with at least one of the plurality of users, and linking data which define time-ordered content links between the plurality of transmedia content items, the plurality of transmedia content items being arranged into linked transmedia content subsets comprising different groups of the transmedia content items and different content links therebetween, the method comprising: receiving, at a transmedia content linking engine, user input indicative of a time-ordering between at least two user-selected transmedia content items; generating with the transmedia content linking engine the content linking data for storage in the memory, thereby defining a linked transmedia content subset including the at least two user-selected transmedia content items; and accessing the memory and surfacing to the given user with a recommender engine: one or more content items of the plurality of transmedia content items; and/or one or more of the linked transmedia content subsets of the linked transmedia content subsets; and/or one or more identifications of identified users other than the given user; and/or the content items of the plurality of transmedia content items associated with at least one identified user other than the given user, wherein the one or more surfaced content items and/or the one or more surfaced linked transmedia content subsets are surfaced for selection by the given user via the transmedia content linking engine as one or more user-selectable transmedia content items. 29. A computer readable medium comprising computer executable instructions, which when executed by a computer, cause the computer to perform the steps of the method of claim 28.