Abstract: Recommendation system based on the actions of a group of users, and not requiring prior metadata, is provided. The recommendation is not limited to from user-to-item (e.g. media recommendation) type; e.g. from user-to-user (e.g. social networking), from item-to-item (e.g. “see also” in internet shopping) and item-to-user (e.g. advertizing) recommendations are supported. The solution utilizes a set of identifiable tokens, associated with each entity, an entity being either a user or an item. Whenever there is an interaction between entities, either existing token sets are updated or new token sets are created such that after an interaction each interacting entity is associated with a token set which resembles more than before the token set(s) associated with the other interacting entity. Recommendation can be produced by searching best matching token sets on the user-to-item, user-to-user, from item-to-item or item-to-user basis.

Abstract: Method (400) for managing a plurality of digital token sets (202, 202b, 202c), wherein each digital token set comprises a plurality of tokens (203) and is associated with a digital item available for access via an e-service, wherein the digital tokens are identifiable elements of substantially no semantic value and interaction between a user-related token set and item-related token set involves adapting both token sets based on the token set of the other party of the interaction, comprises obtaining a first plurality of token sets associated with a corresponding plurality of digital items (300), distributing (304) said first plurality of token sets among a second plurality of at least computationally separate but communications-wise connected, functionally parallel partial repositories (202, 204, 206), wherein said second plurality is smaller than the first plurality, the partial repositories establishing a greater joint, distributed repository, wherein said distributing comprises utilization of a predefined

Abstract: Method (501) for adapting an obtained digital first token set comprising a plurality of tokens, the first token set being associated with a first entity, such as a user of an electronic device, wherein tokens are identifiable elements of substantially no semantic value, the first token set being maintained between and updated responsive to interactions between the first entity and one or more other entities, the token sets of which are also updated based on the interactions, said method comprising detecting interaction (504, 514) between the first entity and another entity, optionally a digital media element such as a web site, web page or a digital resource accessible therethrough, a second token set being associated with the second entity, determining at least one control value (506) regarding the first token set based on the interaction, wherein interaction feedback or interaction frequency is configured to affect said at least one control value, and altering the construction of the first token set (508) i

Abstract: Recommendation system based on the actions of a group of users, and not requiring prior metadata, is provided. The recommendation is not limited to from user-to-item (e.g. media recommendation) type; e.g. from user-to-user (e.g. social networking), from item-to-item (e.g. “see also” in internet shopping) and item-to-user (e.g. advertizing) recommendations are supported. The solution utilizes a set of identifiable tokens, associated with each entity, an entity being either a user or an item. Whenever there is an interaction between entities, either existing token sets are updated or new token sets are created such that after an interaction each interacting entity is associated with a token set which resembles more than before the token set(s) associated with the other interacting entity. Recommendation can be produced by searching best matching token sets on the user-to-item, user-to-user, from item-to-item or item-to-user basis.