1. A recommender system for automatically recommending items to at least one electronic device of one or more users, based on geo-tagged information related to said user, comprising: a database for storing data in a non-volatile storage, each of which being associated with a GeoTag; a recommendation server, in communication with said database and being connected to said electronic devices via a client application and over a data network, configured to: obtain, over said data network, rating values from the user regarding geo-tagged items stored in said database in a form of a user-item matrix; form weighted rating values for said items being closer than a predetermined geographical distance, wherein said weighted rating values are weighted according to: a geographical distance between a pair of items; the items previously rated by said user; a level of similarity between the user and other users; and preferences of similar other users to said user; propagate a user-item matrix with the weighted rating values; construct a user-to-user similarity matrix by calculating the similarity for each pair of users using a correlation measure, wherein the user-to-user similarity matrix contains pairs of values, wherein each pair is assigned to each entry in the user-item matrix; assign a weighted score for each user and item according to the level of similarity to other users; sort, in said database, all the items in the form of a catalog of items according to their weighted scores as calculated for the user and filtering out all items that have been already rated by said user; and automatically present to the user, on the electronic device of the user, items from said catalog of items, rated according to their weighted scores, wherein presented items are fine-grained geo-tagged items that are recommended based on geo-information and user's rating.