Telefonaktiebolaget Lm Ericsson (publ)

Jonas Bjork

Simon Moritz

Vincent Huang

Mattias Lidström

Richard Carlsson

Andreas Fasbender

Hjalmer Olsson

The present invention provides an improved recommender system. In some embodiments, the recommender system automatically builds a user profile for a user based solely on the action or actions the user takes with respect to certain documents and the contents of the documents. That is, the profile is based on implicit ratings. In addition to maintaining a user profile for each user, each document in a set of documents will have its own document profile, which is also referred to as a document vector. Advantageously, in some embodiments, the user profile will consist of the same attributes as the document vectors. This advantageous feature enables the recommender system to compare users and documents in order to generate recommendations.

System and methods for updating user profiles and providing selected documents to users

A method of providing content () associated with a weight-value, the content () previously provided to a current computer associated with a current user () that is represented by a first node () in a social network (). The method comprises the steps of: i) enabling the current computer () to display the content (), in dependence of the weight-value, ii) obtaining an input of the current user (), iii) updating the weight-value of the content (), in dependence of the input of the current user (), iv) determining a receiving computer associated with a second node () in the social network (), and v) providing the content () to the receiving computer. Corresponding computers, computer program and computer readable medium are also described.

Providing content by using a social network

The invention provides an improved recommender system that includes a client device or service provider server, a trusted function handler module and a recommender module. The recommender system functions to protect the privacy of user rating information maintained by the node (i.e., client device/server) by having the node transform the user rating information using a specific function selected by the function handler and then provide the transformed user rating information to the recommender module. In this way, privacy of the user rating information is maintained because the original user rating information will be unknown to a recommender module.

System and methods for protecting the privacy of user information in a recommendation system

A method is provided for determining a correlation between a reference user and another user on the basis of two sets of ratings, where each rating is associated with a respective user. In response to a trigger, user ratings associated with the reference user and user ratings associated with the other user are collected, and all co-rated items of these two sets are correlated in the basis of an adjusted cosine correlation function which is weighted by a first and a second weighting function. The correlation is then stored and may be repeated for a plurality of users. The stored correlations may be used e.g. for ranking purposes.

Double weighted correlation scheme

In one embodiment, a method of generating annotation tags () for a digital image () includes maintaining a library () of human-meaningful words or phrases organized as category entries () according to a number of defined image description categories (), and receiving context metadata () associated with the capture of a given digital image (). The method further includes selecting particular category entries (--) as vocabulary metadata () for the digital image () by mapping the context metadata () into the library (), and generating annotation tags () for the digital image () by logically combining the vocabulary metadata () according to a defined set of deductive logic rules () that are predicated on the defined image description categories (). In another embodiment, a processing apparatus (), such as a digital processor () and supporting memory (), etc., is configured to carry out the above method, or to carry out variations of the above method.

Generation of annotation tags based on multimodal metadata and structured semantic descriptors

A method of estimating a default rating of a rated dataset is provided, where the dataset comprises at least one series of ratings associated with at least one user and each series comprise ratings associated with at least two items. For a reference user and an item for which a rated value is missing the item's average rating, i, the reference users average rating, R, and the datasets average rating, d, is collected. A Poisson distribution of the reference users rating is then generated on the basis of the reference users average rating. A random Poisson rating, u, is calculated on the basis of the Poisson distribution, and a default rating, r, is estimated by weighting the random Poisson rating on the basis of the items average rating, the users average rating and the datasets average rating.

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Stockholm, Sweden

Jonas Bjork