Method and system for generating recommendations of content items

Abstract

A recommendation system comprises a recommendation server (107) which generates a first recommendation set of recommended content items in response to a user profile associated with a first user and stored on the recommendation server (107). Content item identification data identifying the content items of the first recommendation set are transmitted to a first recommendation device (101). The first recommendation device (101) comprises a network interface (301) which receives the content item identification data from the recommendation server (107). A content list processor (303) determines the first recommendation set in response to the content item identification data. The first recommendation device (101) furthermore comprises application processors (309-313) which can execute different recommendation applications. A device recommender (307) generates a second set of recommended content items from the first recommendation set in response to a characteristic of the recommendation application being executed. The application then provides recommendations in response to the second set.

Description

technical field [0001] The present invention relates to a method and system for generating recommendations of content items, and in particular but not exclusively to the generation of recommendations of television programs. Background technique [0002] In recent years, the availability and provision of multimedia and entertainment content has increased substantially. For example, the number of television and radio channels available has grown considerably, and the proliferation of the Internet has provided new means of content distribution. Consequently, many different types of content are increasingly being provided to users from different sources. In order to identify and select desired content, users typically must process large amounts of information, which can be cumbersome and impractical. [0003] Accordingly, substantial resources have been devoted to researching techniques and algorithms that can provide improved user experience and help users identify and select...

AI Technical Summary

Problems solved by technology

[0010] However, the problem with the first approach is that it causes a delay in the generation of recommendations, thus resulting in slow display of recommended applications to the user

Moreover, this method requires high communication capacity and may use considerable communication resources

This shortcoming makes this method impractical in many situations and especially when the communication channel between the device(s) and the server is a limited or slow resource (e.g. for mobile devices)

[0011] The problem with the second approach is that the presentation of recommendation information is limited to actual recommendations already received

Therefore, recommendations tend towards general recommendations for that time interval, and the method tends to lead to more general and less appropriate recommendations

Moreover, the flexibility in providing different recommendations to the user tends to be greatly limited, and this approach tends to result in a suboptimal user experience

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