CLIENT-SIDE RECOMMENDATIONS ON ONE-WAY BROADCAST NETWORKS

• US 20150089524A1
• Filed: 04/12/2012
• Published: 03/26/2015
• Est. Priority Date: 04/12/2012
• Status: Active Grant

• Current Assignee: Contentwise S.R.L. (Moviri S.p.A.)
• Original Assignee: Moviri S.p.A., Politecnico di Milano
• Inventors: Cremonesi, Paolo, Turrin, Roberto
• Granted Patent: US 9,749,691 B2
• Time in Patent Office: Days
• US Class Current: 725/14
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04N 21/23614 Multiplexing of additional data and video streams arrangements for simultaneous broadcast of plural pieces of information H04H20/28
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/2665 Gathering content from different sources, e.g. Internet and satellite
• CPC Class Codes: H04N 21/4348 Demultiplexing of additional data and video streams
• CPC Class Codes: H04N 21/442 Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk arrangements for monitoring broadcast services or broadcast-related services H04H60/29; arrangements for identifying or recognising characteristics with a direct linkage to broadcast information H04H60/35; monitoring of user activities for profile generation for accessing a video database G06F16/739; monitoring in wireless networks H04W24/00
• CPC Class Codes: H04N 21/44226 on social networks
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/4622 Retrieving content or additional data from different sources, e.g. from a broadcast channel and the Internet web site content organization and management for information retrieval from the Internet G06F16/958; transmission by internet of broadcast information H04H60/82; stock exchange data over packet-switching network H04L12/1804; push services including data channel over packet-switching network H04L12/1859
• CPC Class Codes: H04N 21/4667 Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies

Abstract

A method and a client-side Recommender system on One-Way Broadcast Network includes at least a one-way channel connecting a broadcasting station to a set-top-box device of a first set of users, the set-top-box including a memory, a computation and driving unit for tracking the user activity, storing a user profile, generating and displaying a ranking of recommended media items, the ranking being determined by the computation unit through a recommender model stored on the memory. The system further includes a collaborative dual module, a first back-end module running on a auxiliary server connected to a two-way network and belonging to an auxiliary domain, this first back-end module leveraging external data sources to collect community based information on at least part of the media items, while the recommender model stored on the memory being a second front-end module, wherein the broadcasting station and the set-top-box device belong to a target domain.

Claims

1. A client-side Recommender system on One-Way Broadcast Network, comprising at least a one-way channel connecting a broadcasting station to a set-top-box device (STB) of a first set of users, said set-top-box (STB) comprising a memory, a computation and driving unit for at least tracking the user activity, storing a user profile, generating and displaying on a TV set a ranking of recommended media items, said ranking being determined by said computation capacity unit through a recommender model stored on said memory, characterized in that

it comprises a collaborative dual module, a first back-end module running on a auxiliary server connected to a two-way network (Internet) and belonging to an auxiliary domain (domain A), this first back-end module leveraging external data sources to collect community based information on at least part of said media items, while said recommender model stored on said memory of the set-top-box (STB) being a second front-end module, and in that

the broadcasting station and said set-top-box device belong to a target domain (domain T),

said auxiliary server is part of said two-way network, comprising at least two channels to gather feedback data from a second set of users on at least part of said media items,

said first back-end module is processed by said auxiliary server through collaborative techniques including said feedback data collected from said second set of users,

said first back-end module is transformed in a compact representation by said server and one-way broadcast to said set-top-box (STB) where it is implemented as said second front-end module.

2. The client-side recommender system as in claim 1, wherein said second set of users is different from said first set of users.

3. The client-side recommender system as in claim 1, wherein said computation capacity unit, through said second front-end module, tracks locally behavior of the user of said first set of users and compares it with the behavior of the other users of said second set of users, in order to provide said ranking of recommended media items.

4. The client-side recommender system as in claim 1, wherein said first back-end module is processed through hybrid recommender algorithms by combining both collaborative and content-based techniques including additional items different from said media items.

7. The client-side recommender system as in claim 2, wherein said computation capacity unit, through said second front-end module, tracks locally behavior of the user of said first set of users and compares it with the behavior of the other users of said second set of users, in order to provide said ranking of recommended media items.

8. The client-side recommender system as in claim 2, wherein said first back-end module is processed through hybrid recommender algorithms by combining both collaborative and content-based techniques including additional items different from said media items.

9. The client-side recommender system as in claim 3, wherein said first back-end module is processed through hybrid recommender algorithms by combining both collaborative and content-based techniques including additional items different from said media items.

10. The client-side recommender system as in claim 7, wherein said first back-end module is processed through hybrid recommender algorithms by combining both collaborative and content-based techniques including additional items different from said media items.

5. A one-way broadcast program recommendation method comprising providing a one-way channel connecting a broadcasting station to a set-top-box device (STB) of a first set of users in a target domain (domain T), wherein said set-top-box (STB) is arranged for tracking the user activity, storing a user profile, generating and displaying on a TV set a ranking of recommended media items, said ranking being determined by a computation unit of said set-top-box (STB) through a recommender model stored in a memory thereof, characterized in that it comprises the steps of

operating a collaborative dual module, where a first back-end module is run on a auxiliary server belonging to a two-way network where a collaborative model is developed between an auxiliary set of users and auxiliary set of items, at least partially overlapping with said media items, belonging to an auxiliary domain (domain A),

compacting and tailoring said collaborative model developed in the auxiliary domain (domain A) to be broadcast in said target domain (domain T) to be used as said recommender model stored in said memory of the set-top-box (STB) by exploiting said user activity and user profile belonging to the target domain (domain T).

6. A one-way broadcast program recommendation method comprising providing a one-way channel connecting a broadcasting station to a set-top-box device (STB) of a first set of users, wherein said set-top-box (STB) is arranged for tracking the user activity, storing a user profile, generating and displaying on a TV set a ranking of recommended media items, said ranking being determined by a computation unit of said set-top-box (STB) through a recommender model stored in a memory thereof, characterized in that it comprises the step of operating a collaborative dual module, a first back-end module running on a auxiliary server connected to a two-way network (Internet) and belonging to an auxiliary domain (domain A), this first back-end module leveraging external data sources to collect community based information on at least part of said media items, and a second front-end module being said recommender model stored on said memory of the set-top-box (STB) belonging to a target domain (domain T), and in that

said auxiliary server comprises at least two channels to gather feedback data from a second set of users on at least part of said media items,

said first back-end module is processed by said auxiliary server through collaborative techniques including said feedback data collected from said second set of users,

said first back-end module is transformed in a compact representation by said auxiliary server and one-way broadcast to said set-top-box (STB) where it is implemented as said second front-end module.