GB2452519A

GB2452519A - System and Method for Providing User Recommendations

Info

Publication number: GB2452519A
Application number: GB0717318A
Authority: GB
Inventors: David Arthur Fell; Robert John Noble
Original assignee: Ant Software Ltd
Current assignee: Ant Software Ltd
Priority date: 2007-09-06
Filing date: 2007-09-06
Publication date: 2009-03-11
Also published as: GB0717318D0

Abstract

The invention generally relates to the field of recommendations of viewable content, and in particular to the recommendation of live and pre-recorded video streams. A system, apparatus and method of providing recommendations of viewable content from a plurality of viewable content to a user substantially in real time, the method comprises: generating viewing data from viewing of said viewable content by one or more other users substantially in real time, said viewing data comprises data such as program details, viewers ratings and opinions and user data associated with each of said other users, said user data comprising at least an identity of said other users; filtering said viewing data by one or both of said viewable content data and said user data; distributing via a network said viewing data to one or more of said users substantially in real time in response to a content characteristic of said filtered viewing data matching a corresponding user characteristic of said one or more users; decoding said viewing data to extract said viewable content data and said user data; processing said extracted viewable content data and said extracted user data to determine one or more statistics of one or both of said extracted viewable content data and said extracted user data; and displaying one or more of said statistics, said viewable content data and said user data to provide a recommendation of viewable content to said user substantially in real time based on viewing data from said one or more other users.

Description

1 2452519 System and Method for Providing User Recommendations

FiELD OF IRE INVENTION

The invention generally relates to the field of providing recommendations of viewable content, and in particular to providing recommendation of video stream content to a user substantially in real time.

BACKGROUND TO THE iNVENTION

When wanting to watch video streams, for example a live television transmission or a pre-recorded program, a user is often presented with a bewildering list of viewable video content. Such a bewildering list makes it difficult to discern which video streams are worth watching.

Whilst publications and systems are available to describe to the user the content of the various programmes, the user may not have the same preferences, or interests as the reviewer. There is therefore a need for a system to provide recommendations of viewable content to a user based on other users known to the user seeking a recommendation, or based on other users having similar or like interests to the user seeking a recommendation.

SUMMARY OF THE INVENTION

The present invention provides a method of providing recommendations of viewable content from a plurality of viewable content to a user substantially in real time, the method comprising: generating viewing data from viewing of said viewable content by one or more other users substantially in real time, said viewing data comprising viewable content data associated with said viewable content being viewed by said one or more other users, and user data associated with each of said other users, said user data comprising at least an identity of said other users; filtering said viewing data by one or both of said viewable content data and said user data; distributing said viewing data to one or more of said users substantially in real time in response to a content characteristic of said filtered viewing data matching a corresponding user characteristic of said one or more users; decoding said viewing data to extract said viewable content data and said user data; processing said extracted viewable content data and said extracted user data to determine one or more statistics of one or both of said extracted viewable content data and said extracted user data; and displaying one or more of said statistics, said viewable content data and said user data to provide a recommendation of viewable content to said user substantially in real time based on viewing data from said one or more other users.

In embodiments, the user is provided with recommendations of viewable content based on other users connected to the system. The other users may, for example, be known to the user, or may have similar or like interests.

In embodiments, generating viewing data comprises: monitoring said one or more other users' viewing of said viewable content; determining an identity of said content being viewed; and generating said viewable content data based on said identity of said content being viewed. Preferably, said determining occurs after a settling period following the one or more other users beginning to view said content.

Preferably, said viewing data further comprises user input data, and wherein generating viewing data comprises: receiving user input data from said one or more users, said user input data defining a parameter associated with said viewable content; generating said viewable content data based on said user input data. Preferably, said parameter is a user rating of said viewable content that indicates a user's opinion of said viewable content.

In embodiments, generating viewing data further comprises formatting said viewable content data and said user data into a message for transmission to one or more distribution clusters. Preferably, said message forms part of an Instant Message (IM), Blog or Short Messaging Service (SMS) text. Formatting the data into messages suitable for transmission enables a standard platform on which the users may provide recommendations.

Preferably, said content and said user characteristic comprise one or more of viewable content genre, content name, user rating, user hobbies, user interests or user friend.

Preferably, said statistics comprise one or both of a number of users viewing a viewable content and an average of user rating for said viewable content.

Preferably, said users are subscribers to a distribution cluster, said distribution cluster defining one or more relationships between said subscribers.

In embodiments, the method further comprises: receiving search criteria from a user, said criteria defining a search of said viewing data; retrieving said viewing data; and providing said data to said user. Preferably further comprises: decoding said retrieved viewing data to extract said viewable content data and said user data; processing said extracted viewable content data and said extracted user data to determine one or more statistics of one or both of said extracted viewable content data and said extracted user data; and displaying one or more of said statistics, said viewable content data and said user data. Preferably, said criteria comprises one or more of user interests, user hobbies, content identifier, and user name.

Preferably, said viewable content is a video stream. Preferably, said video stream is a live transmission video stream or a pre-recorded video stream.

The present invention also provides a system for providing recommendations of viewable content from a plurality of viewable content to a user substantially in real time, the system comprising: a viewing data generator to generate viewing data from viewing of said viewable content by one or more other users substantially in real time, said viewing data comprising viewable content data associated with said viewable content being viewed by one or more other users, and comprising user data associated with each of said other users, said user data comprising at least an identity of said other users; a filter to filter said viewing data by one or both of said viewable content data and said user data; one or more distribution clusters to distribute said viewing data to one or more of said users substantially in real time in response to a content characteristic of said filtered viewing data matching a corresponding user characteristic of said one or more users; a decoder to decode said viewing data to extract said viewable content data and said user data; a processor to process said extracted viewable content data and said extracted user data to determine one or more statistics of one or both of said extracted viewable content data and said extracted user data; and a user interface to display one or more of said statistics, said viewable content data and said user data to provide a recommendation of viewable content to said user substantially in real time based on viewing data from said one or more other users.

In embodiments, said viewing data generator comprises: a monitor to monitor said one or more other users' viewing of said viewable content and to determine an identity of said content being viewed, said viewing data generator generating viewable content data based on said identity. Preferably, said viewing data further comprises user input data and wherein said viewing data generator comprises: a user input for receiving said user input data, said user input data defining a parameter associated with said viewable content from said users. Preferably, said parameter is a user rating of said viewable content that indicates a user's opinion of said viewable content.

In embodiments, the system further comprises a formatter to format said viewable content data and said user data into a message for transmission to one or more distribution clusters. Preferably, said message forms part of an Instant Message (IM), Blog or Short Messaging Service (SMS) text.

Preferably, each of said distribution clusters has a plurality of users subscribed thereto, each of said clusters defining one or more relationships between said subscribers.

The present invention further provides a receiver for use with a display and for providing recommendations of viewable content from a plurality of viewable content to a user substantially in real time, said set top box comprising: a viewing data generator to generate viewing data from viewing of said viewable content by said user, said viewing data comprising viewable content data associated with said viewable content being viewed by said user, and comprising user data associated with said user, said user data comprising at least an identity of said user; a transmitter to transmit said viewing data to one or more distribution clusters substantially in real time, each of said distribution clusters having a one or more other users subscribed thereto, each of said clusters defining one or more relationships between said subscribers; a receiver to receive said viewing data from one or more users subscribed to a distribution cluster; a decoder to decode said viewing data to extract said viewable content data and said user data; a processor to process said extracted viewable content data and said extracted user data to determine one or more statistics of one or both of said extracted viewable content data and said extracted user data; and user interface to display one or more of said statistics, said viewable content data and said user data to provide a recommendation of viewable content to said user substantially in real time based on viewing data from said one or more other users.

Preferably, the receiver further comprises a formatter to format said viewable content data and said user data into a message for transmission to one or more distribution clusters. Preferably, said receiver is a set top box.

The invention further provides processor control code to implement the above-described systems and methods, in particular on a data carrier such as a disk, CD-or DVD-ROM, programmed memory such as read- only memory (Firmware), or on a data carrier such as an optical or electrical signal carrier. Code (and/or data) to implement embodiments of the invention may comprise source, object or executable code in a conventional programming language (interpreted or compiled) such as C, or assembly code, code for setting up or controlling an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array), or code for a hardware description language such as Verilog (Trade Mark) or VHDL (Very high speed integrated circuit Hardware Description Language). As the skilled person will appreciate such code and/or data may be distributed between a plurality of coupled components in communication with one another.

Some particular embodiments of the system and method may be implemented, for example, on a set-top box (STB) or as part of a computer system associated with or incorporated within a television or other home multimedia entertainment system. In such embodiments the above described methods may be implemented as part of a mark-up language browser such as an HTML or XML browser, and the screen display may comprise a television screen display, the data in the screen frame buffer overlying a video display. The system (and embodiments of the above described method) may also be implemented in a portable device such as a mobile communications device or portable audio and/or video player.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other aspects of the invention will now be further described, by way of example only, with reference to the accompanying figures in which: Figure 1 shows a system for providing recommendations according to the present invention; Figure 2 shows a data collection and transmission portion of the system of Figure 1; Figure 3a and 3b show a distribution cluster of Figure 1; Figure 4 shows a receiving section of the system of Figure 1; Figure 5 shows a method of requesting additional recommendations; and Figure 6 shows a receiver for a display.

DETAILED DESCRIPTION OF EMBODIMENTS

Figure 1 shows a preferred embodiment of the present invention. Broadly speaking, a distribution system collects video content recommendations in the form of viewing data messages from one or more users connected to the distribution system substantially in real-time. The distribution system distributes those recommendations to a plurality of users based on a relationship between the users defmed in the distribution system.

Whilst a user is watching a video stream, a device 10 collects viewing data 12 relating to the video stream being watched substantially in real-time and transmits 14 the viewing data to a distribution data network 16. Other users connected to the distribution network 16 receive the transmitted data 22 and a recommendation based on the data collected from the originating users is displayed 24 to the user receiving the data substantially in real-time.

Figure 2 shows a more detailed view of the device 10. The device 10 collects viewing data, which is data relating to the video content being viewed. Such data includes viewable content data, such as the identity of the video stream being viewed (for example programme name, programme genre, programme transmission time and date etc.). The device 10 also collects user data that is associated with the user (for example user identity). The viewing data is collected substantially in real-time, that is, as the viewer is watching the video content.

The device 10 also collects user input data associated with the video stream being viewed. Such data includes a user rating of the video stream, which indicates a user's opinion of the viewable content. Again, the user input data is collected in substantially real-time.

The viewable content data and user data are detected automatically by the device 10 upon viewing of the video stream, that is substantially in real-time. In order to ensure that the data is valid, that is a true representation of the what video stream the user is viewing, the data associated with the video stream being viewed is collected after a settling period. This settling period prevents viewable content data being collected when the user "channel hops" through various streams of video content before settling on a suitable video stream to watch. The user input data is entered manually by the user by means of a user interface within the device 10.

Once collected, the viewable content data, user data and user input data are combined to create viewing data, which is input to a formatting device 18. The formatting device 18 formats the viewing data into a format suitable for transmission onto the distribution data network 16. Such formatted messages include text strings for transmission as an Instant Message (IM), a short message service text (SMS) and a Blog-type text. Once formatted, the message is transmitted 14 to the distribution data network 16.

Figure 3a shows a more detailed view of the distribution data network 16. The receiver 32 receives messages from a plurality of users connected to the distribution data network substantially in real-time. Once received, the messages are filtered 34 based on one or both of the viewable content data and the user data. The filtered data is then transmitted 36 to one or more users in response to a match between a user-defined characteristic and the viewing data and user data contained in the message. User-defined characteristics may, for example, be another user identified as a friend of the user, the video stream identity, the video stream genre etc. This ensures that the data is only transmitted to users who may have an interest in the video stream being watched by the user. As well as transmitting the data, the distribution network may also store the data for future use.

Alternatively, the messages are filtered with respect to the user from which they are sent which negates the need to process the message. The filter would therefore be classed as an opaque filter, and the distribution network passes the messages on "blindly", without knowing the content therein.

The distribution data network has a number of users subscribed thereto. The network defines one or more relationships between the subscribed users. The relationships may be based on an expression of a user's interests or hobbies, or linked by friendship.

Examples of known distribution networks include social networking services, for example Twitter, Skype, Facebook and other like services. The network may also be connected to the internet.

In such networks, the user defines one or more relationships with other users, such as a friendship, a common interest or hobby. Alternatively, the data network automatically creates relationships between users based on viewing data being received by the users.

Figure 3b shows a distribution network that comprises more than one network. Each of the networks I 6a, I 6b comprise a number of subscriber users. The networks could be considered cluster networks, each comprising a cluster of users having a relationship to one another defmed by the cluster. The clusters receive data from the user watching a video stream and the one or more distribution clusters 16a, 16b distributing this information to a number of other users. The relationship between the originator user and the receiving users is therefore a one to many relationship. Furthermore, it will be apparent to the skilled reader that each user in the system has a one-to-many relationship with other users in the system.

Each of the distribution clusters may be provided by a single service provider.

Alternatively, each distribution cluster may be provided by different service providers.

For example, one cluster I 6a may be provided by Twitter, and the second cluster 1 6b may be provided by Skype. Only two distribution clusters are shown in figure 3b. It will, of course, be apparent to those skilled in the art that the system is not limited to two clusters, and other providers are available.

Figure 4 shows a receiver device 20. Upon receipt of a message from the distribution network 16 by the receiver 22, the message is passed to a decoder 26, which listens to data being sent by the distribution network for messages formatted in the correct manner. The decoder will ignore the non-matches, which prevents the processor being deluged with data unsuitable for processing. When a suitable message is detected, the decoder extracts the viewable content data and the user data from the message.

In the situation where there are a plurality of distribution networks or clusters transmitting information to the receiving device 20, the receiving device aggregates the received data. This feature may be provided by the receiver or the decoder.

The extracted data is then forwarded to a processor 28, which cross-references the received data with configuration data associated with the receiver being used by the user. The processor looks for matches between the received data and the configuration data (for example channels available for viewing, or recordings saved). Upon detecting a match, the processor inputs the received data into a table and cross-references the data to the configuration data.

The processor then determines a number of statistics using the extracted data. Such statistics, for example, include an average number of users viewing that particular video stream, the average ratings for the viewing stream and other such statistics.

The statistics, viewable content data and the user data are then displayed 30 to provide a recommendation of the video stream based on the data provided by other users. The recommendation therefore occurs substantially in real-time from the originating user watching a video stream. The recommendations may be stored in the receiving device for future retrieval.

The recommendation may be shown as a graphic or text on the user interface. For example an icon or textual matter may appear next to a video stream listed in a programme guide being displayed on a television screen that indicates that another user known to the user, such as a friend, approves or disapproves of that particular video stream. The other user need not be a friend of the user, but may instead be another user with a common interest with the user, as defined by a relationship in the distribution network The user interface allows the recommendations to be sorted by any of the displayed fields (for example programme name, programme channel, programme time, user name, user rating, the statistics discussed above etc), or prioritised by the user. The recommendations may also be grouped based on the context of the recommendation.

In embodiments, the user interface is provided as a mark-up language browser such as an HTML or XML browser. Other types of browsers will be apparent to those skilled in the art.

As well as receiving recommendations from other users known to the user, the user seeking a recommendation may input a set of criteria using the user interface. This is shown in Figure 5. The criteria is transmitted to one or more of the distribution clusters, which search for matches relating to the criteria set by the user. The records matching the criteria are transmitted to the user seeking further recommendation and the messages are received, decoded, processed and displayed as described above.

Figure 6 shows a receiver for a display, for example a set top box for use with a television, computer, portable viewing device or the like. The receiver comprises the transmitting 10 and receiving 20 devices as shown in Figure 1. The receiver further comprises receivers (not shown) capable of receiving video transmissions (for example over the air, cable, satellite, internet or the like) and displaying the received video content on a display (not shown). Additionally, the receiver may also record the video transmission and save the video content for later viewing. The receiver may be connected to a television set for the user to view video streams and to send and receive recommendations of the video streams. The user is provided with a user interface to send and receive such data, as described above.

It will be clear to the skilled reader that the above systems and methods apply equally to live video transmissions (over the air, cable, satellite, video over internet etc) or video stream that have been previously recorded from such live video transmissions.

The above systems and methods therefore provide visual summaries to your nominated friends (or people with a common interest) of what you have been or are watching, which they can use as a recommendation of video content to watch. The recommendations can be sent in real-time by watching a video stream, for example on a television through a set top box. Additional data is also provided to the user in the form of the user rating system.

No doubt many other effective alternatives will occur to the skilled person. It will be understood that the invention is not limited to these described embodiments and encompasses modifications apparent to those skilled in the art lying within the spirit and scope of the claims appended hereto.

Claims

CLAIMS: 1. A method of providing recommendations of viewable content from a plurality of viewable content to a user substantially in real time, the method comprising: generating viewing data from viewing of said viewable content by one or more other users substantially in real time, said viewing data comprising viewable content data associated with said viewable content being viewed by said one or more other users, and user data associated with each of said other users, said user data comprising at least an identity of'said other users; filtering said viewing data by one or both of said viewable content data and said user data; distributing said viewing data to one or more of said users substantially in real time in response to a content characteristic of said filtered viewing data matching a corresponding user characteristic of said one or more users; decoding said viewing data to extract said viewable content data and said user data; processing said extracted viewable content data and said extracted user data to determine one or more statistics of one or both of said extracted viewable content data and said extracted user data; and displaying one or more of said statistics, said viewable content data and said user data to provide a recommendation of viewable content to said user substantially in real time based on viewing data from said one or more other users.
2. A method according to claim 1, wherein generating viewing data comprises: monitoring said one or more other users' viewing of said viewable content; determining an identity of said content being viewed; and generating said viewable content data based on said identity of said content being viewed.
3. A method according to claim 2, wherein said determining occurs afier a settling period following the one or more other users beginning to view said content.
4. A method according to claim 1, 2 or 3, wherein said viewing data further comprises user input data, and wherein generating viewing data comprises: receiving user input data from said one or more users, said user input data defining a parameter associated with said viewable content; generating said viewable content data based on said user input data.
5. A method according to claim 4, wherein said parameter is a user rating of said viewable content that indicates a user's opinion of said viewable content.
6. A method according to any preceding claim, wherein generating viewing data further comprises formatting said viewable content data and said user data into a message for transmission to one or more distribution clusters.
7. A method according to claim 6, wherein said message forms part of an Instant Message (1M), Blog or Short Messaging Service (SMS) text.
8. A method according to any preceding claim, wherein said content and said user characteristic comprise one or more of viewable content genre, content name, user rating, user hobbies, user interests or user friend.
9. A method according to any preceding claim, wherein said statistics comprise one or both of a number of users viewing a viewable content and an average of user rating for said viewable content.
10. A method according to any preceding claim, wherein said users are subscribers to a distribution cluster, said distribution cluster defming one or more relationships between said subscribers.
11. A method according to any preceding claim, further comprising: receiving search criteria from a user, said criteria defining a search of said viewing data; retrieving said viewing data; and providing said data to said user.
12. A method according to claim Ii, further comprising: decoding said retrieved viewing data to extract said viewable content data and said user data; processing said extracted viewable content data and said extracted user data to determine one or more statistics of one or both of said extracted viewable content data and said extracted user data; and displaying one or more of said statistics, said viewable content data and said user data.
13. A method according to claims 11 or 12, wherein said criteria comprises one or more of user interests, user hobbies, content identifier, and user name.
14. A method according to any preceding claim, wherein said viewable content is a video stream.
15. A method according to claim 14, wherein said video stream is a live transmission video stream or a pre-recorded video stream.
16. A system for providing recommendations of viewable content from a plurality of viewable content to a user substantially in real time, the system comprising: a viewing data generator to generate viewing data from viewing of said viewable content by one or more other users substantially in real time, said viewing data comprising viewable content data associated with said viewable content being viewed by one or more other users, and comprising user data associated with each of said other users, said user data comprising at least an identity of said other users; a filter to filter said viewing data by one or both of said viewable content data and said user data; one or more distribution clusters to distribute said viewing data to one or more of said users substantially in real time in response to a content characteristic of said filtered viewing data matching a corresponding user characteristic of said one or more users; a decoder to decode said viewing data to extract said viewable content data and said user data; a processor to process said extracted viewable content data and said extracted user data to determine one or more statistics of one or both of said extracted viewable content data and said extracted user data; and a user interface to display one or more of said statistics, said viewable content data and said user data to provide a recommendation of viewable content to said user substantially in real time based on viewing data from said one or more other users.
17. A system according to claim 16, wherein said viewing data generator comprises: a monitor to monitor said one or more other users' viewing of said viewable content and to determine an identity of said content being viewed, said viewing data generator generating viewable content data based on said identity.
18. A system according to claim 16 or 17, wherein said viewing data further comprises user input data and wherein said viewing data generator comprises: a user input for receiving said user input data, said user input data defining a parameter associated with said viewable content from said users.
19. A system according to claim 18, wherein said parameter is a user rating of said viewable content that indicates a user's opinion of said viewable content.
20. A system according to any one of claims 16 to 19, further comprising a formatter to format said viewable content data and said user data into a message for transmission to one or more distribution clusters.
21. A system according to claim 20, wherein said message forms part of an Instant Message (IM), Blog or Short Messaging Service (SMS) text.
22. A system according to any one of claims 16 to 21, wherein said content and said user characteristic comprise one or more of viewable content gelire, content name, user rating, user hobbies, user interests or user friend.
23. A system according to any one of claims 16 to 22, wherein said statistics comprise one or both of a number of users viewing a viewable content and an average of user rating for said viewable content.
24. A system according to any one of claims 16 to 23, wherein each of said distribution clusters has a plurality of users subscribed thereto, each of said clusters defining one or more relationships between said subscribers.
25. A system according to any one of claims 16 to 24, wherein said viewable content is a video stream.
26. A system as claimed in any one of claims 16 to 25, wherein said video stream is a live transmission video stream or a pre-recorded video stream.
27. A receiver for use with a display and for providing recommendations of viewable content from a plurality of viewable content to a user substantially in real time, said set top box comprising: a viewing data generator to generate viewing data from viewing of said viewable content by said user, said viewing data comprising viewable content data associated with said viewable content being viewed by said user, and comprising user data associated with said user, said user data comprising at least an identity of said user; a transmitter to transmit said viewing data to one or more distribution clusters substantially in real time, each of said distribution clusters having a one or more other users subscribed thereto, each of said clusters defining one or more relationships between said subscribers; a receiver to receive said viewing data from one or more users subscribed to a distribution cluster; a decoder to decode said viewing data to extract said viewable content data and said user data; a processor to process said extracted viewable content data and said extracted user data to determine one or more statistics of one or both of said extracted viewable content data and said extracted user data; and a user interface to display one or more of said statistics, said viewable content data and said user data to provide a recommendation of viewable content to said user substantially in real time based on viewing data from said one or more other users.
28. A receiver according to claim 27, further comprising a formatter to format said viewable content data and said user data into a message for transmission to one or more distribution clusters.
29. A receiver according to claim 27 or 28, wherein said receiver comprises a set top box.