Method and Apparatus for Intelligent Channel Zapping

Abstract

The availability of television channels today may easily be overwhelming for a user and the use of conventional linear zapping when a user switches sequentially between channels arranged in a list as a method of finding interesting content becomes still more inefficient. Thus, a method of automatically determining a channel content for multi-media, audio, and video channels distributed to or acquired by an electronic device is provided, the method comprises the steps of collecting channel data, analyzing the data using statistical methods to determine a channel content, and categorizing the channels into predetermined clusters depending on the channel content. The determination may be made dynamically so that the clusters reflect the specific day and/or time of the day at which the electronic device is used. Also a system for providing such a method is provided.

Description

FIG. 1 shows the result of applying a user profile for categorizing the channels into pre-defined clusters,

FIG. 2 shows a categorization of channels according to a reference channel, and

FIG. 3 shows an example of applying a dynamically determination of source content.

FIG. 1 shows channels received on an electronic device 1 receiving a number of broadcasted channels 2a, 2b, . . . , 2n. The channels are provided to a processor 3 for collecting channel data and analyzing the data. The data are analyzed using statistical methods to determine a channel content, and the channels are categorized (or classified) into predetermined clusters depending on the channel content.

In a preferred embodiment, the electronic device is a television, but it may be any other electronic device capable of receiving distributed channels or capable of acquiring channels from locations in a network, like a set-top box or a video recorder with tuner.

The information sources or channels may comprise any type of content, such as audio, visual, video, multi-media content or any combination thereof, and the channels may be distributed via networks, such as the Internet, via local networks, or via other networks comprising channel storages, via peer-to-peer networks, they may be broadcasted using cables, fibers, etc. or by wireless data transmission via satellite or terrestrial.

The electronic 1 device may also be adapted to acquire channels, e.g. on request from a user. For example, the electronic device 1 may form part of a network comprising other electronic devices having channels accessible for the electronic device 1, by e.g. having the channels stored in a local storage. A user wanting to watch e.g. an action movie may then request the electronic device 1 to find an action movie. Upon receiving such a request, the electronic device 1 may then look into storages present in the network and find a corresponding movie, or a cluster of action movies, upon analyzation of the storages provided in the network.

The channels received by the electronic device 1 are clustered into predefined clusters, such as genre cluster, being cartoons, music, action movies, home shopping, etc. Furthermore, the clusters may be rated according to the user profile, either inter-cluster rated so that the favorite clusters are rated highest, in the specific example action movies are rated highest, then cartoons and having home shopping at the lowest rating. Also, intra-cluster rating may be provided so that the specific channels showing e.g. action movies are rated according to the user profile, so that for example the most frequently watched channel of the channels showing action movies has the highest rating.

The user profile 4 may either be provided by the user or be based on actual user behavior, the user behavior being monitored over time.

In FIG. 2, another embodiment of the present invention is shown. In this case there need not be a user profile, rather a user selects a reference channel and the processor analyses the channels distributed to or acquired by the electronic device so as to find similar channels. If there is a user profile present, the similar channels may be rated according to the user behavior.

There may be more than one tuner present in the electronic device, hereby different tuners can perform different operations. For example, one tuner may be used for watching a selected channel or for zapping, another tuner may be used for finding similar channels, another may be used for recording, etc. This may of course also be accomplished having one digital tuner capable of handling multiplexed channels.

Instead of selecting a reference channel, the user may select a reference event, such as a soccer goal, a specifically romantic scene, a murder, etc. and the channels in which such an event takes place may be clustered according to the specific events. A soccer goal may for example not only be shown on sport channels, but also on news channels, etc.

In FIG. 3, a dynamically determination of channel content is depicted. Upon starting up of the system at Day 0, the channels are categorized in to predefined static clusters, such as into clusters comprising action movies, cartoons, home shopping, etc. However, the determination of channel content may be continually performed over time, so that the categorization of the channels is refined.

Furthermore, by continuing to analyze the channel content, the fact that the channel content on many channels vary over time may be taken into account. For channels having a specific genre such as MTV or Eurosport, showing more or less the same content throughout the day, this may not change the categorization, however, also for e.g. Eurosport, the categorization may be refined so that specific sport subclasses may be provided, e.g. Formula 1, soccer, etc.

For more general type content channels, such as NBS, NDR, ARD, BBC, the continued determination on channel content may provide a categorization according to the scheme shown in FIG. 3 where only channel no. 2 shows action movies in the morning from 9-11, and channel 1 from 11-13, whereas the channels 1, 3, 5, and 7 show cartoons from 9-11, and channels 3, 4, and 5 show cartoons from 11-13. Home shopping is from 9-11 shown on channels 4, 6, and 8 and from 11-13 on channels 2, 6, 7 and 8. This clustering of the channels may be provided to the user, or it may just be used for providing similar content type channels to a user. Of course the times of the day provided in FIG. 3 are only examples, and furthermore, different time schemes may be provided for each channel and for each day.

When the determination process has been allowed to run for a couple of weeks and so that the results are accumulated in a database in order to track varying channel programming in different daytime and regarding the day of the week. Furthermore, when the determination process has acquired sufficient information, a separate clustering may be available for each particular time interval, with granularity varying from a couple of minutes to several hours. Hence, also weekday specific occurrences may be included in the structure, so that the system will know that the content of Saturday night is different from any weekday night content, etc.

Furthermore, the processor 3 may store information regarding national/regional holidays, local festivals, international events, such as a soccer champion ships, or any other events that might influence programming and take such holidays or events into consideration upon categorization of channels. This information may be pre-stored in the processor, the information may be transmitted from a user or the processor may obtain these data from any external source, such as via the Internet, broadcast to the processor, etc, which information may then be retrieved with or without input from the user.

Furthermore, if there is a sudden deviation from the found scheme of channel content, such as a deviation from the normal behaviour, it may be signalled to the user, or an automatic operation may be triggered or initiated, e.g. the recording of the content that deviates from the normal behaviour may be started, etc., as this may indicate that some global event has taken place. If all the channels suddenly shift to the news cluster, it may mean that a mayor event, such as the shooting of Kennedy, the 9 September or any other event having global impact may have occurred.

It is envisaged that the dynamic determination of content may be performed continually, it may be performed at regular intervals, such as once every hour, once every half-hour, etc.

However, for e.g. creation of 24×7 clustering, to keep track of events and to detect sudden global deviations, it is preferred that the dynamic determination is performed continually.

Furthermore, the dynamically detection of content may also be used to obtain key frames from channels, so that a user may be provided with a reliable overview screen of the channels available. The overview screen may comprise a combination of key frames representing the content on the channels available, and the combination of key frames may be used to create a reliable overview of the content being broadcasted at the moment. A screen picture may show a number of downsized scenes from the available channel, the scene being a small dynamic sequence, a shot or several shots, or a non-sequential selection of representative shots/scenes (“Movie-in-a-minute”) per channel per last time period. These scenes and the display of the scenes on e.g. the TV screen may be grouped according to any of the clustering methods described above.

The scope of the invention is not limited to using statistical analysis to determine the content of the channel. Also other methods may be used like neural networks and fuzzy logic.

Furthermore, the invention may also be embodied with less components than provided in the embodiments described here, wherein one component carries out multiple functions. Just as well may the invention be embodied using more elements than depicted in FIG. 1, wherein functions carried out by one component in the embodiment provided are distributed over multiple components.

Also, it will be appreciated to a person skilled in the art that the invention may be carried out by a dedicated consumer electronics device just as well as by a general purpose computer programmed with a computer programme product comprising computer executable instructions for programming one or more processing units of said computer.

In summary, the invention relates to the following: The availability of television channels today may easily be overwhelming for a user and the use of conventional linear zapping when a user switches sequentially between channels arranged in a list as a method of finding interesting content becomes still more inefficient. Thus, a method of automatically determining a channel content for multi-media, audio, and video channels distributed to or acquired by an electronic device is provided, the method comprises the steps of collecting channel data, analyzing the data using statistical methods to determine a channel content, and categorizing the channels into predetermined clusters depending on the channel content. The determination may be made dynamically so that the clusters reflect the specific day and/or time of the day at which the electronic device is used. Also a system for providing such a method is provided.

Claims

1. A method of automatically determining a channel content distributed to or acquired by an electronic device, the method comprises the steps of: collecting channel data,analyzing the data to determine a channel content, andcategorizing at least one channel into at least one predetermined cluster depending on the channel content.

2. A method according to claim 1, wherein a user of the electronic device sends a request to the electronic device to find one or more channels with content corresponding to the content of a reference channel.

3. A method according to claim 1, wherein a user of the electronic device send a request to the electronic device to find one or more channels corresponding to a reference cluster.

4. A method according to claim 1, wherein the electronic device keeps track of user behavior to generate or maintain a user profile comprising channels or clusters being rated according to the user behavior.

5. A method according to claim 1, wherein processing resources used to collect and analyze channel data are assigned on the basis of the user profile.

6. A method according to claim 1, wherein the method further comprises the step of continually repeating the steps of collecting, analyzing, and categorizing during operation of the electronic device to achieve a dynamic determination of channel content.

7. A method according to claim 6, wherein the continual repetition of the steps of collecting, analyzing, and categorizing is performed in the background without interrupting the primary functions of the electronic device.

8. A method according to claim 6, wherein the dynamic determination of content comprises the determination of specific events in the channels content.

9. A method according to claim 8, wherein the channels are categorized into clusters according to the specific events.

10. A method according to claim 9, wherein a sudden change of channel content in a number of channels is communicated to a user or is initiating an automatic behavior.

11. The method according to claim 1, further comprising using statistical analysis for determining the channel content.

12. The method according to claim 1, further comprising using fuzzy logic for determining the channel content.

13. The method according to claim 1, wherein the steps of collecting, analyzing, and categorizing are executed periodically to determine the content of a channel various intervals in time.

14. The method according to claim 14, wherein the content is determined for a predetermined interval in time per day or per week.

15. The method according to claim 13, wherein the channel is moved from one cluster to another cluster when the content of a channel changes over time.

16. A method of dynamically determining a channel content for channels distributed to or acquired by an electronic device, the method comprises the steps of collecting channel data,analyzing the data using statistical methods to determine a channel content, andcontinually repeating the steps of collecting and analyzing during operation of the electronic device to achieve a dynamic determination of channel content.

17. A system for determining channel content comprising an electronic device for receiving channels distributed to or acquired by the electronic device, the system comprising: a processing unit for collecting channel data from the broadcasted channels, the processing unit comprising a statistical tool for analyzing the data, andcategorizing means for classifying channels into predetermined clusters depending on the channel content.

18. (canceled)

19. Computer program, embedded in a computer readable medium, comprising computer readable and executable instructions to automatically determine a channel content distributed to or acquired by an electronic device, comprising: collecting channel data,analyzing the data to determine a channel content, andcategorizing at least one channel into at least one predetermined cluster depending on the channel content.

20. (canceled)

21. (canceled)