WO2012059960A1 - Method, system and apparatus for interest reports - Google Patents

Method, system and apparatus for interest reports Download PDF

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WO2012059960A1
WO2012059960A1 PCT/JP2010/006519 JP2010006519W WO2012059960A1 WO 2012059960 A1 WO2012059960 A1 WO 2012059960A1 JP 2010006519 W JP2010006519 W JP 2010006519W WO 2012059960 A1 WO2012059960 A1 WO 2012059960A1
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probability
media
user equipment
user
display
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PCT/JP2010/006519
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French (fr)
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Swaroop Sampath Kumar
Pek Yew Tan
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Panasonic Corporation
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0201Market data gathering, market analysis or market modelling
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination

Abstract

A system of interest reports, comprising of a media info server that provides information related to current media being shown on a display, a UE that receives the media info and computes the probability of user interest in the media based on usage statistics of the UE and an interest report server that receives probability of user watching media.

Description

METHOD, SYSTEM AND APPARATUS FOR INTEREST REPORTS

The present invention pertains to the field of networking and multimedia. The invention applies to cases when the mobile phone could be used to detect users watching certain programs.

The necessity to detect the person watching media has been a long sought after problem. Audience have been measured by controlled surveys and subsequent extrapolation, by checking user profiles when they log in to websites and other techniques. The referred prior art identifies audience in a controlled environment by assigning a portable device, and measuring sensitivity from a stationary detector to calculate approximate distance from the portable device. In addition, the prior art suggests using existing mechanisms to judge the number of persons in the room using ultrasonic or heat sensing methods. This is done to correlate with number of portable devices detected.

U.S. Patent Application Laid-Open No. 2009/0265729

While the prior art solves the problem of automating the survey process, we wish to extend the audience measurement process to every home. When such a scenario is introduced, one problem that the prior art will have is that we cannot expect users to act as volunteers to carry such portable devices. Even if we use mobile phones as portable devices, these mobile phones are not dedicated to measuring interest. For example, they could be with the user at the moment or not. We cannot expect the users to always answer through a button whenever the interest in program needs to be judged.

Other mechanisms such as face detection could be imagined. Some apparatus close to the TV could detect faces and report names of users who are watching the current program. Face detection mechanisms suffer a fundamental weakness of privacy.

Furthermore, such a system assumes that the face-detection-apparatus can recognize all the faces it sees, and further more the service provider of the media has the user profiles of the users watching the media. The invention wishes to work in cases where the fixed-apparatus and the UE have no tight linkage apart from exchanging media info. The trust relationships exist between the UE and the Interest Report Server. For example, a person could be watching football in his friend's house and his phone could send an interest report without any linkage between his phone and the set-top-box/TV at his friend's home.

The invention intends to use the assumption of each user owning a unique mobile phone, and compute the probability of interest of the user watching a certain program.

This IPR uses the assumption that most users have mobile phones, and each mobile phone is unique to a user. The mobile phone has a trust relationship with a service provider. When the mobile phone is within a reasonable distance from the display device, a media info acquisition module is triggered. The mobile phone gets the information of the media such as media source, media type, time, display screen size, etc. The mobile phone then calculates distance from the TV. Various mechanisms can be used to estimate the distance such as using indoor propagation models. If the mobile phone is near the TV, a high probability of user being close to TV is assigned. Next, the mobile phone checks the recent interactivity by the user. For example, it checks whether the user has typed on the phone recently, or taken a picture. This will confirm that the user is near the mobile phone. Based on time when the user interacted with the mobile phone last, we can assign a suitable probability that the user is nearby. Next, we can check whether the user is using any other program on the mobile phone. An extension is that the mobile phone checks whether the user is watching a video on any other screens (e.g. PC) in the house through p2p connectivity. This will give us information whether user is busy with something else. If so, we can assign a low probability of interest when user is watching something else. After we check these individual probabilities, we can calculate the probability of the user's interest in the TV show. This probability can be sent to the operator who in turn can forward relevant information of the user to the content provider. The content provider can then customize the content, e.g. customize the ads he shows.

FIG. 1 is a diagram illustrating the preferred system. FIG. 2 is a diagram illustrating the preferred apparatus of the UE. FIG. 3 is a diagram illustrating the preferred method of evaluation of user interest. FIG. 4 is a diagram illustrating the preferred method of usage analytics in the UE. FIG. 5 is a diagram illustrating another embodiment of the system.

Hereafter, the UE 10 or Media Info Server 11 or Interest Report Server 12 refers to any device with networking capabilities. Furthermore, it may refer to functionality implemented in a plethora of devices. As non-limiting examples, it may entirely be possible for a part of the functionality of the Media Info Server 12 could be implemented in a television set or a PC or a set top box or another mobile phone. The Interest Report Server could be implemented as a web server, or an IMS Application Server.

Figure 1 describes the system for interest reports. It consists of a UE 10, a Media Info Server 11, a Interest Report Server 12 and a display 14. Each of the 3 devices (UE 10, Media Info Server 11, Interest Report Server 12) has interfaces to the other two devices. The Interest Report Server provides the Media Info Server with information related to the media. Non-limiting examples of the different information that could be provided are media name, media type, media characteristics, time/date information, session information. In addition, the Interest Report Server 12 could provide configuration of the Interest Reports. Non-limiting examples of such configuration are frequency of interest reports, device identification of the Media Info Server 11, address of server where Interest reports are to be sent, authentication information for optional authentication of UE 10, need for user interface request for interest, threshold probability to query user for interest, etc. The information sent by the Interest Report Server 12 is stored in the Media Info Server and the storage information is updated when the Interest Report Server 12 updates the information. Basically, the Media Info Server 11 is a local entity that is made aware of the media that is currently being sent to the Media Info Server. The above information can also be included as part of the Electronic Program Guide (EPG). The Media Info Server 11 then provides the Media Info to the UE 10 in at least 2 ways. The first way is when the UE 10 requests for information explicitly from the Media Info Server 11. The second way is to send above information as part of IP multicast information. In this way, a UE can get the information without querying the Media Info Server 11. Either of the methods will achieve the objective of getting media info to the UE 10. Either or both of the methods could be implemented in a Info Transmission module in the Media Info Server 11. The UE 10 decides to get the media info when it is triggered to do so. The trigger can be various things: non-limiting examples are that the UE 10 detects the WLAN SSID that it can associate to be in a certain location, or UE has a location area defined by GPS co-ordinates and a trigger is received whenever the UE 10 is in such an area, or the UE 10 is a cell-ID that is identifiable as a certain location, or the user chooses a "home profile" option on the UE 10 or the UE explicitly asks the UE to start media info query. Here the user can be the owner of the phone of the service provider with which the owner of the phone has a contract with for phone subscription.

Once, there is a trigger to get the media info, the UE 10 uses the direct query or reading multicast information to obtain the media info. Once this is done, the UE 10 computes a graph of UE's distance from the display 14 vs probability of user interest using the display size as input. This is important because different display sizes mean different viewing distances. For example, if a laptop is the display 14 and is just 12 inches wide, a distance of more than 2-3 metres can be considered to have a low probability of user being close to the display 14. On the contrary, a display size of 50 inches a distance of 2-3 metres between the mobile phone and the display 14 conveys a higher probability of user being interested in the media. The graph need not be computed but can be preconfigured in the software for different screen sizes. Now the UE 10 calculates the distance between the UE 10 and display 14. The distance calculation algorithm is out of scope of this specification and various radio propagation models may be used to estimate the distance. Based on the distance calculated, the UE 10 estimates the probability of mobile phone being within viewing distance based on the chart computed or internally stored configurations. Based on the probability, the UE 10 could decide to analyze further or not. For example, if the current distance is very far and therefore corresponding probability of viewing is very low (e.g. < 10%), the UE 10 could stop further calculations and check again after some preconfigured time. Or if the further distance is very close to the display 14, the UE 10 could continue with its further usage analytics to confirm user is close to the UE 10. Such thresholds of probability where the UE 10 continues or does not continue with the analytics is configurable and person skilled in the art will be able to recognize that different configurations would still be within the concept explained within the specification.

The UE 10 is also capable of analyzing the time since the user physically input any information into the mobile phone. The various forms of input that can be keyboard input, touchpad input, pressing of any of the buttons on the phone such as volume control or camera, or changes in any of the sensors in phone such as gyroscope, compass, accelerometers, etc. The UE 10 could measure the time since the last user input. As done for the distance estimation part, the UE 10 either computes a plot of time passed since last input versus probability of usage or uses a preconfigured mapping between the two. Further parameters such as using different probabilities for different types of input could be used. For example, if typing is considered as the last input, we can infer that there is high probability that the user has typed on the phone. But if, we can only know that the phone's position changed recently, then we can imagine anybody could have kept the phone in another place and we place a lower probability of the user near the UE 10. This way, the phone estimates a probability of the user being close to the UE 10. Again, there might be preset thresholds of low probability below which the UE considers the user to be high unlikely to be near the phone. So, the UE 10 could stop the current loop and check for user presence again after some preconfigured time.

In some cases, the user i.e. owner of the phone might be watching a video or listening to a song from the phone. In this case, the owner of the UE 10 might be sitting close to the display 14 but he could be engrossed in the multimedia in the UE 10 rather than the media on the display 14. The UE 10 again estimates whether the UE is displaying media or playing audio through the headphones or the speakers. Or if a browser is open, the owner could be busy browsing the Internet. The UE 10 could again compute the probability that the user is not completely focussed on the content in the mobile phone. Further, the UE 10 could use information such as profile settings to guess who is using the mobile phone. Some profiles could allow access to personal information such as email. Other profiles could be more limited and might offer access to only media. Such profile could be used to guess the current user of the UE 10.

After the above checks have been made, the UE 10 computes the overall probability of the user watching the media on TV. One example of such a computation assumes that at least the distance check and the usage analytics to be independent, that is, position of the UE 10 from the display 14 is independent of whether the user is using the UE 10. In the usage analytics part, we can check whether the phone has been used recently or not and if so how long back. Further, we can imagine that the estimated probability of owner of the phone using it is independent of whether output is being used extensively. This way, we can come up with various ways of calculating probability by also studying human behaviour around mobile phones. The intention of this specification is to specify the different data we could use to estimate the probability.

Once the probability of owner of the UE 10 watching the TV has been estimated, the UE 10 then uses either the address provided by the Media Info or a pre-configured address of the Interest Report Server 12. The UE 10 could also provide the device identification of the Media Info Server 11.

The Interest Report Server 12 receives the media info from the UE 10. The probability is received and processed by the probability processing module in the Interest Report Server 12. Once it receives this info, there are many ways this information can be used in real time. One way is to verify the profile of the user and customize the advertisements that are shown in between broadcast content. The advertisements could be unicast in between the broadcast content. Or customized advertisements could be stored in Media Info Server 11 and the Media Info Server 11 could play the customized advertisements during the advertisement breaks.

The display 14 is an electronic device that displays the media to the user. It is entirely possible that the Media Info Server 11 can be implemented inside the display 14.

Figure 2 is the apparatus of the UE 10. The modules shown in the figure are relevant to this invention, and other modules that are inherent in a mobile phone such as radio, memory, processors, sensors are not shown here but are implicitly assumed to be present. It consists of an Interest Report Trigger Module 27 that checks for need to compute Interest Reports. The Interest Report Trigger Module 27 may trigger the Interest Report generation in various ways: non-limiting examples are that the UE detects the WLAN SSID that it can associate to be in a certain location, or UE has a location area defined by GPS co-ordinates and a trigger is received whenever the UE 10 is in such an area, or the UE 10 is a cell-ID that is identifiable as a certain location, or the user chooses a "home profile" option on the UE 10 or the UE explicitly asks the UE to start media info query. Here the user can be owner of the phone of the service provider with which the owner of the phone has a contract with for phone subscription. It consists of a Media Info Acquisition Module 21 that is responsible for retrieving media info from the Media Info Server 11. The media info includes information related to the media and configuration information that is used in generating interest reports. The Media Info Acquisition Module 21 could get the media either through querying the Media Info Server or receiving the information through broadcast/multicast. The Distance Estimation Module 23 estimates the distance between display 14 and the UE 10 using various possible algorithms, non-limiting examples are using radio based propagation model. It is used to estimate the relative distance between the UE 10 and the display 14. The Output Monitoring Module 26 measures the type of output used recently and the time since it has last been used. The various non-limiting outputs it monitors are mobile display and speakers. Further, it may have also monitor the active applications that are running currently. The type of output and the timestamp of the last output is provided to the Interest Estimation Module 25.The Input Monitoring Module 22 checks whether the user is interacting with the UE 10. The interactions can be via the keyboard, touch pad, microphone or any other input modules that the UE 10 has. For example, it may even be the movement of the phone and changes in the gyroscope or accelerometer readings. The Input Monitoring Module 22 also checks the timestamp of the last input. The type of input and the timestamp of the last input is provided to the Interest Estimation Module 25.

The Remote UI Module 26 is an application residing in the UE 10 that is used to remotely control the display 14. The Remote UI Module 26 is queried by the Interest Estimation Module 26 to check whether the Remote UI Module 26 a) is running currently and b) is controlling the display 14 that is attached to the Media Info Server 11.

The UI Module 24 is a user interface component in the UE 10. It queries the user of his interest in the media currently being shown in the display 14. The query can be triggered when the service provider explicitly wishes to know whether the user is interested in the media currently displayed. Based on the user answer, the Interest Estimation Module 25 can report a corresponding probability of interest to the Interest Report Server 12.

The User Identification Module 27 is used to confirm the identification of the user currently using the phone. This can be done if the UE 10 has implemented user profiles on the phone. For example, the owner of the phone may have enabled a limited profile when he lends his UE 10 to his kids. In this case, the User Identification Module 27 knows that it is unlikely for the user to be using the phone right now. In other cases, the owner may have a specific password for his login to the UE 10. Such information is passed on to the Interest Estimation Module 25.

The Interest Estimation Module 25 is the central probability-estimating module relevant to interest reports in the UE 10. It receives input parameters from Input Monitoring Module 22, Distance Estimation Module 23, Output Monitoring Module 26, Remote UI Module 26, UI Module 24, User Identification Module 27. The exact algorithm used to analyze the usage of the UE 10 can be service provider independent or even vendor dependent. The Interest Estimation Module may have mapping tables that map various parameters to probability estimates for that event. Example: it may map the distance of UE 10 to display to a certain probability that user may be watching the media.

Figure 3 illustrates the method used to estimate the probability of the user watching the media on the display. Step 30 is the step is the trigger for media info acquisition. The trigger can be implemented in various ways: non-limiting examples are the UE 10 detects the WLAN SSID that it can associate to be in a certain location, or UE has a location area defined by GPS co-ordinates and a trigger is received whenever the UE 10 is in such an area, or the UE 10 is a cell-ID that is identifiable as a certain location, or the user chooses a "home profile" option on the UE 10 or the UE explicitly asks the UE to start media info query. Step 31 is the media acquisition step. The UE 10 receives Media related information from the Media Info Server 11. Non-limiting examples of the different information that could be provided are media name, media type, media characteristics, time/date information, session information. In addition, the Interest Report Server 12 could provide configuration of the Interest Reports. Non-limiting examples of such configuration are frequency of interest reports, device identification of the Media Info Server 11, address of server where Interest reports are to be sent, authentication information for optional authentication of UE 10, need for user interface request for interest, threshold probability to query user for interest, etc. Step 32 is the step of Usage Analytics. Here the UE 10 checks the probability of user being close to the UE 10 by checking the recent usage characteristics of UE 10. The UE 10 then sends the calculated probability to the Interest Report Server 12 as shown in Step 33.

Figure 4 is an embodiment of the possible steps that could be used to analyze the possibility of user being close to the UE 10. The figure explains one variation of the steps involved. It is entirely possible to perform the steps in a different order as well. As shown in Step 40, the UE 10 estimates the distance between display 14. The UE 10 may use various techniques; non-limiting examples are usage of radio based propagation models. Once the distance is measured, the UE 10 can also use the screen size of the display 14 it received during the media info acquisition to compute a probability of the UE 10 being within viewing distance of the display 14. If probability of the UE 10 being within viewing distance is within a certain threshold value, the UE 10 then checks whether the identity of the user is the same as that of the owner, as shown in step 41. This can be done if the UE 10 has implemented user profiles on the phone. For example, the owner of the UE 10 may have enabled the use of a limited profile when he lends his UE 10 to his kids. In this case, UE 10 knows that it is unlikely for the user to be using the phone right now. In other cases, the owner may have a specific password (text or biometric or face recognition or other techniques) for his login to the UE 10. Such information can be used to increase the accuracy of identifying the user. Based on this knowledge, the UE 10 can assign a probability that the owner of the UE 10 is the current user.

Next, as shown in Step 42, the UE checks whether a) the Remote UI application is running currently and b) the Remote UI application is controlling the display 14 that is attached to the Media Info Server 11. If the Remote UI application is running, then the probability of the user being close to the display and interested in the media in the display is very high. If the probability is high enough at this point, the UE 10 may choose to report the probability to the Interest Report Server 12.

Next, as shown in Step 43, the UE 10 analyzes the time since the user physically input any information into the mobile phone. The various forms of input that can be keyboard input, touchpad input, pressing of any of the buttons on the phone such as volume control or camera, or changes in any of the sensors in phone such as gyroscope, compass, accelerometers, etc. The UE 10 measures the time since the last user input. The UE 10 computes a probability of usage based on the time. Further parameters such as using different probabilities for different types of input could be used. For example, if typing is considered as the last input, we can infer that there is high probability that the user has typed on the phone. But if, we can only know that the phone's position changed recently, then we can imagine anybody could have kept the phone in another place and we place a lower probability of the user near the UE 10. This way, the phone estimates a probability of the user being close to the UE 10. Again, there might be preset thresholds of low probability below which the UE considers the user to be high unlikely to be near the phone. So, the UE 10 could stop the current loop and check for user presence again after some preconfigured time.

In Step S44, the UE 10 checks whether the Output modules of the UE 10 are being used. The UE 10 then checks the type of output used recently and the time since it has last been used. The various non-limiting outputs it monitors are mobile display and speakers. Further, it may have also monitor the active applications that are running currently.

In Step 45, the UE 10 can request the user through a user interface query about whether he is interested in the media. Such requests are generally better to be avoided as it creates an irritation for the user watching the content. But there are ways to soften this requirement. One way is to ask the user only if the probability of user being close to TV is between a certain high and low threshold. For example, if probability is below 50% and above 30%, the user can be requested. Another option is to always ask the user for this information in return for free media broadcast to the user.

In Step 46, the UE 10 estimates the probability of the user being close the UE 10, and therefore the probability of the user being close to the display 14. One variation of the method to compute the probability is as follows: Consider the probability of UE's distance from display 14, probability that user is owner, and probability of user being close to UE 10 to be independent. So, these three probabilities can be multiplied. The probability of user being close to UE 10 can be computed using input/output analytics. The time stamp of last input and type of input is checked. This is compared with time stamp of last output usage, for example the time when the display screen was locked. The later of the two time stamps is considered more reliable and used to calculate probability. For example, if user typed 10 minutes ago but the screen was active 2 minutes ago, we can consider the output time stamp to compute probability. We can further increase the accuracy of the output by verifying the user identification again.

Once the probability is computed, it can be reported to the Interest Report Server. If configured to do so, the UE 10 can also send the values used in calculation of the final probability such as distance from TV, time since last, etc.

Figure 5 shows another embodiment of the system. In this system, the Media Server 13 is separated from the Interest Report Server 12 and managed by a different business entity. In this embodiment, the Media Info Server 11 is owned/serviced by the Media Server 13 and the Interest Report Server 12 services the UE 10. The UE 10 and the Media Info Server 11 therefore belong to different domains. The Interest Report Server 12 is a service offered by the Service provider of the UE 10 to external Content Providers such as Media Server 13. The Interest Report Server provides the profiles of the UEs that are within viewing distance of the Media Info Server 11 managed by the Media Server 13. The Interest Report Server 12 can protect privacy of the user by only releasing user identity agnostic information such as age and sex.

An example usage of the system is as follows: A teenager and a parent are watching a sitcom broadcast show. Each of them has their own mobile phones. The mobile phones detect being at home location and trigger media info acquisition. The mobile phones receive the information of the media and the configuration parameters such as address of the Interest Report Server 12. Based on the location of the UE 10 and the usage statistics of the UE 10, a probability of presence is computed and sent to the Interest Report Server 12. The Interest Report Server 12 extracts the profiles of the particular users and provides the relevant information to the Media Server 13. The Media Server 13 now receives information that an adult male of age 45 and a female teen of age 14 are currently watching the media on Media Info Server 11 number B45678V. Now, the Media Server 13 can unicast customized advertisements of rock concerts in the particular city and inform the Media Info Server 11 of the times when unicast media are to replace the broadcast advertisements. In this way, the advertisements can be customized to the viewers in real time.

Another example of the use of the system is in a public display system installed for example in a train. There could be 1 or more televisions in each coach of the train wherein the television broadcasts the Media Info. The television could include the modules of the Display and the Media Info Server. As many people are watching the advertisements, the operator of the public display system can receive information of whom are the people watching the particular advertisements in the coach. If in particular, the user has directly indicated interest in the display, the Media Server 13 could not only send customized advertisements to the television but also send customized advertisements to each specific mobile phone.

Claims (35)

  1. A user equipment used in a system of interest reports, comprising:
    a Media Info Acquisition module that receives media info from a Media Info Server; and
    an Interest Estimation Module that computes the probability of user interest in the media based on usage statistics of the user equipment and informs the probability of user watching media to an interest report server.
  2. The user equipment according to claim 1, wherein the initiation of media info acquisitions is performed when the distance to the display is detected to be within a certain threshold.
  3. The user equipment according to claim 2, wherein the probability of the user equipment being within viewing distance of display is calculated.
  4. The user equipment according to claim 3, wherein the size of the display is considered in computing the probability of the user equipment being within viewing distance of display.
  5. The user equipment according to claim 3, wherein the distance of the user equipment from the display is considered in computing the probability of the user equipment being within viewing distance of display.
  6. The user equipment according to claim 1, wherein the information of the user equipment remotely controlling the display is considered in computing the probability of the probability of the user watching the media.
  7. The user equipment according to claim 1, wherein the time estimated since a user input modules have been used is considered in computing the probability of the probability of the user watching the media.
  8. The user equipment according to claim 7, wherein the time estimated since the keyboard has been used is considered in computing the probability of the probability of the user watching the media.
  9. The user equipment according to claim 7, wherein the time estimated since the touch pad has been used is considered in computing the probability of the probability of the user watching the media.
  10. The user equipment according to claim 7, wherein the time estimated since the microphone has been used is considered in computing the probability of the probability of the user watching the media.
  11. The user equipment according to claim 7, wherein the time estimated since the external buttons have been pressed is considered in computing the probability of the probability of the user watching the media.
  12. The user equipment according to claim 1, wherein the time estimated since an output module has been used is considered in computing the probability of the probability of the user watching the media.
  13. The user equipment according to claim 12, wherein the output module is a display of the user equipment.
  14. The user equipment according to claim 12, wherein the output module is an audio speaker of the user equipment.
  15. The user equipment according to claim 1, wherein the Media Info Acquisition Module receives contact information of the Interest Report Server from the Media Info Server.
  16. A system of interest reports, comprising a media info server, a user equipment and an Interest report server, wherein
    the media info server comprises a Media Info Transmission module that provides the media information to the user equipment,
    the user equipment comprises:
    a Media Info Acquisition module that receives media info from a Media Info Server; and
    an Interest Estimation Module that computes the probability of user interest in the media based on usage statistics of the user equipment and informs the probability of user watching media to an interest report server, and
    the Interest report server comprises a probability processing module that receives the probability of user watching media to an interest report server.
  17. The system according to claim 16, wherein customized advertisements are sent after receiving the probability of user watching the media.
  18. The system according to claim 16, wherein customized advertisements sent by the Interest Report Server replace the broadcast advertisements.
  19. A method of Interest reports, comprising the steps of:
    providing information related to current media being shown on a display;
    computing the probability of user interest in the media based on usage statistics of the user equipment; and
    receiving probability of user watching media
  20. The method according to claim 19, further comprising the step of initiating the media info acquisitions when it detects the distance to the display to be within a certain threshold.
  21. The method according to claim 19, further comprising the step of computing the probability of the user equipment being within viewing distance of display.
  22. The method according to claim 21, further comprising the step of considering the size of the display in computing the probability of the user equipment being within viewing distance of display.
  23. The method according to claim 21, further comprising the step of the considering the distance of the user equipment from the display in computing the probability of the user equipment being within viewing distance of display.
  24. The method according to claim 19, further comprising the step of judging whether it is currently controlling the display remotely.
  25. The method according to claim 19, further comprising the step of estimating the time since a user input modules have been used.
  26. The method according to claim 25, further comprising the step of estimating the time since the keyboard has been used.
  27. The method according to claim 25, further comprising the step of estimating the time since the touch pad has been used.
  28. The method according to claim 25, further comprising the step of estimating the time since the microphone has been used.
  29. The method according to claim 25, further comprising the step of estimating the time when external buttons have been pressed.
  30. The method according to claim 19, further comprising the step of estimating the time since output modules have been used.
  31. The method according to claim 30, further comprising the step of estimating the time when display has been active.
  32. The method according to claim 30, further comprising the step of estimating the time when audio output has been active.
  33. The method according to claim 19, further comprising the step of providing contact information of the Interest Report Server.
  34. The method according to claim 19, further comprising the step of sending customized advertisements to the Media Info Server after receiving the probability of user watching the media on the display.
  35. The method according to claim 19, further comprising the step of replacing the broadcast advertisements with the customized advertisements sent by the Interest Report Server.
PCT/JP2010/006519 2010-11-05 2010-11-05 Method, system and apparatus for interest reports WO2012059960A1 (en)

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