WO2014034163A1 - Information processor and method for displaying recommended program - Google Patents

Information processor and method for displaying recommended program Download PDF

Info

Publication number
WO2014034163A1
WO2014034163A1 PCT/JP2013/058187 JP2013058187W WO2014034163A1 WO 2014034163 A1 WO2014034163 A1 WO 2014034163A1 JP 2013058187 W JP2013058187 W JP 2013058187W WO 2014034163 A1 WO2014034163 A1 WO 2014034163A1
Authority
WO
WIPO (PCT)
Prior art keywords
program
recommended
programs
operation history
preference information
Prior art date
Application number
PCT/JP2013/058187
Other languages
French (fr)
Inventor
Yasukazu Higuchi
Yuji Irie
Toyokazu Itakura
Original Assignee
Kabushiki Kaisha Toshiba
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Kabushiki Kaisha Toshiba filed Critical Kabushiki Kaisha Toshiba
Publication of WO2014034163A1 publication Critical patent/WO2014034163A1/en

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • H04N21/4668—Learning process for intelligent management, e.g. learning user preferences for recommending movies for recommending content, e.g. movies
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/41—Structure of client; Structure of client peripherals
    • H04N21/422—Input-only peripherals, i.e. input devices connected to specially adapted client devices, e.g. global positioning system [GPS]
    • H04N21/42204—User interfaces specially adapted for controlling a client device through a remote control device; Remote control devices therefor
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • H04N21/4667—Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/47—End-user applications
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/47—End-user applications
    • H04N21/475—End-user interface for inputting end-user data, e.g. personal identification number [PIN], preference data
    • H04N21/4755—End-user interface for inputting end-user data, e.g. personal identification number [PIN], preference data for defining user preferences, e.g. favourite actors or genre
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/47—End-user applications
    • H04N21/482—End-user interface for program selection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00—Details of television systems
    • H04N5/76—Television signal recording

Definitions

  • Embodiments described herein relate generally to an information processor and a method for displaying a recommended program.
  • FIG. 1 is an exemplary perspective external view of one example of a digital television according to an embodiment
  • FIG. 2 is an exemplary block diagram illustrating functions of the digital television in the present embodiment
  • FIG. 3 is an exemplary flowchart of a processing for displaying recommended programs on the digital television in the present embodiment.
  • FIG. 4 is an exemplary view of an example of a display of the recommended programs in the digital television in the present embodiment .
  • an information processor comprises: a storage controller; an acquisition module; and a display controller.
  • the storage controller is configured to store at least one operation history of at ' least one program in a storage module.
  • the acquisition module is configured to acquire preference information of a user based on the at least one operation history stored in the storage module at a predetermined timing.
  • the display controller is configured to select at least one program based on the preference information as at least one recommended program, and display the at least one selected recommended program on a display.
  • the display controller is configured to select, when a number of the at least one operation history is less than a predetermined number, at least one program that satisfies a predetermined condition as the at least one recommended program.
  • an information processor and a method for displaying a recommended program according to the present embodiment are explained in conjunction with the drawings.
  • an information processor having functions for acquiring the preference information of a user based on at least one operation history of a processing concerning at least one program, and displaying at least one program based on the acquired preference information on a display, such as a recorder, may be applicable.
  • FIG. 1 is a perspective external view illustrating one example of the digital television according to the present embodiment .
  • a digital television 100 has the external appearance of a rectangular shape as viewed in a front view from the front side thereof (as viewed in a planar view with respect to the front face thereof) .
  • the digital television 100 is provided with a casing 2 and a liquid crystal display (LCD) panel 3.
  • the LCD panel is provided with a casing 2 and a liquid crystal display (LCD) panel 3.
  • LCD liquid crystal display
  • FIG. 3 is a display that receives video signals from a recommended program provider 116 described later (see FIG. 2) and displays videos such as still images or videos.
  • the casing 2 is supported by a support
  • FIG. 2 is a block diagram illustrating functions of the digital television in the present embodiment.
  • the digital television 100 in the present embodiment is provided with a user operation input module 101, a user operation processor 102, a first management module 103 for operation histories, an operation history storage module 104, a personal preference learning module 105, a second management module 106 for results of learning of personal preference, a learned result storage module 107, a first acquisition module 108 for recommended programs, a recommended program selector 109, a degree-of-learning calculator 110, a second acquisition module 111 for operation history information, a third acquisition module 112 for learned personal preference information, a first selector 113 of personal-preference-based recommended programs, a program information storage module 114, a second selector 115 of non-personal-preference-based recommended programs, and the recommended program provider 116.
  • each of the operation history storage module 104, the learned result storage module 107, and the program information storage module 114 is configured by a generally used storage medium such as a hard disk drive (HDD) , an optical disk, a memory card, or a random access memory (RAM) .
  • HDD hard disk drive
  • RAM random access memory
  • the user operation input module 101 receives an instruction of an operation (a user operation) concerning a broadcast program (hereinafter, referred to as a user operation instruction) from a remote controller, a tablet terminal, or the like.
  • a user operation instruction for instructing various kinds of processing such as timer recording, recording, reproducing, or viewing of the broadcast program.
  • the user operation processor 102 performs various kinds of processing such as timer recording, recording, reproducing, or viewing of the broadcast program in response to the user operation instruction received from the user operation input module 101. Furthermore, the user operation processor 102 transmits the user operation instruction received from the user operation input module 101 to the first management module 103.
  • the digital television 100 has a long-duration automatic simultaneous recording function for recording the broadcast programs of a plurality of channels automatically and simultaneously for many hours.
  • the programs recorded by the long-duration automatic simultaneous recording function can be used.
  • a program selected as the recommended program described later is not limited to the program recorded by the long-duration automatic simultaneous recording function, and may be a program scheduled to be broadcasted in the future based on program list information, a program recorded by usual program-designated recording, or a program capable of being operated (being acquired) by the digital television 100 from among programs stored in an external device such as a digital television set or a personal computer (PC) on the network to which the digital television 100 is connected.
  • PC personal computer
  • the user operation processor 102 instructs the first acquisition module 108 to acquire a list of recommended programs when the user operation instruction received by the user operation input module 101 instructs users to provide (display) recommended programs (hereinafter, referred to as recommended programs) .
  • the first management module 103 functions as a storage controller that receives the user operation instruction from the user operation processor 102, and stores a history of the user operation instruction (the operation instruction for instructing various kinds of processing such as the above-mentioned timer recording, recording, reproducing, or viewing of the broadcast program, for example) received as an operation history in the operation history storage module 104.
  • the first management module 103 stores the operation history and operation history information including an operation date and time at which the user operation instruction with respect to the corresponding operation history is received in the operation history storage module 104.
  • the first management module 103 specifies an ID (hereinafter, referred to as a user ID) for identifying a user before its operation or at the time of its operation, so that the first management module 103 also stores operation history information including the user ID specified as the information of the user who has performed the operation, in the operation history storage module 104.
  • an ID hereinafter, referred to as a user ID
  • the personal preference learning module 105 functions as an acquisition module that acquires an operation history from the operation history storage module 104 via the first management module 103 at a predetermined acquisition timing, and learns (acquires) the preference information of the user based on the acquired operation history. For example, the personal preference learning module 105 acquires the operation history from the operation history storage module 104 at each predetermined date and time or every predetermined period, and acquires the preference information of the user based on the acquired operation history. Furthermore, the personal preference learning module 105 transmits the learned preference information of the user to the second management module 106.
  • the second management module 106 stores, in the learned result storage module 107: the preference information of the user learned by the personal preference learning module 105; and learned personal preference information that includes a learning date and time at which the preference information of the user has been learned.
  • the first acquisition module 108, the recommended program selector 109, the degree-of-learning calculator 110, the second acquisition module 111, the third acquisition module 112, the first selector 113, the second selector 115, and the recommended program provider 116 function as a display controller that select at least one program based on the preference information of the user learned
  • the personal preference learning module 105 (acquired) by the personal preference learning module 105 as at least one recommended program, and display the at least one recommended program selected on the LCD panel 3.
  • FIG. 3 is a flowchart illustrating the flow of processing for displaying recommended programs on the digital television set in the present embodiment .
  • the first acquisition module 108 instructs the recommended program selector 109 to select at least one recommended program corresponding to preference information of a user. Then, the recommended program selector 109 instructs the degree-of-learning calculator 110 to calculate degree of learning.
  • the degree of learning means the accuracy of the preference information of the user that is learned by the personal preference learning module 105; that is, the degree of learning indicates whether the preference information of the user is learned using sufficient operation histories and is high in reliability.
  • the degree of learning is defined as a value obtained by dividing the number of the operation histories used for learning the preference information of the user by a predetermined threshold value.
  • the degree of learning is defined as the value obtained by dividing the number of the operation histories used for learning the preference information of the user by a predetermined threshold value
  • the degree of learning is not limited thereto.
  • the degree of learning may be defined as described below. That is, immediately after the preference information is learned for the first time, the degree of learning may be set to a predetermined initial degree of learning. Then, along with an increase in the number of times a recommended program is operated based on the preference information with respect to the number of selection of the recommended program, the degree of learning is set higher. On the other hand, along with a decrease in the number of times a recommended program is operated based on the preference information with respect to the number of selection of the recommended program, the degree of learning is set lower .
  • the degree-of-learning calculator 110 first instructs the second acquisition module 111 to acquire the operation history information.
  • the second acquisition module 111 acquires the operation history information including the oldest operation date and time from the operation history storage module 104 via the first management module 103 (S301) .
  • the degree-of-learning calculator 110 instructs the third acquisition module 112 to acquire the learned personal preference information.
  • the third acquisition module 112 acquires the learned personal preference information including a learning date and time at which the preference information has- been learned last time (the latest learning date and time) from the learned result storage module 107 via the second management module 106 (S302 ) .
  • the degree-of-learning calculator 110 instructs the second acquisition module 111 to acquire the number of operation histories stored at an operation date and time prior to the latest learning date and time acquired.
  • the second acquisition module 111 acquires the number of operation histories stored with the operation history information including an operation date and time prior to the latest learning date and time acquired by the third acquisition module 112 from among the operation histories stored in the operation history storage module 104 (S303) . Furthermore, the
  • the degree-of-learning calculator 110 instructs the third acquisition module 112 to acquire the preference information stored with the learned personal preference information including the latest learning date and time acquired.
  • the third acquisition module 112 acquires the preference information stored with the learned personal preference information including the latest learning date and time from the learned result storage module 107 via the second management module 106 (S303) .
  • the degree-of-learning calculator 110 calculates the degree of learning (S304). To be more specific, the
  • the degree-of-learning calculator 110 compares the operation date and time included in the operation history information acquired by the second acquisition module 111 with the learning date and time included in the learned personal preference information acquired by the third acquisition module 112.
  • the degree-of-learning calculator 110 sets the degree of learning to zero to bring the degree of learning into a state that the learning of the preference information has not been performed.
  • the degree-of-learning calculator 110 calculates a value by dividing the number of operation histories acquired by the second acquisition module 111 by the predetermined threshold value, as the degree of learning.
  • the recommended program selector 109 determines whether the preference information has already been learned based on the degree of learning calculated by the degree-of-learning calculator 110 (S305) . When the degree of learning calculated is not zero, the recommended program selector 109 determines that the preference information has already been learned (Yes at S305) , and instructs the first selector 113 to select at least one recommended program.. The first selector 113 acquires the learned personal preference information from the second management module 106 to select at least one program based on the acquired preference information from among the programs of which program information thereof is stored in the program information storage module 114 (S306) .
  • the recommended program selector 109 determines whether the preference information is sufficiently learned based on the degree of learning calculated by the degree-of-learning calculator 110 (S307) . To be more specific, the recommended program selector 109 determines that the preference information is sufficiently learned when the degree of learning calculated by the degree-of-learning calculator 110 is equal to or larger than 1. That is, the recommended program selector 109 determines that the preference information is sufficiently learned when the number of operation histories acquired by the second acquisition module 111 is equal to or larger than the predetermined threshold value.
  • the recommended program selector 109 determines that the preference information is not learned (No at S305) , or when the recommended program selector 109 determines that the preference information is insufficiently learned (No at S307), the recommended program selector 109 instructs the second selector 115 to select at least one recommended program that is not based on the preference information.
  • the second selector 115 selects at least one program which satisfies a predetermined condition and not based on the preference information, from among programs in which program information thereof is stored in the program information storage module 114 (S308) .
  • the second selector 115 selects the predetermined number of latest recorded programs (50 programs, for example) from among programs of a plurality of channels that are recorded by using the long-duration automatic simultaneous recording function.
  • the second selector 115 may select at least one program related to at least one program lastly displayed on the LCD panel 3.
  • the second selector 115 may acquire at least one program based on the preference information of at least one of other users from an external device or the like such as another digital television connected via a network (not illustrated in the drawings) , and select the at least one program acquired.
  • the second selector 115 selects at least one program that satisfies the predetermined condition and not based on the preference information, by using at least one of the above-mentioned three methods for selecting programs: however, the method for selecting programs is not limited thereto. That is to say, for example, as the at least one program that satisfies the predetermined condition and not based on the preference information, the second selector 115 may select at least one program set as at least one recommended program in other digital television, select at least one program set as at least one recommended program in a server for distributing broadcast programs, or the like, from among programs of a plurality of channels that are recorded by using the long-duration automatic simultaneous recording function .
  • the recommended program selector 109 selects at least one recommended program to be provided to users from among the programs selected by the first selector 113 and the programs selected by the second selector 115 depending on the degree of learning calculated by the degree-of-learning ! calculator 110 (S309) .
  • the recommended program selector 109 selects, when the degree of learning calculated is equal to or larger than 1 and the recommended program selector 109 determines that the preference information is sufficiently learned, the programs selected by the first selector 113 as the recommended programs to be provided to the users.
  • the recommended program selector 109 increases a number of programs, which is to be selected as the recommended programs and is based on the preference information. Further, when the number of acquired operation histories is increased while the number of acquired operation histories is smaller than a predetermined number, the recommended program selector 109 increases a ratio of the number of programs to be selected based on the preference information as the recommended programs.
  • the recommended program selector 109 selects, from the programs selected by the first selector 113, a number of recommended programs obtained by multiplying the maximum number of programs capable of being selected as the recommended programs (hereinafter, referred to as "the maximum number of programs") by the degree of learning as a ratio. Further, the recommended program selector 109 selects a remaining number of the recommended programs from the programs selected by the second selector 115. That is to say, for example, when the calculated degree of learning is 0.7 and the maximum number of programs is 50, the recommended program selector 109 selects, from the programs selected by the first selector 113, 35 recommended programs by multiplying 50 by 0.7. Further, the recommended program selector 109 selects 15 recommended programs by subtracting 35 from 50, from the programs selected by the second selector 115.
  • the recommended program selector 109 selects, from among the programs selected by the first selector 113 and as the recommended programs, a number of programs obtained by multiplying the maximum number of programs by the calculated degree of learning. Furthermore, the recommended program selector 109 selects, from the programs selected by the second selector 115 and as the recommended programs, a number of programs obtained by multiplying the maximum number of programs by a value Which is obtained by subtracting the degree of learning from 1.
  • the recommended program selector 109 selects recommended programs only from the programs selected by the second selector 115.
  • the recommended program selector 109 increases the number of programs to be selected based on the preference information as the recommended programs or increases the ratio of the number of programs to be selected based on the preference information as the recommended programs, within the predetermined maximum number of programs.
  • the recommended program selector 109 changes the ratio of the number of programs, which is to be selected based on the preference information as the recommended programs, to the predetermined maximum number of programs, depending on the degree of learning.
  • the present embodiment is not limited to such a configuration.
  • the recommended program selector 109 may increase the number of programs to be selected based on the preference information as the recommended programs or increase the ratio of the number of programs to be selected based on the preference information as the recommended programs, without setting an upper limit to the number of programs capable of being selected as the recommended programs (that is, the maximum number of programs) .
  • the recommended program selector 109 selects,: from the programs selected by the first selector 113 and as the recommended programs, a number of programs obtained by multiplying the total number of the programs selected by the first selector 113 by the degree of learning as a ratio.
  • the recommended program selector 109 selects, from the programs selected by the second selector 115 and as the recommended programs, a number of programs obtained by multiplying the total number of the programs selected by the second selector 115 by a value which is obtained by subtracting the degree of learning from 1 (1-learning degree) as a ratio. For example, when the degree of learning is 0.7, the number of programs selected by the first selector 113 is 100, and the number of programs selected by the second selector 115 is 50, the recommended program selector 109 selects, from the programs selected by the first selector 113 and as the recommended programs, 70 programs a number of which is obtained by multiplying 100 by 0.7.
  • the recommended program selector 109 selects, from among the programs selected by the second selector 115 and as the recommended programs, 15 programs the number of which is obtained by multiplying 50 by the number obtained by subtracting 0.7 from 1. That is, the recommended program selector 109 selects 85 recommended programs in total.
  • the programs may be selected in the descending order of a predetermined recommendation degree or selected in the ascending/descending order of a program broadcasting date and time.
  • the selection order such as the descending order of the recommendation degree or the ascending/descending order of the program broadcasting date and time may be optionally selected by the user .
  • the selection order may be determined based on program information to which the order of the recommendation degree, the program broadcast date and time, or the like can be imparted, and the present embodiment is not limited to such a configuration that the selection order is determined by specific information.
  • the recommended program provider 116 acquires
  • the digital television 100 is capable of providing the recommended programs to users.
  • FIG. 4 is a view illustrating an example of displaying recommended programs in the digital television in the present embodiment.
  • the recommended program provider 116 displays a recommended program list L superimposed on the video image of a broadcast program being viewed on the LCD panel 3.
  • the contents (broadcast dates and times, channels, titles, program contents, or the like) n of the selected recommended programs are listed, the contents n being acquired from program table data (EIT) stored in the program information storage module 114.
  • EIT program table data
  • an operation confirmation dialog D of the selected recommended program is displayed.
  • the dialog D becomes a viewing confirmation dialog.
  • the selected program is a
  • the dialog D becomes a viewing-recording reservation confirmation dialog.
  • the operation confirmation dialog D displays thereon buttons bl and b2 enabling the User to indicate whether the user views or reserves the recording or viewing of the selected program. These buttons bl and b2 are operated by using the remote controller or the like (not illustrated in the drawing) .
  • the method for displaying (providing) the recommended programs is not limited to the example of displaying the recommended programs, the example being illustrated in FIG. 4 and, for example, the recommended program list L may be displayed on the whole screen of the LCD panel 3.'
  • a program executed in the digital television 100 of the present embodiment is provided in the form of the read only memory (ROM) or the like into which the program is integrated in advance.
  • the program executed in the digital television 100 of the present embodiment may be provided in the form of the storage medium capable of being read by the computer; that is, a CD-ROM, a flexible disk (FD) , a CD-R, a digital versatile disk (DVD), or the like in which the program is stored in an installable or executable file.
  • the program executed in the digital television 100 of the present embodiment may be stored on a computer connected to a network such as the Internet and provided by downloading via the network.
  • the program executed in the digital television 100 of the present embodiment may be provided or distributed via a network such as the Internet.
  • the program executed in the digital television 100 of the present embodiment is configured of modules including the
  • a central processing unit reads out the program from the above-mentioned ROM to execute the program, and thus the above-mentioned respective modules are loaded on a main memory, and the user operation input module 101, the user operation processor 102, the first management module 103, the personal preference learning module 105, the second management module 106, the first acquisition module 108, the recommended program selector 109, the degree-of-learning calculator 110, the second acquisition module 111, the third acquisition module 112, the first selector 113, the second selector 115, and the . recommended program provider 116 are generated on the main memory.
  • CPU central processing unit
  • modules of the systems described herein can be implemented as software applications, hardware and/or software modules, or components on one or more computers, such as servers. While the various modules are illustrated separately, they may share some or all of the same underlying logic or code.

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Databases & Information Systems (AREA)
  • Human Computer Interaction (AREA)
  • Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)
  • Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)

Abstract

According to one embodiment, an information processor includes a storage controller, an acquisition module, and a display controller. The storage controller stores at least one operation history of at least one program in a storage module. The acquisition module acquires preference information of a user based on the at least one operation history stored in the storage module at a predetermined timing. The display controller selects at least one program based on the preference information as at least one recommended program, and displays the at least one selected recommended program on a display. The display controller selects, when a number of the at least one operation history is less than a predetermined number, at least one program that satisfies a predetermined condition as the at least one recommended program.

Description

DESCRIPTION
INFORMATION PROCESSOR AND METHOD FOR DISPLAYING RECOMMENDED PROGRAM
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is based upon and claims the benefit of priority from Japanese Patent Application No. 2012-193554, filed September 3, 2012; the entire contents of which are incorporated herein by reference.
FIELD
[0002] Embodiments described herein relate generally to an information processor and a method for displaying a recommended program.
BACKGROUND
[0003] There has been disclosed a technique for recording operation histories concerning programs to be viewed, learning the preference of a viewer from the recorded operation histories, and recommending programs to the viewer based on the learned preference.
[0004] However, in the conventional technique, programs cannot be recommended to the viewer when the operation histories concerning the program to be viewed are insufficiently recorded or when the preference of the viewer based on the recorded operation histories has not been learned, e.g., when a device has been displayed in a store or a device is a brand new device.
CITATION LIST PATENT LITERATURE
[0005] Japanese patent Application Laid-open No. 2008-005200
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] A general architecture that implements the various features of the invention will now be described with reference to the drawings. The drawings and the associated descriptions are provided to illustrate embodiments of the invention and not to limit the scope of the invention.
[0007] FIG. 1 is an exemplary perspective external view of one example of a digital television according to an embodiment;
FIG. 2 is an exemplary block diagram illustrating functions of the digital television in the present embodiment;
FIG. 3 is an exemplary flowchart of a processing for displaying recommended programs on the digital television in the present embodiment; and
FIG. 4 is an exemplary view of an example of a display of the recommended programs in the digital television in the present embodiment .
DETAILED DESCRIPTION
[0008] In general, according to one embodiment, an information processor comprises: a storage controller; an acquisition module; and a display controller. The storage controller is configured to store at least one operation history of at' least one program in a storage module. The acquisition module is configured to acquire preference information of a user based on the at least one operation history stored in the storage module at a predetermined timing. The display controller is configured to select at least one program based on the preference information as at least one recommended program, and display the at least one selected recommended program on a display. The display controller is configured to select, when a number of the at least one operation history is less than a predetermined number, at least one program that satisfies a predetermined condition as the at least one recommended program.
[0009] Hereinafter, an information processor and a method for displaying a recommended program according to the present embodiment are explained in conjunction with the drawings. Here, in the present embodiment, although a digital television is explained, an information processor having functions for acquiring the preference information of a user based on at least one operation history of a processing concerning at least one program, and displaying at least one program based on the acquired preference information on a display, such as a recorder, may be applicable.
[0010] FIG. 1 is a perspective external view illustrating one example of the digital television according to the present embodiment . As illustrated in FIG. 1, a digital television 100 has the external appearance of a rectangular shape as viewed in a front view from the front side thereof (as viewed in a planar view with respect to the front face thereof) . The digital television 100 is provided with a casing 2 and a liquid crystal display (LCD) panel 3. The LCD panel
3 is a display that receives video signals from a recommended program provider 116 described later (see FIG. 2) and displays videos such as still images or videos. The casing 2 is supported by a support
4.
[0011] FIG. 2 is a block diagram illustrating functions of the digital television in the present embodiment. As illustrated in FIG. 2, the digital television 100 in the present embodiment is provided with a user operation input module 101, a user operation processor 102, a first management module 103 for operation histories, an operation history storage module 104, a personal preference learning module 105, a second management module 106 for results of learning of personal preference, a learned result storage module 107, a first acquisition module 108 for recommended programs, a recommended program selector 109, a degree-of-learning calculator 110, a second acquisition module 111 for operation history information, a third acquisition module 112 for learned personal preference information, a first selector 113 of personal-preference-based recommended programs, a program information storage module 114, a second selector 115 of non-personal-preference-based recommended programs, and the recommended program provider 116. Here, each of the operation history storage module 104, the learned result storage module 107, and the program information storage module 114 is configured by a generally used storage medium such as a hard disk drive (HDD) , an optical disk, a memory card, or a random access memory (RAM) .
[0012] The user operation input module 101 receives an instruction of an operation (a user operation) concerning a broadcast program (hereinafter, referred to as a user operation instruction) from a remote controller, a tablet terminal, or the like. For example, the user operation input module 101 receives the user operation instruction for instructing various kinds of processing such as timer recording, recording, reproducing, or viewing of the broadcast program.
[0013] The user operation processor 102 performs various kinds of processing such as timer recording, recording, reproducing, or viewing of the broadcast program in response to the user operation instruction received from the user operation input module 101. Furthermore, the user operation processor 102 transmits the user operation instruction received from the user operation input module 101 to the first management module 103.
[0014] In the present embodiment, the digital television 100 has a long-duration automatic simultaneous recording function for recording the broadcast programs of a plurality of channels automatically and simultaneously for many hours. Thus, as a recommended program described later, the programs recorded by the long-duration automatic simultaneous recording function can be used. Here, a program selected as the recommended program described later is not limited to the program recorded by the long-duration automatic simultaneous recording function, and may be a program scheduled to be broadcasted in the future based on program list information, a program recorded by usual program-designated recording, or a program capable of being operated (being acquired) by the digital television 100 from among programs stored in an external device such as a digital television set or a personal computer (PC) on the network to which the digital television 100 is connected.
[0015] Furthermore, in the present embodiment, the user operation processor 102 instructs the first acquisition module 108 to acquire a list of recommended programs when the user operation instruction received by the user operation input module 101 instructs users to provide (display) recommended programs (hereinafter, referred to as recommended programs) .
[0016] The first management module 103 functions as a storage controller that receives the user operation instruction from the user operation processor 102, and stores a history of the user operation instruction (the operation instruction for instructing various kinds of processing such as the above-mentioned timer recording, recording, reproducing, or viewing of the broadcast program, for example) received as an operation history in the operation history storage module 104. In the present embodiment, the first management module 103 stores the operation history and operation history information including an operation date and time at which the user operation instruction with respect to the corresponding operation history is received in the operation history storage module 104. Furthermore, the first management module 103 specifies an ID (hereinafter, referred to as a user ID) for identifying a user before its operation or at the time of its operation, so that the first management module 103 also stores operation history information including the user ID specified as the information of the user who has performed the operation, in the operation history storage module 104.
[0017] The personal preference learning module 105 functions as an acquisition module that acquires an operation history from the operation history storage module 104 via the first management module 103 at a predetermined acquisition timing, and learns (acquires) the preference information of the user based on the acquired operation history. For example, the personal preference learning module 105 acquires the operation history from the operation history storage module 104 at each predetermined date and time or every predetermined period, and acquires the preference information of the user based on the acquired operation history. Furthermore, the personal preference learning module 105 transmits the learned preference information of the user to the second management module 106.
[0018] The second management module 106 stores, in the learned result storage module 107: the preference information of the user learned by the personal preference learning module 105; and learned personal preference information that includes a learning date and time at which the preference information of the user has been learned.
[0019] The first acquisition module 108, the recommended program selector 109, the degree-of-learning calculator 110, the second acquisition module 111, the third acquisition module 112, the first selector 113, the second selector 115, and the recommended program provider 116 function as a display controller that select at least one program based on the preference information of the user learned
(acquired) by the personal preference learning module 105 as at least one recommended program, and display the at least one recommended program selected on the LCD panel 3.
[0020] Here, in conjunction with FIG. 2 and FIG. 3, the first acquisition module 108, the recommended program selector 109, the degree-of-learning calculator 110, the second acquisition module 111, the third acquisition module 112, the first selector 113, the program information storage module 114, the second selector 115, and the recommended program provider 116 are explained in detail. FIG. 3 is a flowchart illustrating the flow of processing for displaying recommended programs on the digital television set in the present embodiment .
[0021] When the user operation processor 102 provides instruction for acquiring a list of recommended programs, the first acquisition module 108 instructs the recommended program selector 109 to select at least one recommended program corresponding to preference information of a user. Then, the recommended program selector 109 instructs the degree-of-learning calculator 110 to calculate degree of learning. Here, the degree of learning means the accuracy of the preference information of the user that is learned by the personal preference learning module 105; that is, the degree of learning indicates whether the preference information of the user is learned using sufficient operation histories and is high in reliability. In the present embodiment, the degree of learning is defined as a value obtained by dividing the number of the operation histories used for learning the preference information of the user by a predetermined threshold value. Here, in the present embodiment, although the degree of learning is defined as the value obtained by dividing the number of the operation histories used for learning the preference information of the user by a predetermined threshold value, the degree of learning is not limited thereto. For example, the degree of learning may be defined as described below. That is, immediately after the preference information is learned for the first time, the degree of learning may be set to a predetermined initial degree of learning. Then, along with an increase in the number of times a recommended program is operated based on the preference information with respect to the number of selection of the recommended program, the degree of learning is set higher. On the other hand, along with a decrease in the number of times a recommended program is operated based on the preference information with respect to the number of selection of the recommended program, the degree of learning is set lower .
[0022] When the calculation of the degree of learning is instructed, the degree-of-learning calculator 110 first instructs the second acquisition module 111 to acquire the operation history information. The second acquisition module 111 acquires the operation history information including the oldest operation date and time from the operation history storage module 104 via the first management module 103 (S301) . Furthermore, the degree-of-learning calculator 110 instructs the third acquisition module 112 to acquire the learned personal preference information. The third acquisition module 112 acquires the learned personal preference information including a learning date and time at which the preference information has- been learned last time (the latest learning date and time) from the learned result storage module 107 via the second management module 106 (S302 ) .
[0023] Next, the degree-of-learning calculator 110 instructs the second acquisition module 111 to acquire the number of operation histories stored at an operation date and time prior to the latest learning date and time acquired. The second acquisition module 111 acquires the number of operation histories stored with the operation history information including an operation date and time prior to the latest learning date and time acquired by the third acquisition module 112 from among the operation histories stored in the operation history storage module 104 (S303) . Furthermore, the
degree-of-learning calculator 110 instructs the third acquisition module 112 to acquire the preference information stored with the learned personal preference information including the latest learning date and time acquired. The third acquisition module 112 acquires the preference information stored with the learned personal preference information including the latest learning date and time from the learned result storage module 107 via the second management module 106 (S303) .
[0024] Next, the degree-of-learning calculator 110 calculates the degree of learning (S304). To be more specific, the
degree-of-learning calculator 110 compares the operation date and time included in the operation history information acquired by the second acquisition module 111 with the learning date and time included in the learned personal preference information acquired by the third acquisition module 112. When the learning date and time is a date and time prior to the operation date and time, the operation history has not been stored for the time of learning and hence, the degree-of-learning calculator 110 sets the degree of learning to zero to bring the degree of learning into a state that the learning of the preference information has not been performed. By contrast, when the learning" date and time is a date and time after the operation date and time, the degree-of-learning calculator 110 calculates a value by dividing the number of operation histories acquired by the second acquisition module 111 by the predetermined threshold value, as the degree of learning.
[0025] The recommended program selector 109 determines whether the preference information has already been learned based on the degree of learning calculated by the degree-of-learning calculator 110 (S305) . When the degree of learning calculated is not zero, the recommended program selector 109 determines that the preference information has already been learned (Yes at S305) , and instructs the first selector 113 to select at least one recommended program.. The first selector 113 acquires the learned personal preference information from the second management module 106 to select at least one program based on the acquired preference information from among the programs of which program information thereof is stored in the program information storage module 114 (S306) . Next, the recommended program selector 109 determines whether the preference information is sufficiently learned based on the degree of learning calculated by the degree-of-learning calculator 110 (S307) . To be more specific, the recommended program selector 109 determines that the preference information is sufficiently learned when the degree of learning calculated by the degree-of-learning calculator 110 is equal to or larger than 1. That is, the recommended program selector 109 determines that the preference information is sufficiently learned when the number of operation histories acquired by the second acquisition module 111 is equal to or larger than the predetermined threshold value.
[0026] When the recommended program selector 109 determines that the preference information is not learned (No at S305) , or when the recommended program selector 109 determines that the preference information is insufficiently learned (No at S307), the recommended program selector 109 instructs the second selector 115 to select at least one recommended program that is not based on the preference information. The second selector 115 selects at least one program which satisfies a predetermined condition and not based on the preference information, from among programs in which program information thereof is stored in the program information storage module 114 (S308) . To be more specific, the second selector 115 selects the predetermined number of latest recorded programs (50 programs, for example) from among programs of a plurality of channels that are recorded by using the long-duration automatic simultaneous recording function. The second selector 115 may select at least one program related to at least one program lastly displayed on the LCD panel 3. The second selector 115 may acquire at least one program based on the preference information of at least one of other users from an external device or the like such as another digital television connected via a network (not illustrated in the drawings) , and select the at least one program acquired. In the present embodiment, the second selector 115 selects at least one program that satisfies the predetermined condition and not based on the preference information, by using at least one of the above-mentioned three methods for selecting programs: however, the method for selecting programs is not limited thereto. That is to say, for example, as the at least one program that satisfies the predetermined condition and not based on the preference information, the second selector 115 may select at least one program set as at least one recommended program in other digital television, select at least one program set as at least one recommended program in a server for distributing broadcast programs, or the like, from among programs of a plurality of channels that are recorded by using the long-duration automatic simultaneous recording function .
[0027] The recommended program selector 109 selects at least one recommended program to be provided to users from among the programs selected by the first selector 113 and the programs selected by the second selector 115 depending on the degree of learning calculated by the degree-of-learning! calculator 110 (S309) . To be more specific, the recommended program selector 109 selects, when the degree of learning calculated is equal to or larger than 1 and the recommended program selector 109 determines that the preference information is sufficiently learned, the programs selected by the first selector 113 as the recommended programs to be provided to the users.
[0028] When the number of acquired operation histories is increased while the calculated degree of learning is smaller than 1 (that is, when the number of operation histories acquired is smaller than the predetermined number) , the recommended program selector 109 increases a number of programs, which is to be selected as the recommended programs and is based on the preference information. Further, when the number of acquired operation histories is increased while the number of acquired operation histories is smaller than a predetermined number, the recommended program selector 109 increases a ratio of the number of programs to be selected based on the preference information as the recommended programs. To be more specific, when the calculated degree of learning is smaller than 1, the recommended program selector 109 selects, from the programs selected by the first selector 113, a number of recommended programs obtained by multiplying the maximum number of programs capable of being selected as the recommended programs (hereinafter, referred to as "the maximum number of programs") by the degree of learning as a ratio. Further, the recommended program selector 109 selects a remaining number of the recommended programs from the programs selected by the second selector 115. That is to say, for example, when the calculated degree of learning is 0.7 and the maximum number of programs is 50, the recommended program selector 109 selects, from the programs selected by the first selector 113, 35 recommended programs by multiplying 50 by 0.7. Further, the recommended program selector 109 selects 15 recommended programs by subtracting 35 from 50, from the programs selected by the second selector 115.
[0029] That is, when the calculated degree of learning is smaller than 1, the recommended program selector 109 selects, from among the programs selected by the first selector 113 and as the recommended programs, a number of programs obtained by multiplying the maximum number of programs by the calculated degree of learning. Furthermore, the recommended program selector 109 selects, from the programs selected by the second selector 115 and as the recommended programs, a number of programs obtained by multiplying the maximum number of programs by a value Which is obtained by subtracting the degree of learning from 1. Here, when the degree of learning calculated is zero, the recommended program selector 109 selects recommended programs only from the programs selected by the second selector 115. [0030] In the above-mentioned examples, when the number of acquired operation histories is increased, the recommended program selector 109 increases the number of programs to be selected based on the preference information as the recommended programs or increases the ratio of the number of programs to be selected based on the preference information as the recommended programs, within the predetermined maximum number of programs. In other words, the recommended program selector 109 changes the ratio of the number of programs, which is to be selected based on the preference information as the recommended programs, to the predetermined maximum number of programs, depending on the degree of learning. However, the present embodiment is not limited to such a configuration. That is to say, when the number of acquired operation histories is increased, the recommended program selector 109 may increase the number of programs to be selected based on the preference information as the recommended programs or increase the ratio of the number of programs to be selected based on the preference information as the recommended programs, without setting an upper limit to the number of programs capable of being selected as the recommended programs (that is, the maximum number of programs) . To be more specific, the recommended program selector 109 selects,: from the programs selected by the first selector 113 and as the recommended programs, a number of programs obtained by multiplying the total number of the programs selected by the first selector 113 by the degree of learning as a ratio. Then, the recommended program selector 109 selects, from the programs selected by the second selector 115 and as the recommended programs, a number of programs obtained by multiplying the total number of the programs selected by the second selector 115 by a value which is obtained by subtracting the degree of learning from 1 (1-learning degree) as a ratio. For example, when the degree of learning is 0.7, the number of programs selected by the first selector 113 is 100, and the number of programs selected by the second selector 115 is 50, the recommended program selector 109 selects, from the programs selected by the first selector 113 and as the recommended programs, 70 programs a number of which is obtained by multiplying 100 by 0.7. Further, the recommended program selector 109 selects, from among the programs selected by the second selector 115 and as the recommended programs, 15 programs the number of which is obtained by multiplying 50 by the number obtained by subtracting 0.7 from 1. That is, the recommended program selector 109 selects 85 recommended programs in total.
[0031] Here, regarding a selection order in selecting a number of programs corresponding to the degree of learning from the programs selected by the first selector 113 and the second selector 115, the programs may be selected in the descending order of a predetermined recommendation degree or selected in the ascending/descending order of a program broadcasting date and time. Furthermore, the selection order such as the descending order of the recommendation degree or the ascending/descending order of the program broadcasting date and time may be optionally selected by the user . In the present embodiment, the selection order may be determined based on program information to which the order of the recommendation degree, the program broadcast date and time, or the like can be imparted, and the present embodiment is not limited to such a configuration that the selection order is determined by specific information.
[0032] The recommended program provider 116 acquires
recommended programs selected by the recommended program selector 109 via the first acquisition module 108 to display the acquired recommended programs on the LCD panel 3 (S310) . Due to such a configuration, the digital television 100 is capable of providing the recommended programs to users.
[0033] FIG. 4 is a view illustrating an example of displaying recommended programs in the digital television in the present embodiment. As illustrated in FIG.4, the recommended program provider 116 displays a recommended program list L superimposed on the video image of a broadcast program being viewed on the LCD panel 3. On the recommended program list L, the contents (broadcast dates and times, channels, titles, program contents, or the like) n of the selected recommended programs are listed, the contents n being acquired from program table data (EIT) stored in the program information storage module 114. Furthermore, when a program is selected by a remote controller or the like (not illustrated in the drawing) from the recommended program list L, an operation confirmation dialog D of the selected recommended program is displayed. When the selected program is a recorded program, the dialog D becomes a viewing confirmation dialog. When the selected program is a
broadcast-scheduled program, the dialog D becomes a viewing-recording reservation confirmation dialog. The operation confirmation dialog D displays thereon buttons bl and b2 enabling the User to indicate whether the user views or reserves the recording or viewing of the selected program. These buttons bl and b2 are operated by using the remote controller or the like (not illustrated in the drawing) . Here, the method for displaying (providing) the recommended programs is not limited to the example of displaying the recommended programs, the example being illustrated in FIG. 4 and, for example, the recommended program list L may be displayed on the whole screen of the LCD panel 3.'
[0034] As a message m included in a program proposal message M,
"Starting soon" while viewing a program, "There are programs recommended for you" while zapping, "There are programs recommended for you today" while no program is displayed, and the like can be' considered.
[0035] In this manner, according to the digital television 100 in the present embodiment, it is also possible to recommend programs in a device exhibited in the store or brand-new device.
[0036] Here, a program executed in the digital television 100 of the present embodiment is provided in the form of the read only memory (ROM) or the like into which the program is integrated in advance.. The program executed in the digital television 100 of the present embodiment may be provided in the form of the storage medium capable of being read by the computer; that is, a CD-ROM, a flexible disk (FD) , a CD-R, a digital versatile disk (DVD), or the like in which the program is stored in an installable or executable file. [0037] In addition, the program executed in the digital television 100 of the present embodiment may be stored on a computer connected to a network such as the Internet and provided by downloading via the network. The program executed in the digital television 100 of the present embodiment may be provided or distributed via a network such as the Internet.
[0038] The program executed in the digital television 100 of the present embodiment is configured of modules including the
above-mentioned respective modules (the user operation input module 101, the user operation processor 102, the first management module 103, the personal preference learning module 105, the second management module 106, the first acquisition module 108, the recommended program selector 109, the degree-of-learning calculator 110, the second acquisition module 111, the third acquisition module 112, the first selector 113, the second selector 115, and the recommended program provider 116) . As actual hardware, a central processing unit (CPU) reads out the program from the above-mentioned ROM to execute the program, and thus the above-mentioned respective modules are loaded on a main memory, and the user operation input module 101, the user operation processor 102, the first management module 103, the personal preference learning module 105, the second management module 106, the first acquisition module 108, the recommended program selector 109, the degree-of-learning calculator 110, the second acquisition module 111, the third acquisition module 112, the first selector 113, the second selector 115, and the. recommended program provider 116 are generated on the main memory.
[0039] Moreover, the various modules of the systems described herein can be implemented as software applications, hardware and/or software modules, or components on one or more computers, such as servers. While the various modules are illustrated separately, they may share some or all of the same underlying logic or code.
[0040] While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel embodiments described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the embodiments described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or
modifications as would fall within the scope and spirit of the inventions .

Claims

1. An information processor comprising:
a storage controller configured to store at least one operation history concerning at least one program in a storage module;
an acquisition module configured to acquire preference information of a user based on the at least one operation history stored in the storage module at a. predetermined timing; and
a display controller configured .to select at least one program based on the preference information as at least one recommended program, and display the at least one selected recommended program on a display, wherein
the display controller is configured to select, when a number of the at least one operation history is less than a predetermined number, at least one program that satisfies a predetermined condition as the at least one recommended program.
2. The information processor of Claim 1, wherein the display controller is configured to increase a number of programs to be selected as the at least one recommended program based on the preference information, in accordance with an increase in the number of the at least one operation history.
3. The information processor of Claim 1 or 2, wherein the display controller is configured to increase a ratio of a number of programs, which is based on the preference information and to be selected as the at least one recommended program, in accordance with an increase in the number of the at least one operation history.
4. The information processor of any one of Claims 1 to 3, wherein the display controller is configured to select, when the number of the at least one operation history is smaller than the predetermined number, a predetermined number of latest recorded programs as the at least one recommended program from among simultaneously recorded programs of a plurality of channels.
5. The information processor of any one of Claims 1 to 4, wherein the display controller is configured to select, when the number of the at least one operation history is smaller than the predetermined number, at least one program related to at least one program lastly displayed on the display as the at least one recommended program.
6. The information processor of any one of Claims 1 to 5, wherein the display controller is configured to acquire, when the number of the at least one operation history is smaller than the predetermined number, at least one program which is based on preference information of at least one of other users, and select the at least one acquired program as the at least one recommended program.
7. A method for displaying a recommended program performed by an information processor, the method comprising:
storing at least one operation history concerning at least one program in a storage module;
acquiring preference information of a user based on the at least one operation history stored in the storage module at a predetermined timing; and
selecting at least one program based on the preference information as at least one recommended program, and displaying the at least one selected recommended program on a display (3) , wherein, when a number of the at least one operation history is less than a predetermined number, at least one program that satisfies, a predetermined condition is selected as the at least one recommended program.
8. An information processor comprising:
a storage controller configured to store at least one operation history concerning at least one program in a storage module;
a learning module configured to learn preference information of a user based on the at least one operation history stored in the storage module at a predetermined timing;
a calculator configured to calculate a degree of learning of the preference information based on the at least one operation history stored in the storage module and the preference information learned by the learning module;
a first selector configured to select at least one program based on the learned preference information;
a second selector configured to select at least one program based on information different from the learned preference information; and
a display controller configured to select, based on the calculated degree of learning and from the at least one program selected by the first selector and the at least one program selected by the second selector, at least one program to be presented to a user as at least one recommended program, and to display the at least one selected program on a display.
PCT/JP2013/058187 2012-09-03 2013-03-14 Information processor and method for displaying recommended program WO2014034163A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2012-193554 2012-09-03
JP2012193554A JP2014050053A (en) 2012-09-03 2012-09-03 Information processing apparatus and recommended program display method

Publications (1)

Publication Number Publication Date
WO2014034163A1 true WO2014034163A1 (en) 2014-03-06

Family

ID=50182991

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2013/058187 WO2014034163A1 (en) 2012-09-03 2013-03-14 Information processor and method for displaying recommended program

Country Status (2)

Country Link
JP (1) JP2014050053A (en)
WO (1) WO2014034163A1 (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2018037935A (en) * 2016-09-01 2018-03-08 シャープ株式会社 Content recommendation apparatus, content recommendation system, content recommendation method, and program
JP6627042B2 (en) * 2017-09-28 2020-01-08 有限会社ＮｅｔＡ Information processing apparatus, information processing method and program

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002025939A2 (en) * 2000-09-20 2002-03-28 Koninklijke Philips Electronics N.V. Television program recommender with automatic identification of changing viewer preferences
JP2005339523A (en) * 2004-04-26 2005-12-08 Matsushita Electric Ind Co Ltd Information providing apparatus and information providing method
JP2006050322A (en) * 2004-08-05 2006-02-16 Victor Co Of Japan Ltd User taste information providing system
JP2010183319A (en) * 2009-02-05 2010-08-19 Hitachi Software Eng Co Ltd Program recommendation apparatus
JP2011142468A (en) * 2010-01-06 2011-07-21 Sony Corp Information processing apparatus, information processing method, and program
US20110251988A1 (en) * 2008-12-23 2011-10-13 Axel Springer Digital Tv Guide Gmbh Adaptive implicit learning for recommender system

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002025939A2 (en) * 2000-09-20 2002-03-28 Koninklijke Philips Electronics N.V. Television program recommender with automatic identification of changing viewer preferences
JP2005339523A (en) * 2004-04-26 2005-12-08 Matsushita Electric Ind Co Ltd Information providing apparatus and information providing method
JP2006050322A (en) * 2004-08-05 2006-02-16 Victor Co Of Japan Ltd User taste information providing system
US20110251988A1 (en) * 2008-12-23 2011-10-13 Axel Springer Digital Tv Guide Gmbh Adaptive implicit learning for recommender system
JP2010183319A (en) * 2009-02-05 2010-08-19 Hitachi Software Eng Co Ltd Program recommendation apparatus
JP2011142468A (en) * 2010-01-06 2011-07-21 Sony Corp Information processing apparatus, information processing method, and program

Also Published As

Publication number Publication date
JP2014050053A (en) 2014-03-17

Similar Documents

Publication Publication Date Title
KR101015328B1 (en) Video recording conflict management and user interface
US8280226B2 (en) Content recorder multi-angle viewing and playback
CN101374214B (en) Information processing apparatus, information processing method
US9077951B2 (en) Television program selection system, recommendation method and recording method
EP3340612B1 (en) Systems and methods for indicating media asset access conflicts using a time bar
US8930992B2 (en) TV social network advertising
US11809478B2 (en) Systems and methods for arranging contextually related media assets
US20070074245A1 (en) Virtual channels
CN102054014B (en) Information processing apparatus, tuner, and information processing method
CN102523489A (en) Systems and methods for managing content
EP2605528A1 (en) Control method and display apparatus providing various types of content
EP3678380B1 (en) Electronic apparatus and control method thereof
WO2011022215A2 (en) Integrated user interface for internet-enabled tv
US10555044B2 (en) Systems and methods for control of channel surfing
WO2014034163A1 (en) Information processor and method for displaying recommended program
US20150163554A1 (en) Method, electronic device, and computer program product
US20170164050A1 (en) Presenting alternate content
US9912997B2 (en) System and method to determine content items and associated toggle triggers for a viewer
US20140089984A1 (en) Control device, control method, recording device, recording method, and program
CN113383556A (en) Viewing history analysis device
JP2007235193A (en) Recording/reproducing apparatus, program recording method, and program
JP2024050660A (en) System, method, and program for distributing live video
EP2785071A2 (en) System for synchronising and centralising event instructions and/or indicators in video/audio systems
Bhachu MASTER OF PHILOSOPHY
US20100138408A1 (en) Information Processing Apparatus and Information Processing Method

Legal Events

Date Code Title Description
WWE Wipo information: entry into national phase

Ref document number: 2013741958

Country of ref document: EP

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 13741958

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE