Channel recommendation method, device, storage medium and computer program product

Abstract

The present application discloses a channel recommendation method, device, storage medium and computer program product, the method comprising: upon receiving a display terminal start-up instruction, obtaining character information in the external environment where the display terminal is located; determining a person to be recommended from the external environment based on the character information, and obtaining a preset program recommendation list corresponding to the person to be recommended; and determining target broadcast program information from the program recommendation list.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a channel recommendation method, device, storage medium and computer program product. Background Art

[0002] The program lists in current display terminals are fixed. If a user wants to watch a certain program channel and does not remember the channel number, he needs to use a remote control to traverse one by one, which brings great inconvenience to the user. When the user calls up the program list, the program list can be sorted according to the user's viewing frequency of TV programs. However, since different users like to watch different TV channels and TV programs in different time periods, if the default or universal program push method is used, the personalized needs of users cannot be taken care of. The user's favorite programs are saved in advance, and the user still needs to manually select them when turning on the machine. That is, the user cannot quickly and conveniently switch to the channel he wants to watch when turning on the display terminal, and the efficiency of switching channels is low.

[0003] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present application is to provide a channel recommendation method, device, storage medium and computer program product, aiming to solve the technical problem of low efficiency of manual channel switching by users when a display terminal is started.

[0005] To achieve the above purpose, the present application proposes a channel recommendation method, which includes:

[0006] When receiving a display terminal start instruction, obtaining person information in the external environment where the display terminal is located;

[0007] Determine a person to be recommended from the external environment based on the person information, and obtain a preset program recommendation list corresponding to the person to be recommended;

[0008] The target broadcast program information is determined from the program recommendation list.

[0009] In addition, to achieve the above objectives, the present application also proposes a channel recommendation device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the channel recommendation method described above.

[0010] In addition, to achieve the above purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the channel recommendation method described above are implemented.

[0011] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, wherein the computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the channel recommendation method described above are implemented.

[0012] In the present application, when a display terminal power-on instruction is received, character information in the external environment in which the display terminal is located is obtained; based on the character information, a person to be recommended is determined from the external environment, and a preset program recommendation list corresponding to the person to be recommended is obtained; and target broadcast program information is determined from the program recommendation list.

[0013] The present application can identify the recommended users who use the display terminal in the external environment by acquiring the information of the characters in the external environment where the display terminal is located, determine the program to be played from the program recommendation list based on the preset program recommendation list corresponding to the recommended user, and play the channel where the program is located through the display terminal. Through the automated channel display process, the user's manual program selection operation is avoided, so that the user can directly watch the preferred program after turning on the TV, thereby reducing the time for the user to manually select the program and improving the channel switching efficiency when the display terminal is turned on. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0015] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 A flowchart of the first embodiment of the channel recommendation method of the present application is provided;

[0017] Figure 2 This is a directional push information architecture involved in a channel recommendation method according to an embodiment of the present application;

[0018] Figure 3 A schematic diagram of a program favorites folder involved in a directional push information architecture according to an embodiment of the present application;

[0019] Figure 4 A schematic diagram of historical records involved in a targeted push information architecture according to an embodiment of the present application;

[0020] Figure 5 This is a brief flowchart of a channel recommendation method according to an embodiment of the present application;

[0021] Figure 6 A schematic diagram of a process of performing channel recommendation based on program favorites in a channel recommendation method according to an embodiment of the present application;

[0022] Figure 7 A schematic diagram of a fuzzy recommendation process involved in a channel recommendation method according to an embodiment of the present application;

[0023] Figure 8 A schematic diagram of a brief process of creating a program favorite folder involved in a channel recommendation method according to an embodiment of the present application;

[0024] Fig. 9 This is a schematic diagram of the module structure of a channel recommendation device involved in a channel recommendation method according to an embodiment of the present application;

[0025] Fig.10 A schematic diagram of a simplified process of recording viewing time involved in a channel recommendation method according to an embodiment of the present application;

[0026] Fig.11 This is a schematic diagram of the device structure of the hardware operating environment involved in the channel recommendation method in the embodiment of the present application.

[0027] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0028] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0029] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0030] The main solution of the embodiment of the present application is: when receiving a display terminal power-on instruction, obtaining character information in the external environment where the display terminal is located; determining the person to be recommended from the external environment based on the character information, and obtaining a preset program recommendation list corresponding to the person to be recommended; determining the target playback program information from the program recommendation list.

[0031] In this embodiment, for the convenience of description, the following description is made with the channel recommendation device as the execution subject.

[0032] Since there is usually more than one user watching the TV at home, and these users may have different preferences for programs due to differences in age, gender, etc. If the default or universal program push method is used, the personalized needs of users cannot be taken care of, and directly saving the user's favorite programs for selection when turning on the TV still requires the user to manually select the program, that is, the user cannot watch his favorite program the first time he turns on the TV.

[0033] The present application provides a solution, which can identify the users to be recommended in the external environment who use the display terminal by acquiring the information of the people in the external environment where the display terminal is located, determine the program to be played from the program recommendation list based on the preset program recommendation list corresponding to the users to be recommended, and play the channel where the program is located through the display terminal. Through the automated channel display process, the user's manual program selection operation is avoided, so that the user can directly watch the preferred program after turning on the TV, thereby reducing the time for the user to manually select the program and improving the channel switching efficiency when the display terminal is turned on.

[0034] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a display terminal, etc., or an electronic device capable of realizing the above functions, a channel recommendation device, etc. The following takes the channel recommendation device as an example to illustrate this embodiment and the following embodiments.

[0035] Based on this, the present application embodiment provides a channel recommendation method, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the channel recommendation method of the present application.

[0036] In this embodiment, the channel recommendation method includes steps S10 to S40:

[0037] Step S10, when receiving the display terminal start instruction, obtaining the character information in the external environment where the display terminal is located;

[0038] It should be noted that the display terminal start-up instruction refers to a signal or command that triggers the display terminal device (such as a smart TV, monitor, etc.) to start. In a specific implementation, when a user starts the display terminal through a remote control, button or other means, the system will receive a start-up instruction. This instruction is a trigger signal for the device to start running, enter standby mode, or directly switch from a closed state to a working state. In modern display terminals such as smart TVs, the display terminal start-up instruction may also trigger a series of initialization operations, such as loading user settings, starting the operating system, etc.

[0039] When receiving the display terminal start-up instruction, obtain the character information in the external environment where the display terminal is located. The character information refers to the data about the characters in the external environment where the display terminal is located, specifically including the information representing the distribution of the characters and the identity of the characters. The character information can be obtained through devices such as image sensors and used for subsequent user identification, behavior analysis or personalized recommendations. It should be noted that the distribution of the characters includes the number and location distribution of the characters in the environment where the display terminal is located. For example, in the living room, if there are multiple family members watching TV, their positions and numbers can be sensed by the image sensor to obtain the distribution of the characters. The identity of the characters refers to the personal identity information of the characters in the environment where the display terminal is located, which can include name, age, gender, membership level, etc. By identifying the identity of the characters, their historical viewing records, preferences and other information can be obtained based on the identity information in the future, so as to provide more personalized program recommendations. It can be understood that by obtaining accurate character information, a basis is provided for the subsequent personalized program recommendations, so that programs that users may be interested in can be recommended more accurately.

[0040] Step S20, determining a person to be recommended from the external environment based on the person information, and obtaining a preset program recommendation list corresponding to the person to be recommended;

[0041] Based on the acquired character information, the person to be recommended is determined from the external environment. The person to be recommended refers to the user determined as the program recommendation target based on the current environmental information and user behavior. In the scenario of multiple people watching, the operator of the display terminal can be determined as the person to be recommended. In the scenario of single person watching, the person in the current environment is the person to be recommended.

[0042] Get the preset program recommendation list corresponding to the person to be recommended. The program recommendation list refers to a list containing programs that the person to be recommended may be interested in. The programs in the list can be sorted according to various factors, such as viewing time, ratings, popularity, etc. It should be noted that the preset program recommendation list can be generated based on the historical viewing records of the person to be recommended; it can also be a custom list pre-set by the person to be recommended, such as favorites and program lists created by the person to be recommended; it can also be generated from various programs based on the program preferences of the person to be recommended; it can also be determined by combining a custom list, historical viewing records and user preferences. There is no specific limitation here and it can be set according to actual needs.

[0043] Step S30: determining target broadcast program information from the program recommendation list.

[0044] It should be noted that the target broadcast program information refers to the program information of the program selected from the program recommendation list and to be broadcast on the display terminal. According to certain rules (such as current broadcast status, viewing time, rating, etc.), a program can be determined from the program recommendation list as the target broadcast program information, and the channel where the target broadcast program information is located can be jumped to. By automatically playing programs that the user may be interested in, the user does not need to manually select programs or channels, thereby saving the user's time and improving the efficiency of channel switching.

[0045] In a feasible implementation manner, the step S30: determining target broadcast program information from the program recommendation list includes:

[0046] Step S301, determining whether there is a preset key person in the external environment based on the character information;

[0047] In current smart TVs or home entertainment systems, with the diversification of family members (such as children, the elderly, and people with special interests, etc.), it becomes increasingly challenging to provide programs suitable for all family members. In order to ensure that key members of the family (such as children, the elderly, or people with special interests) can watch programs suitable for their age, interests, or needs, the special needs of these key members need to be considered when recommending programs. Therefore, this embodiment proposes to customize program screening rules based on the identity information of key members to ensure that they are provided with appropriate content, thereby improving the accuracy of program recommendations.

[0048] Key personnel refer to those who need to be pre-screened for programs. Key personnel can be children, the elderly, and other personnel who need to be classified for programs, or they can be those who have pre-set program preferences. There is no specific restriction here.

[0049] Step S302, if the key person exists, determining the preset program level and preset program type corresponding to the key person based on the identity information of the key person;

[0050] If there are key personnel, the preset program level and preset program type corresponding to the key personnel are determined based on the identity information of the key personnel. It should be noted that the program level refers to the classification or grading of television programs based on factors such as the content, nature, and suitable audience groups of the television programs. The program level corresponding to the key personnel is called the preset program level. The preset program level can be obtained according to the grading system based on the age of the key personnel, or it can be set according to demand. There is no restriction here. Different program levels represent different suitable viewing ages, content sensitivity or theme types. Program type refers to the type obtained by classifying television programs according to the theme, form, content and other characteristics of the television programs. For example, program types can include news, TV series, movies, variety shows, documentaries, etc. The preset types corresponding to key personnel for program screening are called preset program types.

[0051] Step S303: among the programs in the program recommendation list, the programs that meet the preset program level and the preset program type are determined as candidate broadcast program information, and target broadcast program information is determined from the candidate broadcast program information.

[0052] Programs whose program levels meet the preset program levels and whose program types meet the preset program types are selected from the program recommendation list to form candidate broadcast program information. One of the candidate broadcast programs is selected as the target broadcast program information. The process of determining the target broadcast program information is not described in detail here.

[0053] It is understandable that by formulating specific program screening rules for key personnel, it is possible to ensure that key personnel watch programs that are suitable for their age, interests or needs, thereby improving the suitability and satisfaction of the content, thereby enhancing the user experience. In addition, for groups that may need special protection, such as children or the elderly, limiting their access to inappropriate content through this implementation can provide additional safety guarantees and further improve the user experience.

[0054] In this embodiment, by acquiring information about people in the external environment where the display terminal is located, it is possible to identify users to be recommended in the external environment who are using the display terminal, and based on a preset program recommendation list corresponding to the users to be recommended, determine the program to be played from the program recommendation list, and play the channel where the program is located through the display terminal. Through the automated channel display process, the user's manual program selection operation is avoided, so that the user can directly watch the preferred program after turning on the TV, thereby reducing the time for the user to manually select the program and improving the channel switching efficiency when the display terminal is turned on.

[0055] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar contents as those in the first embodiment can be referred to the above description, and will not be described in detail later. On this basis, step S20: determining the person to be recommended from the external environment based on the person information includes:

[0056] Step S201, if the display terminal is in a state of being used by multiple people, obtaining device location information of a control device of the display terminal, and determining a person to be recommended from various persons in the external environment based on the device location information;

[0057] The multi-user use state refers to a state in which a display terminal is used by multiple users or may be used by different users in the same time period. In the multi-user use state, it is necessary to identify the user who is currently using or may be about to use the display terminal in order to provide personalized content or services.

[0058] When the display terminal is in a state of being used by multiple people, the user who is currently operating or is most likely to operate the terminal is determined. Specifically, the device location information of the control device of the display terminal is first obtained, and based on the device location information, the person who is closest to the device location or is most likely to be using the device is determined from various people in the external environment as the person to be recommended. It should be noted that the control device of the display terminal may be a remote control device that is connected to the display terminal for communication, such as a remote control, a game controller, a smart phone, etc. as a remote control device; the control device may also be a local control device of the display terminal, which may be a device integrated in or near the body of the display terminal that allows the user to operate it without an additional remote control. For example, televisions, displays, and computer monitors are equipped with some basic control buttons on their front panels or sides, such as power switches, volume adjustments, menu navigation, etc., that is, the display terminal itself can also be used as a local control device.

[0059] It can be understood that by determining the user who actually operates the display terminal, programs that meet the interests and needs of the user can be recommended more accurately, reducing the possibility of erroneous recommendations and making it easier for users to find programs that interest them.

[0060] Step S202: If the display terminal is in a single-person use state, the persons in the external environment are taken as persons to be recommended.

[0061] Single-user status refers to a status where a display terminal is used by only one user. When a display terminal is in single-user status, it indicates that only one person is currently using or may use the display terminal. Therefore, people in the external environment are directly used as persons to be recommended. In the single-user status, there is no need to obtain additional device location information and compare people, which simplifies the recommendation process, reduces system processing time, and enables users to obtain recommended programs faster, thereby improving recommendation efficiency.

[0062] In one feasible implementation, the step S201, the step of determining the person to be recommended from the persons in the external environment based on the device location information, includes:

[0063] Step S2011, determining the position information of each person in the external environment based on the person information;

[0064] Personnel location information refers to the position information of each person in the external environment relative to the display terminal or other reference points. Personnel location information can be obtained through sensors set on the display terminal (such as cameras, infrared sensors, etc.) and used to determine the distance, direction and other relationships between the person and the display terminal. In this implementation, the specific process of obtaining personnel location information is not described in detail.

[0065] Step S2012: The persons in the external environment whose position information matches the device location information are selected as persons to be recommended.

[0066] The device location information is used to describe the location information of the control device of the display terminal. The device location information can be obtained through GPS, Wi-Fi positioning and other technologies. When multiple people are using the device, the current location information of the control device of the display terminal is obtained, the personnel's position information is compared with the device location information, and the distance, direction and other differences between each person and the device are calculated to determine the person to be recommended: according to the comparison results, the person who is closest to the device, has the most consistent direction or is most likely to be operating the device is selected as the person to be recommended.

[0067] There are many ways to match the orientation information of personnel with the location information of equipment, which are not limited here. For example, in one feasible implementation, the matching can be based on distance and direction, traversing each person in the external environment (hereinafter referred to as environmental personnel), calculating the straight-line distance between the position of the environmental personnel and the position of the equipment; determining the position direction of the environmental personnel relative to the control device, such as east, south, west, north or a specific angle; and selecting the person closest to the equipment and with the most consistent direction from each environmental personnel as the person to be recommended.

[0068] In a feasible implementation manner, the step S20: the step of obtaining a preset program recommendation list corresponding to the person to be recommended, comprises:

[0069] Step S203, detecting whether there is a custom program list corresponding to the person to be recommended;

[0070] Check whether there is a custom program list previously created by the person to be recommended, and the custom program list contains programs manually added by the user according to personal preferences or specific needs. Exemplarily, obtain the unique identifier of the person to be recommended, and use the identifier to query whether there is a custom program list associated with the person in the database. If a matching custom program list is found, proceed to the next step; otherwise, continue to check the historical viewing record.

[0071] Step S204: if the custom program list exists, use the custom program list as a preset program recommendation list;

[0072] When it is detected that the person to be recommended has a customized program list, the list is used as the program list recommended to the user. In a specific implementation, all programs in the list can also be extracted from the database and displayed to the user in a preset format (such as a list, a grid, etc.) as a preset program recommendation list. It can be understood that by directly using the user-defined content, the user's personalized needs are met without the need for complex recommendation algorithm calculations, thereby improving the efficiency of program recommendation.

[0073] Step S205, if the customized program list does not exist, then checking whether there is a historical viewing record of the person to be recommended;

[0074] If no customized program list is found, it is detected whether the person to be recommended has a historical viewing record, which can reflect the user's viewing habits and preferences.

[0075] Step S206, if the historical viewing record exists, determining a preferred program tag from each preset program tag based on the historical viewing record, and determining the program list under the preferred program tag as the program recommendation list, wherein the preferred program tag is the program tag with the longest cumulative viewing time among each preset program tag;

[0076] If the historical viewing record exists, the program tags in the historical viewing record are analyzed to determine the user's preferred program tags, and the program list under the tag is used as the recommended content. It should be noted that program tags refer to tags used to describe program types, content and other features. Program tags are the basis for content classification and recommendation. By labeling programs with appropriate tags, the type and content of programs can be more accurately determined. Preferred program tags refer to program type tags that the user prefers, which are determined based on the user's viewing history.

[0077] The process of determining the preferred program label may be: traversing each preset program label, counting the total viewing time of all programs under the program label based on historical viewing records, determining the total viewing time as the cumulative viewing time of the preset program label, and after obtaining the cumulative viewing time of each preset program label, taking the program label with the longest cumulative viewing time among the preset program labels as the preferred program label. It can be understood that based on the user's actual viewing behavior, recommending the program that best meets his or her preferences can more accurately predict the user's preferences and improve the accuracy of program recommendations.

[0078] Step S207: If the historical viewing record does not exist, a user portrait is constructed based on the personal characteristics of the person to be recommended, and the program recommendation list is determined based on the user portrait.

[0079] Personnel characteristics refer to information that describes a person's identity, age, gender, occupation, behavior and other attributes. User portraits are user models built based on personnel characteristics and are used to describe personnel characteristics. User portraits usually include information on the user's age, gender, occupation, interests, hobbies, consumption habits and other aspects. The specific process of constructing user portraits is not restricted here and can be set according to actual needs.

[0080] When there is no customized program list and no historical viewing record, the user profile is constructed using the personnel characteristics of the person to be recommended, and recommendations are made based on the profile. The specific process may be: collecting the personnel characteristics of the person to be recommended; constructing the user profile using the personnel characteristics; searching the database for the most matching program list according to the user profile. For example, the user profile may be input into a preset program recommendation model to obtain a program recommendation list, wherein the program recommendation model is trained using the user profiles of different users as input data and the program recommendation lists of each user as labels. The specific training process and model structure are not limited here.

[0081] In a feasible implementation manner, the program recommendation list is the custom program list; the step S30: determining target broadcast program information from the program recommendation list includes:

[0082] Step S304: if there is a currently broadcasting program in the program recommendation list, and the number of the currently broadcasting program is one, the currently broadcasting program is used as the target broadcasting program information;

[0083] It is detected whether there is a currently broadcasting program (i.e., the currently playing program) in the custom program recommendation list, and it is detected that there is only one currently broadcasting program. If both conditions are met, the currently broadcasting program is selected as the target broadcasting program information. It can be understood that when there is a clear, currently broadcasting, and only program selection, directly selecting this program for playback reduces the user's operation complexity and improves the user's viewing convenience.

[0084] Step S305: If the currently playing program exists and the number of the programs is at least two, the program with the longest historical viewing time among the currently playing programs is determined as the target playing program information;

[0085] If there are multiple currently broadcasting programs in the custom program recommendation list, the program with the longest historical viewing time of the user is selected as the target playback program information. It can be understood that by considering the user's historical viewing time, more personalized program recommendations can be provided to the user, thereby improving user satisfaction.

[0086] Step S306: If the currently playing program does not exist, the predicted broadcast time of each program in the program recommendation list is determined based on the preset program preview information, and the program with the closest predicted broadcast time among the programs in the program recommendation list is determined as the target playing program information.

[0087] If there is no currently broadcasting program in the custom program recommendation list, a selection is made according to preset program preview information. Specifically, a program with the nearest broadcasting time is determined from various programs and is used as the target broadcasting program information.

[0088] In a feasible implementation manner, the program recommendation list is a list of programs under the preferred program label;

[0089] The step S30: determining target broadcast program information from the program recommendation list comprises:

[0090] Step S307, determining the viewing duration and viewing frequency of each program in the program recommendation list;

[0091] It should be noted that the program viewing time is the cumulative continuous time that the recommended person watches the program. The program viewing time can measure the preference of the recommended person for the program. The longer the program viewing time, the higher the interest of the recommended person in the program. The number of program viewing times refers to the number of times the recommended person watches the program. During the counting process, when the recommended person switches back to the program from other programs or watches the program when the terminal is turned on, the number of program viewing times for the program is accumulated to 1.

[0092] Step S308, traversing each program in the program recommendation list, weighting the viewing time of the currently traversed program by a first preset weight to obtain a first weight, weighting the viewing times of the currently traversed program by a second preset weight to obtain a second weight, and determining the sum of the first weight and the second weight as the viewing score of the currently traversed program;

[0093] Each program in the program recommendation list is traversed, and the currently traversed program is called the currently traversed program. For the currently traversed program, a first preset weight is multiplied by the viewing time to obtain a first weight, and a second preset weight is multiplied by the viewing times to obtain a second weight, and the sum of the first weight and the second weight is used as the viewing score of the current program. It should be noted that the sum of the first preset weight and the second preset weight is 1, and the specific value can be set according to actual needs and is not limited here.

[0094] Step S309: determine the program with the highest viewing score among the programs in the program recommendation list as target broadcast program information.

[0095] The higher the viewing score, the higher the interest of the person to be recommended in the program, and the more inclined the person to be recommended is to choose to play the program. The program with the highest viewing score is selected from the program recommendation list as the target program information to be played. It can be understood that by automatically selecting the highest-rated program, the time required for users to manually screen and select programs is reduced, the efficiency of program recommendations is improved, and the user's viewing experience is optimized.

[0096] In this embodiment, by acquiring information about people in the external environment where the display terminal is located, it is possible to identify users to be recommended in the external environment who are using the display terminal, and based on a preset program recommendation list corresponding to the users to be recommended, determine the program to be played from the program recommendation list, and play the channel where the program is located through the display terminal. Through the automated channel display process, the user's manual program selection operation is avoided, so that the user can directly watch the preferred program after turning on the TV, thereby reducing the time for the user to manually select the program and improving the channel switching efficiency when the display terminal is turned on.

[0097] For example, to help understand the implementation process of the channel recommendation method obtained by combining the first embodiment and the second embodiment, please refer to Figure 2 , Figure 2A targeted push information architecture involved in a channel recommendation method is provided, in which the push information corresponding to each user consists of three parts: facial data, program favorites (i.e., a custom program list), and historical records (i.e., historical viewing records). Among them, facial data is the user's facial sampling data, which is used by the TV to perform facial recognition on the audience and match the user in the targeted push information library. When a new user is created in the TV's targeted push information library, the TV will use a camera to record the user's facial information. Program favorites are a list of programs collected by the user, which serves as a reference for the TV to recommend programs, such as Figure 3 As shown in , the program favorites may include the program name, channel, program tag, and play time. The history record is the user's historical viewing record, which serves as a reference for TV program recommendations, such as Figure 4 As shown, the historical records include program names, channels, program tags, and historical viewing duration. In this embodiment, the historical records only retain information from the past month to ensure the timeliness of the historical records. The targeted push information architecture also includes recommended channels, which include popular programs under various program tags and programs favored by user groups of different ages and genders. The recommended channels are provided by the operator based on big data analysis and through the Internet.

[0098] Based on the above targeted information push architecture, please refer to Figure 5 The process of power-on channel recommendation can be: turn on the TV, detect the remote control position (that is, the device location information) through infrared and object recognition, match the user holding the remote control (that is, determine the person to be recommended) through face recognition, detect whether the match is successful, if the match is successful, detect whether the program favorites corresponding to the person to be recommended are empty, if not empty, load the program favorites (that is, determine the program favorites as the program recommendation list), if empty, make fuzzy recommendations. Figure 6 , the process of loading program favorites for program recommendation can be: loading program favorites, parsing SDT to obtain program information of all current channels, traversing program information favorites in program favorites that match the user, detecting whether there are any programs being broadcast, if not, reading future program previews from EPG and filtering favorite programs closest to the start time of broadcast, if so, filtering the programs being broadcast, detecting whether there is more than one filtered program, if there is more than one, selecting the program with the longest historical viewing time and jumping to the channel where the program is located, if there is only one filtered program, jumping to the channel where the program is located (that is, detecting whether there is a custom program list corresponding to the person to be recommended; if the custom program list exists, the custom program list is used as the preset program recommendation list). Please refer to Figure 7The fuzzy recommendation process can be: face recognition matches all viewers, detects whether all viewers can be matched, if all viewers can be matched, matches the user's historical viewing time accumulated by program label, selects the program label with the longest historical viewing time, and recommends the most popular program under the program label. If all viewers cannot be matched, face detection detects the age and gender of the audience, and performs cloud recommendation through big data analysis of user portraits (that is, if the custom program list does not exist, detects whether there is a historical viewing record of the person to be recommended; if there is a historical viewing record, determines a preferred program label from each preset program label based on the historical viewing record, and determines the program list under the preferred program label as the program recommendation list, wherein the preferred program label is the program label with the longest cumulative viewing time among each of the preset program labels; if the historical viewing record does not exist, constructs a user portrait based on the personnel characteristics of the person to be recommended, and determines the program recommendation list based on the user portrait).

[0099] In this embodiment, please refer to Figure 8 , the process of a user collecting a program and creating a program favorite can be: the user adds the program to the favorite, detects the remote control position through infrared and object recognition, matches the user using the remote control through face recognition, detects whether the user is successfully matched, if so, parses SDT to obtain the current program information and adds the current program to the matching user's program favorites, if not, creates a new user to record the face information, then parses SDT to obtain the current program information and adds the current program to the matching user's program favorites. Please refer to Fig. 9 , the process of recording the viewing time of each user separately can be: record the viewing time, if the program being played changes, match all viewers through face recognition, detect whether all viewers can be matched, if so, filter out the matched users and the newly created users, parse SDT to obtain the information of the program currently being played, and then check the historical record of the user to accumulate the historical viewing time; if not, create a new user for the audience who is not matched, record the face information, and filter out the matched users and the newly created users, parse SDT to obtain the information of the program currently being played, and then check the historical record of the user to accumulate the historical viewing time.

[0100] As can be seen from the above, there are three different levels of push solutions in this embodiment, including precise recommendation based on program favorites, fuzzy recommendation based on historical viewing records, and fuzzy recommendation based on big data analysis of audience group user portraits. Fig.10As shown, the program favorites contain the least programs, but they are all programs selected by users themselves, so the programs that users want to watch can be accurately recommended based on them; the historical viewing records contain information about the programs watched by each user in the past month and the historical viewing time, so the program tags that the audience likes can be analyzed based on this, and then popular programs under the program tags can be recommended; based on the user portraits obtained by big data analysis for different user groups, combined with the age and gender of the audience determined by face detection, users can be distinguished by age group and gender, and programs that similar user groups may like can be fuzzily recommended.

[0101] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the channel recommendation method of the present application. More simple transformations based on this technical concept are all within the protection scope of the present application.

[0102] The present application also provides a channel recommendation device. The channel recommendation device provided by the present application adopts the channel recommendation method in the above embodiment, which can solve the technical problem of low efficiency of manual channel switching by users. Compared with the prior art, the beneficial effects of the channel recommendation device provided by the present application are the same as the beneficial effects of the channel recommendation method provided by the above embodiment, and other technical features in the channel recommendation device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0103] The present application provides a channel recommendation device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the channel recommendation method in the above-mentioned embodiment.

[0104] Reference below Fig.11 , which shows a schematic diagram of the structure of a channel recommendation device suitable for implementing the embodiment of the present application. The channel recommendation device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Fig.11 The channel recommendation device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0105] like Fig.11As shown, the channel recommendation device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the channel recommendation device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the channel recommendation device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a channel recommendation device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0106] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0107] The channel recommendation device provided by the present application adopts the channel recommendation method in the above embodiment, which can solve the technical problem of low efficiency of manual channel switching by users. Compared with the prior art, the beneficial effects of the channel recommendation device provided by the present application are the same as the beneficial effects of the channel recommendation method provided by the above embodiment, and other technical features in the channel recommendation device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0108] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0109] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0110] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the channel recommendation method in the above-mentioned embodiment.

[0111] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0112] The computer-readable storage medium may be included in the channel recommendation device; or may exist independently without being assembled into the channel recommendation device.

[0113] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the channel recommendation device, the channel recommendation device implements the solution of the above embodiment.

[0114] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0115] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0116] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0117] The readable storage medium provided by the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned channel recommendation method, and can solve the technical problem of low efficiency of manual channel switching by users. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as the beneficial effects of the channel recommendation method provided by the above-mentioned embodiment, and will not be described in detail here.

[0118] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned channel recommendation method when executed by a processor.

[0119] The computer program product provided by the present application can solve the technical problem of low efficiency of manual channel switching by users. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as those of the channel recommendation method provided by the above embodiment, which will not be described in detail here.

[0120] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A channel recommendation method, characterized in that: The channel recommendation method comprises: When receiving a display terminal start instruction, obtaining person information in the external environment where the display terminal is located; Determine a person to be recommended from the external environment based on the person information, and obtain a program recommendation list corresponding to the person to be recommended; The target broadcast program information is determined from the program recommendation list.

2. The channel recommendation method according to claim 1, characterized in that: The step of determining the person to be recommended from the external environment based on the character information includes: If the display terminal is in a state of being used by multiple persons, obtaining device location information of a control device of the display terminal, and determining a person to be recommended from various persons in the external environment based on the device location information; If the display terminal is in a single-person use state, the persons in the external environment are taken as persons to be recommended.

3. The channel recommendation method according to claim 2, characterized in that: The step of determining the person to be recommended from the persons in the external environment based on the device location information includes: Determine the personal position information of each person in the external environment based on the person information; Among the persons in the external environment, the persons whose position information matches the device position information are taken as persons to be recommended.

4. The channel recommendation method according to claim 1, characterized in that: The step of obtaining a program recommendation list corresponding to the person to be recommended includes: Detecting whether there is a custom program list corresponding to the person to be recommended; If the custom program list exists, use the custom program list as a program recommendation list; If the customized program list does not exist, then checking whether there is a historical viewing record of the person to be recommended; If the historical viewing record exists, determining a preferred program tag from each preset program tag based on the historical viewing record, and determining the program list under the preferred program tag as the program recommendation list, wherein the preferred program tag is the program tag with the longest cumulative viewing time among each of the preset program tags; If the historical viewing record does not exist, a user portrait is constructed based on the personal characteristics of the person to be recommended, and the program recommendation list is determined based on the user portrait.

5. The channel recommendation method according to claim 4, characterized in that: The program recommendation list is the custom program list; The step of determining target broadcast program information from the program recommendation list includes: If there is a currently broadcasting program in the program recommendation list, and the number of the currently broadcasting program is one, the currently broadcasting program is used as the target broadcasting program information; If the currently playing program exists and the number of the programs is at least two, then the program with the longest historical viewing time among the currently playing programs is determined as the target playing program information; If the currently playing program does not exist, the predicted broadcast time of each program in the program recommendation list is determined based on the preset program preview information, and the program with the closest predicted broadcast time among the programs in the program recommendation list is determined as the target playing program information.

6. The channel recommendation method according to claim 4, characterized in that: The program recommendation list is a list of programs under the preferred program label; The step of determining target broadcast program information from the program recommendation list includes: Determine the viewing duration and viewing frequency of each program in the program recommendation list; Traversing each program in the program recommendation list, weighting the viewing time of the currently traversed program by a first preset weight to obtain a first weight, weighting the number of times the currently traversed program is viewed by a second preset weight to obtain a second weight, and determining the sum of the first weight and the second weight as the viewing score of the currently traversed program; The program with the highest viewing score among the programs in the program recommendation list is determined as the target broadcast program information.

7. The channel recommendation method according to any one of claims 1 to 6, characterized in that: The step of determining target broadcast program information from the program recommendation list includes: Determining whether there is a key person in the external environment based on the character information; If the key person exists, determining the preset program level and preset program type corresponding to the key person based on the identity information of the key person; Among the programs in the program recommendation list, programs that meet the preset program level and the preset program type are determined as candidate broadcast program information, and target broadcast program information is determined from the candidate broadcast program information.

8. A channel recommendation device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the channel recommendation method according to any one of claims 1 to 7.

9. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the channel recommendation method according to any one of claims 1 to 7 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the channel recommendation method according to any one of claims 1 to 7 are implemented.

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