CN112667887B

CN112667887B - Content recommendation method and device, electronic equipment and server

Info

Publication number: CN112667887B
Application number: CN202011533640.0A
Authority: CN
Inventors: 王健
Original assignee: Beijing Dajia Internet Information Technology Co Ltd
Current assignee: Beijing Dajia Internet Information Technology Co Ltd
Priority date: 2020-12-22
Filing date: 2020-12-22
Publication date: 2024-03-12
Anticipated expiration: 2040-12-22
Also published as: CN112667887A

Abstract

The disclosure relates to a content recommendation method, a content recommendation device, electronic equipment and a server. In one method embodiment, analysis may be performed on data acquired by a client, where the data includes vital sign information acquired by the client via a wearable device. When the terminal account watches the video, the vital sign information can reflect the current emotion state of the terminal account more truly, so that the server can determine the emotion of the terminal account when watching the playing content according to the vital sign information, and can label the watched playing content and mark the played content as a corresponding emotion mark. Therefore, the server can search recommended content with the same or similar emotion according to the current emotion mark and return the recommended content to the client, and the client can play the content which better accords with the current emotion state of the terminal account, so that the accuracy of the recommended content is improved.

Description

Content recommendation method and device, electronic equipment and server

Technical Field

The disclosure relates to the technical field of computer data processing, and in particular relates to a content recommendation method, a content recommendation device, electronic equipment and a server.

Background

With the development of science and technology, the speed of the mobile internet is continuously increased, and the short video application of the terminal is gradually popularized. A user can search for and view content of interest through a short video application.

A service provider providing video content sharing may recommend content of possible interest to a user using some recommendation algorithm. For example, in some algorithms, videos may be recommended to a user based on the user's gender, age, region, network environment, etc. recommendation factors. With the increasing demands of users, how to recommend more accurate content to users has become a technical problem to be solved.

Disclosure of Invention

The disclosure provides a content recommendation method, a content recommendation device, electronic equipment and a server, so as to at least solve the problem that recommended content is not accurate enough. The technical scheme of the present disclosure is as follows:

acquiring acquisition information of a client, wherein the acquisition information comprises information of playing content of the client and vital sign information acquired by wearable equipment;

determining emotion identification of the client play content according to the vital sign information;

searching recommended content matched with the emotion mark;

and sending the searched recommended content to the client.

According to another aspect of the disclosed embodiments, in the method, the recommended content matching the emotion identification includes:

shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

According to another aspect of the embodiments of the present disclosure, after the searched recommended content is sent to the client, the method further includes:

acquiring recommendation feedback information of a client, wherein the recommendation feedback information at least comprises one of play duration information of the recommended content and terminal operation information when the recommended content is played;

when the recommendation result of the recommended content is determined to be successful according to the recommendation feedback information, pushing new recommended content, the emotion identification matching degree of which meets the preset requirement, to the client.

According to another aspect of the embodiments of the present disclosure, when determining that the recommendation result of the recommended content is successful according to the recommendation feedback information, the method further includes:

maintaining or improving the recommendation weight of the emotion mark of the recommended content to obtain the updated recommendation weight of the emotion mark;

Correspondingly, pushing the new recommended content, which has the emotion mark matching degree reaching the preset requirement, to the client comprises: and selecting the first M emotion identifications with the highest recommendation weight, pushing recommended contents matched with the M emotion identifications to the client, wherein M is a non-zero natural number.

acquiring recommendation feedback information of a client, wherein the recommendation feedback information comprises collected playing time length information of the recommended content and terminal operation information when the recommended content is played;

when the recommendation result of the recommended content is determined to be failure according to the recommendation feedback information, reducing the recommendation weight of the emotion mark of the recommended content to obtain the recommendation weight of the historical emotion mark;

determining a new emotion mark according to the acquired new acquired data;

and selecting the top N emotion identifications with the highest recommendation weight from the historical emotion identifications and the new emotion identifications, pushing recommended contents matched with the N emotion identifications to the client, wherein N is a non-zero natural number.

According to an aspect of the embodiments of the present disclosure, there is provided a content recommendation method including:

acquiring vital sign information acquired by wearable equipment;

transmitting the playing content information and the vital sign information to a server;

receiving recommended content sent by a server, wherein the recommended content comprises recommended content matched with emotion identifications of played video, and the emotion identifications are determined according to the vital sign information;

and playing the recommended content.

shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

According to another aspect of the embodiments of the present disclosure, after playing the recommended content, the method further includes:

collecting recommendation feedback information comprising the playing time information of the recommended content and terminal operation information when the recommended content is played;

and sending the recommendation feedback information to the server, wherein the recommendation feedback information is used for pushing new recommendation content, the emotion identification matching degree of which meets the preset requirement, to the client when the recommendation result of the recommendation content is determined to be successful according to the recommendation feedback information.

According to another aspect of the disclosed embodiments, in the method, after the recommendation feedback information is sent to the server, new recommendation content sent by the server is also received, where the new recommendation content is determined by:

when the server determines that the recommendation result of the recommended content is successful according to the recommendation feedback information, maintaining or improving the recommendation weight of the emotion mark of the recommended content to obtain the recommendation weight after the emotion mark is updated;

selecting the first M emotion identifications with the highest recommendation weight, taking the recommendation content matched with the M emotion identifications as new recommendation content, wherein M is a non-zero natural number.

the recommendation feedback information is sent to the server and is used for reducing the recommendation weight of the emotion mark of the recommended content to obtain the recommendation weight of the historical emotion mark when the recommendation result of the recommended content is determined to be failed according to the recommendation feedback information;

Receiving new recommended content sent by a server, wherein the new recommended content is determined by adopting the following method:

the server selects top N emotion identifications with highest recommendation weights from the new emotion identifications and the historical emotion identifications, recommended contents matched with the N emotion identifications are used as new recommended contents, N is a natural number, and the new emotion identifications are determined according to new acquired data uploaded by the client.

According to another aspect of the embodiments of the present disclosure, there is also provided a content recommendation apparatus including:

the first receiving module is used for acquiring acquisition information of the client, wherein the acquisition information comprises information of content played by the client and vital sign information acquired by the wearable equipment;

the emotion determining module is used for determining emotion identification of the content played by the client according to the vital sign information;

the content searching module is used for searching recommended content matched with the emotion mark;

and the sending module is used for sending the searched recommended content to the client.

According to another aspect of the disclosed embodiments, in the apparatus, the recommended content matching the emotion identifier may include:

shared content matching the emotional identifier,

Or,

and the associated content of the target account matched with the emotion mark.

According to another aspect of the disclosed embodiments, in the apparatus, the apparatus further includes:

the second receiving module is used for acquiring recommendation feedback information of the client after the searched recommendation content is sent to the client, wherein the recommendation feedback information at least comprises one of play duration information of the recommendation content and terminal operation information when the recommendation content is played;

and the first pushing module is used for pushing new recommended content, the emotion identification matching degree of which meets the preset requirement, to the client when the recommendation result of the recommended content is determined to be successful according to the recommendation feedback information.

the first weight adjustment module is used for maintaining or improving the recommendation weight of the emotion mark of the recommended content when the recommendation result of the recommended content is determined to be successful according to the recommendation feedback information, so as to obtain the updated recommendation weight of the emotion mark;

correspondingly, the pushing, by the first pushing module, the new recommended content, the emotion identification matching degree of which reaches the preset requirement, to the client includes: and selecting the first M emotion identifications with the highest recommendation weight, pushing recommended contents matched with the M emotion identifications to the client, wherein M is a non-zero natural number.

the second receiving module is used for acquiring acquisition information of the client, wherein the acquisition information comprises information of content played by the client and vital sign information acquired by the wearable equipment;

the second weight adjustment module is used for reducing the recommendation weight of the emotion mark of the recommended content to obtain the recommendation weight of the historical emotion mark when the recommendation result of the recommended content is determined to be failed according to the recommendation feedback information;

the new emotion determining module is used for determining a new emotion mark according to the acquired new acquired data;

and the second pushing module is used for selecting the first N emotion identifications with the highest recommendation weight from the historical emotion identifications and the new emotion identifications, pushing recommended contents matched with the N emotion identifications to the client, wherein N is a non-zero natural number.

According to another aspect of the embodiments of the present disclosure, there is also provided a content recommendation apparatus, the apparatus including:

the vital sign acquisition module is used for acquiring vital sign information acquired by the wearable equipment;

the information uploading module is used for sending the playing content information and the vital sign information to a server;

The recommended content receiving module is used for receiving recommended content sent by a server, wherein the recommended content comprises recommended content matched with emotion identifications of the played video, and the emotion identifications are determined according to the vital sign information;

and the playing module is used for playing the recommended content.

shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

the feedback acquisition module is used for acquiring recommendation feedback information comprising playing time length information of the recommended content and terminal operation information when the recommended content is played;

the first feedback module is used for sending the recommendation feedback information to the server, and the recommendation feedback information is used for pushing new recommendation content, the emotion identification matching degree of which meets the preset requirement, to the client when the recommendation result of the recommendation content is determined to be successful according to the recommendation feedback information.

the first new receiving module is used for receiving new recommended content sent by the server after sending the recommended feedback information to the server, and the new recommended content is determined by adopting the following modes:

the second feedback module is used for sending the recommendation feedback information to the server, wherein the recommendation feedback information is used for reducing the recommendation weight of the emotion mark of the recommendation content to obtain the recommendation weight of the historical emotion mark when the recommendation result of the recommendation content is determined to be failure according to the recommendation feedback information;

The second new receiving module is used for receiving new recommended content sent by the server, and the new recommended content is determined by adopting the following mode:

According to another aspect of the embodiments of the present disclosure, there is also provided an electronic device including:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the method of any of the embodiments implemented in the client in the present disclosure.

According to another aspect of embodiments of the present disclosure, there is also provided a storage medium, which when executed by a processor of an electronic device, causes the electronic device to perform the method of any one of the embodiments of the present disclosure implemented in a client.

According to another aspect of the embodiments of the present disclosure, there is also provided a server including:

at least one processor;

A memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the method of any of the embodiments implemented in a server in the present disclosure.

According to another aspect of the embodiments of the present disclosure, there is also provided a storage medium, characterized in that, when the instructions in the storage medium are executed by a processor of a server, the server is enabled to perform the method implemented in any one of the servers in the present disclosure.

The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:

the server can analyze and process the data acquired by the client, wherein the data comprises vital sign information acquired by the client through the wearable device. When the terminal account watches the video, the vital sign information can reflect the current emotion state of the terminal account more truly, so that the server can determine the emotion of the terminal account when watching the playing content according to the vital sign information, and can label the watched playing content and mark the played content as a corresponding emotion mark. Therefore, the server can search recommended content with the same or similar emotion according to the current emotion mark and return the recommended content to the client, and the client can play the content which better accords with the current emotion state of the terminal account, so that the accuracy of the recommended content is improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure and do not constitute an undue limitation on the disclosure.

Fig. 1 is an application environment diagram illustrating a content recommendation method according to an exemplary embodiment.

Fig. 2 is an application environment diagram illustrating a content recommendation method according to an exemplary embodiment.

Fig. 3 is a flowchart illustrating a content recommendation method according to an exemplary embodiment.

Fig. 4 is a flowchart illustrating a content recommendation method according to an exemplary embodiment.

Fig. 5 is a flowchart illustrating a content recommendation method according to an exemplary embodiment.

Fig. 6 is a flowchart illustrating a content recommendation method according to an exemplary embodiment.

Fig. 7 is a flowchart illustrating a content recommendation method according to an exemplary embodiment.

Fig. 8 is a flowchart illustrating a content recommendation method according to an exemplary embodiment.

Fig. 9 is a flowchart illustrating a content recommendation method according to an exemplary embodiment.

Fig. 10 is a block diagram illustrating a content recommendation device according to an exemplary embodiment.

Fig. 11 is a block diagram illustrating a content recommendation device according to an exemplary embodiment.

Fig. 12 is a block diagram illustrating a content recommendation device according to an exemplary embodiment.

Fig. 13 is a block diagram illustrating a content recommendation device according to an exemplary embodiment.

Fig. 14 is a block diagram illustrating a content recommendation device according to an exemplary embodiment.

Fig. 15 is a block diagram illustrating a content recommendation device according to an exemplary embodiment.

Fig. 16 is a block diagram illustrating a content recommendation device according to an exemplary embodiment.

Fig. 17 is a block diagram illustrating a content recommendation device according to an exemplary embodiment.

Fig. 18 is a block diagram illustrating a content recommendation device according to an exemplary embodiment.

Fig. 19 is an internal structural diagram of an electronic device, which is shown according to an exemplary embodiment.

Fig. 20 is an internal structural diagram of a server shown according to an exemplary embodiment.

Detailed Description

In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the disclosure described herein may be capable of operation in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, it is not excluded that additional identical or equivalent elements may be present in a process, method, article, or apparatus that comprises a described element. For example, the terms first, second, etc. may be used to indicate a name and not any particular order.

The content recommendation method provided by the disclosure can be applied to an application environment as shown in fig. 1. Wherein the terminal 110 may interact with the server 120 through a network connection. The server 120 may transmit video data to the terminal 110, and the terminal 110 may locally generate video and play the video after receiving the video data. The video may be played when a video playing Application (APP) is opened at the terminal 110 side, or may be played when a video playing window is activated by switching to the video playing application from another application. The terminal account may be worn with a wearable device 130, such as the smart watch shown in fig. 1, and the wearable device 130 may collect vital sign information of the user, such as heart rate, body temperature, etc. These vital sign information may be transmitted to the terminal 110. For example, the wearable device 130 may send the collected vital sign information to the terminal 110 in real time or periodically through the terminal account after the bluetooth is paired with the terminal 110. The terminal 110 may report the currently played video content to the server 120 together with the collected vital sign information when playing the video. The server 120 may determine, according to the analysis of vital sign information, the emotion of the terminal account when watching the video content, and may sign the video with a corresponding emotion identifier. Server 120 may look up the video or target account for the same emotion and return it to the client. The client side may play the recommended content according to the video or the target account with the same emotion recognition.

The wearable devices described in embodiments of the present disclosure may generally include a portable device that is worn directly on a person or integrated into a person's clothing or accessories. For example, the human body can directly wear intelligent watches, intelligent shoes and the like on four limbs mulberry leaves, can wear intelligent glasses, intelligent helmets and the like on the head, and can indirectly contact with the human body or be used for auxiliary or decorative equipment of human body functions, such as the intelligent coat, the intelligent schoolbag, the intelligent crutch, the intelligent accessory and the like. In general, the wearable device may be provided with one or more sensors, such as an environmental sensor, an optical heart rate sensor, a temperature sensor, etc. The wearable device may have certain data processing and communication capabilities, such as receiving signals from a sensor device, converting analog signals to digital signals or counting data, etc., transmitting collected data to another device, etc. The terminal 110 described in the embodiments of the present disclosure may include, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, vehicle-mounted devices, medical devices, and the like. The servers 120 described in the embodiments of the present disclosure may include, but are not limited to, stand-alone servers, server clusters, distributed processing servers, blockchain servers, cloud computing platforms, and the like, as well as combinations thereof. The server 120 may be understood as one or more servers on the client 110 side, for example, a server that analyzes vital sign information to determine emotion marks, a server that matches recommended content according to emotion marks, and the like. It should be noted that the wearable device and the client may be different devices without mechanical connection, as shown in fig. 1. In another application scenario, the wearable device may be integrated in one device of the client, or the client itself may be integrated with a sensor device for collecting vital sign information, or the wearable device may be provided with a recommended content of a playing server (for example, the wearable device may obtain vital sign information, play video, and may communicate with the server), as shown in fig. 2, the heart rate sensor 140 may be integrated in the client 110, and at this time, the collected information uploaded to the server may still be considered as vital sign information collected by the client through the wearable device.

For ease of description, in some embodiments of the present disclosure, the objects that view the play content and perform the manipulation actions at the terminal 110 may be referred to as a terminal account, such as terminal account c_user1 that is viewing the video play application app_1. The server 120 finds an account matching the emotion of the terminal account (the same or similar emotion) as the target account, for example, the target account s_user1 of video published or uploaded on the content sharing platform, and the server finds the target account s_user2 belonging to the emotion identification "Happy" with the terminal account c_user1. Embodiments of the present disclosure are described below in terms of an exemplary implementation scenario for transmitting recommended content to a terminal account based on vital sign information of the terminal account collected by a client. Of course, the following description of the embodiments does not limit other scalable solutions obtained based on the embodiments of the present specification. Such as content played by the client and recommended content sent to the client, may be video, audio or pictures or text or a combination thereof.

Fig. 3 is a flowchart illustrating a content recommendation method, which may be used in the server 120, as shown in fig. 3, according to an exemplary embodiment, and may include the following steps.

In step S302, the collected information of the client may be obtained, where the collected information includes information of the content played by the client and vital sign information collected by the wearable device.

The vital sign information may include characteristic parameters that directly reflect the living body of the terminal account, such as heart rate, temperature, blood pressure, etc., and may also include collected characteristic parameters related to the environment in which the living body of the terminal account is located, such as altitude related to location, GPS location (Global Positioning System, GPS, global positioning system), brightness information related to light, acceleration related to movement state, etc. The client can establish connection with the wearable device to realize data transmission. In this way, the wearable device can send the collected vital sign information of the terminal account to the client. For example, the wearable device may establish a connection with the client through near field communication, such as bluetooth, infrared, and the like. The wearable device may send the data packet to the client via near field communication. The data structure of the data packet may be set as a combination of the message type and the message body. The message type may be set to different types of vital signs, such as heart rate, body temperature, altitude, etc., and the message body may be specific data.

The wearable device can acquire vital sign information periodically or in real time, and can send the vital sign information to the client periodically or in real time. Or, the client may also actively acquire vital sign information of the wearable device or issue an instruction to require the wearable device to send the vital sign information to the client based on a requirement of reporting the acquired information to the server, before reporting the acquired information. Or the client side can also receive vital sign information sent by the wearable device while reporting the acquired information or other information to the server.

The information of the client playing content may include a category label of the video that the client is playing or has recently played. Generally, the video sharing platform may sort the video content in advance and label the video content with corresponding tags, such as a drama episode, a national animation, a chinese song, a monitoring snapshot, and the like. In some implementations, the classification of the video may include a multi-level classification, may include a parent level classification, a child level classification, etc., or a primary level classification, a secondary level classification, etc. For example, the classification label of a certain video can be "fun" or "error collection" of sub-class classification under "fun". Thus, the client can acquire information including the category label of the play video. The client can send the classification labels of the played videos and the vital sign information to the server during or after the video is played. Of course, the collected information may also include other information content, such as a timestamp, an account identifier, information about the publisher of the video played by the client, and the disclosure is not limited thereto.

In step S304, the emotion identifier of the content played by the client is determined according to the vital sign information.

The emotion identification may include an identifier for indicating the type or extent of emotion in which the terminal account is being located. If the emotion mark 'Happy' can be used for representing the Happy emotion, the 'sad' can be used for representing the emotion of the wounded heart, the expression intensity of the expressed emotion can be enabled, the 'happy_1' can represent that the Happy degree is more intense, the 'happy_2' can represent that the Happy degree is normal, the 'happy_3' can represent that the terminal account is slightly Happy, and the Happy degree is lower. After the vital sign information is obtained, an algorithm or a model can be adopted to analyze and process the vital sign information, and the emotion identification corresponding to the vital sign information is output. The vital sign information can be acquired when the client is playing the video or recently, and can reflect the emotion characteristics of the terminal account when the video is watched, so that the terminal account, the vital sign information, the playing content and the emotion identification can have corresponding relations. For example, the vital sign information collected when the terminal account c_use1 plays the video vid_1 is date_1, and the emotion mark determined by the server based on the vital sign information date_1 is "happy_1". Accordingly, the emotion flag "happy_1" may be used as an emotion flag to be determined based on the vital sign information date_1, or as an emotion flag of the play video vid_1 corresponding to the vital sign information date_1, or as an emotion flag of the terminal account c_use1 when viewing the play video vid_1. The emotion identification may be associated with information such as the corresponding terminal account, vital sign information, content being played, etc., for example, an emotion tag as a tag for playing video.

In this embodiment, the emotion identifier may be generated by performing data processing on vital sign information by using one or more algorithms, or may be determined by combining one or more machine learning models. The machine learning model may employ supervised machine learning models such as logistic regression (Logistic Regression, LR) and support vector machines (Support Vector Machine, SVM). Or constructing an emotion recognition model based on a convolutional neural network (Convolutional Neural Networks, CNN) and the like in advance, and training the emotion recognition model by using vital sign samples. After the server acquires the vital sign information, an emotion recognition model can be input, and the emotion recognition model can output corresponding emotion classification (emotion identification).

In step S306, recommended content matching the emotion recognition is found.

The matching may include that the searched emotion identification of the recommended content and the emotion identification of the content played by the client meet preset matching requirements. For example, the emotion mark "happy_1" of a certain video vid_1 searched by the server side is the same as the emotion mark "happy_1" of the content played by the client, and it can be determined that the emotion mark of the video vid_1 is matched with the emotion mark, and then the video vid_1 can be used as recommended content matched with the emotion mark "happy_1".

In other embodiments, the matching may also include that the similarity or association degree of the emotion marks reaches a preset matching requirement. For example, the emotion mark of a certain video vid_1 is "happy_1", the emotion mark of the content played by the determined client is "Happy", the processing unit determines that the similarity degree of the "happy_1" and the "Happy" meets the matching requirement through recognition, and the processing unit belongs to the Happy emotion category, or determines that the "happy_1" belongs to the sub-category of the "Happy" parent category, the relevance degree meets the matching requirement, and it can be determined that the emotion mark "happy_1" of the video vid_1 is matched with the emotion mark "Happy", and then the video vid_1 can be used as recommended content matched with the emotion mark "Happy".

The server can search for the content matched with the emotion mark in a storage unit for sharing the content such as the video and the like locally or specially storing the emotion mark in the server. The searched content matched with the emotion mark can be completely or partially used as recommended content pushed to the terminal account. As mentioned above, the recommended content searched may be content of the same media type as the content played by the client, such as video content, or other types of recommended content, such as audio or image matching with emotion marks.

And transmitting the searched recommended content to the client in step S308.

The server may send all or part of the found content matching the emotion identification to the client as recommended content pushed to the terminal account. When a plurality of matched contents are found, a pre-designed algorithm can be adopted to further screen out recommended contents which are finally sent to the client. For example, when the server finds a plurality of videos of the category of funneling according to the emotion identification "happy", a video with the highest matching degree can be further screened out according to the attributes of the age, the sex and the like of the terminal account and used as recommended content to be sent to the client.

According to the content recommendation method, analysis processing can be performed on data acquired by the client, wherein the data comprise vital sign information acquired by the client through the wearable device. When the terminal account watches the video, the vital sign information can reflect the current emotion state of the terminal account more truly, so that the server can determine the emotion of the terminal account when watching the playing content according to the vital sign information, and can label the watched playing content and mark the played content as a corresponding emotion mark. Therefore, the server can search recommended content with the same or similar emotion according to the current emotion mark and return the recommended content to the client, and the client can play the content which better accords with the current emotion state of the terminal account, so that the accuracy of the recommended content is improved.

In another exemplary embodiment of the disclosure, the emotion identification may be used not only as an identification of video equally shared content, but also as an emotion identification of a target account. For example, the emotion of the terminal account c_use1 watching short video in the video playing application app_1 is identified as "Happy", and the server 120 may search for the target account s_use1 whose emotion is identified as "Happy" in a certain period (for example, in the last 3 minutes at the current time). The associated information of the target account s_use1 may then be used as recommended content. The associated content of the target account can comprise information related to the target account, such as an account number, a live broadcast number, video introduction of the target account, and the like, and also can comprise play content under the target account, such as video under the target account S_user1. Thus, in another exemplary embodiment of the present disclosure, the recommended content matching the emotion recognition may include:

shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

The shared content generally refers to specific media information, such as video data, audio data, pictures, etc., which can be played at the client. For example, shared content involved in short video applications may include video data. After the emotion of the terminal account is identified, not only can the sharing content with matched emotion be pushed to the client, but also the target account with matched emotion can be found, and then the related information of the target account or the sharing content of the target account is pushed to the terminal account, so that the terminal account can quickly acquire the related content of the target account with the same emotion, the accuracy of the recommended content is further improved, the recommended content and the recommended mode are diversified, and the interactive experience of the terminal account is enriched and improved.

Fig. 4 is a flowchart illustrating a content recommendation method according to an exemplary embodiment, and as shown in fig. 4, in another exemplary embodiment of the present disclosure, after the searched recommended content is transmitted to the client, the method may further include:

s402: acquiring recommendation feedback information of a client, wherein the recommendation feedback information at least comprises one of play duration information of the recommended content and terminal operation information when the recommended content is played;

s404: when the recommendation result of the recommended content is determined to be successful according to the recommendation feedback information, pushing new recommended content, the emotion identification matching degree of which meets the preset requirement, to the client.

The recommendation feedback information may include information of the playing condition of the recommended content acquired by the client in the client, or may include operation behavior (which may be referred to as terminal operation information here) performed on the client when the terminal account views the recommended content. For example, the client may collect the playing time information of the recommended content, and may also collect the terminal operation information such as praise, collection, sharing, etc. of the terminal account when the recommended content is played. The playing time length information can be an absolute value of the playing time length, or a relative value of the playing time length compared with the complete playing time length of the recommended content. For example, when the recommended content is a short video of 10 seconds, if the client detects that the short video is only played for 5 seconds, the playing duration information may be 5 seconds. Alternatively, the client may determine that the playing duration information is 50% based on that the short video is played for 10 seconds and is actually played for 5 seconds. In another example, if the short video is completely played for 10 seconds and is actually played for 10 seconds, the playing time information may be determined to be 100%, or it may be determined that the short video is completely played.

The server may analyze the recommendation feedback information including the above, and determine whether the recommendation result of the recommendation content sent to the client is successful. The decision basis for whether the recommendation was successful may include one or more information. For example, in one implementation manner, if the recommendation is completely played by the client in the recommendation, the recommendation result of the recommended content may be determined to be successful, or if the recommendation feedback information includes that the terminal account collected by the client performs a praise operation on the recommended content, the recommendation result of the recommended content may be determined to be successful. Of course, the two types of recommendation feedback information may be combined together, for example, when the playing duration information is not less than 10 seconds and at least one of terminal operation information including praise, analysis, comment and repeated playing is included, the recommendation result of the recommended content is determined to be successful.

The recommendation results of the recommended content may be identified using field information or an identifier. For example, the field "Result" may be used to indicate that the recommendation was successful, and "Result" value "false" indicates that the recommendation was failed. The server can determine the value of Result according to the recommendation feedback information, and then determine whether the recommendation Result is successful or recognized. Of course, the present disclosure does not exclude that other ways of indicating whether the recommendation was successful or identified may be employed, such as determining that the recommendation was successful directly based on whether the recommendation was played in its entirety and performed a praise action.

If the server determines that the recommendation result of the recommended content is successful according to the recommendation feedback information, the recommended content can be indicated to meet the current emotion requirement of the terminal account, and in some embodiments of the present disclosure, the recommended content with the same or similar emotion identification as the recommended content can be further pushed to the client. And specifically acquiring new recommended content with the emotion mark matching degree reaching the preset requirement. The recommended content may be searched again according to the emotion identification or the matched recommended content which has been searched as the new recommended content. The implementation manner in which the matching degree reaches the preset requirement may refer to the implementation manner of "matching" in the step S306. Of course, the matching setting requirements set in the process of determining the new recommended content may be set to be the same as or different from the matching requirements of determining the recommended content described above.

FIG. 5 is a flowchart illustrating a content recommendation method according to an exemplary embodiment, and as shown in FIG. 5, when determining that a recommendation result of the recommended content is successful according to the recommendation feedback information, another exemplary embodiment of the present disclosure further includes:

S502: maintaining or improving the recommendation weight of the emotion mark of the recommended content to obtain the updated recommendation weight of the emotion mark;

The unused emotion identifications may be identified by corresponding recommendation weights. The recommendation weight may represent an emotion identifier corresponding to the recommended content as a weight of the recommended content. In general, the higher the recommendation weight (the larger the numerical value) of a certain emotion mark, the content corresponding to the emotion mark can be pushed preferentially. The recommendation weight of emotion identifications may be varied or adjusted. For example, if it is determined according to the vital sign information that the emotion of the terminal account is identified as "happy_3" when the video vid_1 is watched, the emotion of the terminal account is regarded as Happy. And then sending a video Vid_2 of 'happy_3' to the client, wherein the video Vid_2 is the matched recommended content searched according to the emotion mark. According to the recommendation feedback information of the recommended content Vid_2 fed back by the client, the terminal account finishes watching the video Vid_2 and performs praying, and the terminal account likes the recommended content Vid_2, which indicates that the recommended content meets the content watching requirement of the current emotional state of the terminal account. At this time, the recommendation weight of the emotion mark "happy_3" may be raised to 0.85 from the last recommendation weight of 0.8. If the recommended content is successful, the recommendation weight of the emotion mark can be updated, and the updated recommendation weight is obtained. Of course, the recommendation weight may also be kept unchanged, and in the embodiment of the disclosure, the recommendation weight that is kept unchanged still belongs to one of the updated recommendation weight embodiments.

Because the embodiment of the disclosure adds the recommendation weight to the emotion mark, when the server recommends new content to the client (new recommended content), the server can preferentially take the recommended content corresponding to the emotion mark with high recommendation weight as the new recommended content and send the new recommended content to the client. For example, the emotion mark with the highest recommendation weight (i.e., m=1) may be selected as the emotion state that is most matched with the terminal account currently, and then the recommended content that is matched with the emotion mark with the highest recommendation weight is pushed to the client. The recommendation value of the top M emotion identifications can be selected, and the recommendation value can comprise a recommendation weight updated from the emotion identifications or a recommendation weight of a new generated or previous emotion identification. The matching may be implemented by referring to the matching related description in the related embodiments, which is not described herein.

When the recommended content or the new recommended content is selected, if the determined emotion marks exist, the recommended content with one or more emotion marks is selected and pushed to the user. Minimum requirements for recommendation weights may also be set in some embodiments. For example, if the recommendation weight is lower than 0.3, it may indicate that the recommended content may not conform to the current emotional state of the terminal account, and may be set to a normal recommendation policy according to age, gender, etc.

Therefore, it can be seen that, according to the embodiment, whether the terminal account likes the recommended content or not can be identified according to the recommended content playing time length information and the terminal operation information of the terminal account, if so, the weight of the emotion mark corresponding to the recommended content can be improved, the content of the emotion category can be continuously pushed, the emotion state of the recommended content is watched by the terminal account, the accuracy of the recommended content is improved, and the experience of the terminal account watching the shared content is also improved.

FIG. 6 is a flowchart illustrating a content recommendation method according to an exemplary embodiment, and in another exemplary embodiment of the present disclosure, after the searched recommended content is transmitted to the client, as shown in FIG. 6, the method may further include:

s602: acquiring recommendation feedback information of a client, wherein the recommendation feedback information at least comprises one of play duration information of the recommended content and terminal operation information when the recommended content is played;

s604: when the recommendation result of the recommended content is determined to be failure according to the recommendation feedback information, reducing the recommendation weight of the emotion mark of the recommended content to obtain the recommendation weight of the historical emotion mark;

S606: determining a new emotion mark according to the acquired new acquired data;

s608: and selecting the top N emotion identifications with the highest recommendation weight from the historical emotion identifications and the new emotion identifications, pushing recommended contents matched with the N emotion identifications to the client, wherein N is a natural number.

The embodiment of step S602 may refer to the aforementioned step S402, and will not be described herein.

In step 604, if it is determined that the recommendation result of the recommended content is failure according to the recommendation feedback information, the recommendation weight of the emotion mark of the recommended content may be reduced accordingly. For example, in the foregoing example, if it is determined that the emotion of the terminal account is identified as "happy_3" when the video vid_1 is watched according to the vital sign information, the emotion of the terminal account is regarded as Happy. And then sending a video Vid_3 of 'happy_3' to the client, wherein the video Vid_3 is the matched recommended content searched according to the emotion mark. According to the recommendation feedback information of the recommended content vid_3 fed back by the client, the terminal account does not see the video vid_3, and the video is quickly slipped away, so that the terminal account does not like the recommended content vid_3, and the recommended content accords with the content watching requirement which does not accord with the current emotional state of the terminal account. At this time, the emotion flag "happy_3" recommendation weight may be reduced from 0.85, which is the last recommendation weight, to 0.75. For ease of description and distinction, emotion identifications after adjustment (including lowering, raising, maintaining) of recommendation weights may be referred to herein as historical emotion identifications.

In step S606, new collected data of the client may be acquired, and the emotion identification (which may be referred to herein as a new emotion identification) of the terminal account is redetermined according to vital sign information in the new collected data, or in combination with play duration information of the recommended content, terminal operation information, and the like.

If multiple emotion identifications exist after the new emotion identifications are redetermined in the successful processing mode as the recommendation result of the recommended content, the method can comprise an emotion identification F1 determined according to previous acquired data (the acquired new acquired data is used as the acquired data in the implementation process of the scheme), a historical emotion identification F2 after the emotion identification is lifted or lowered, and a new emotion identification F3 determined by the acquired new acquired data. Then the recommended content matching the top N emotion identifications with the highest recommendation weight may be selected and pushed to the client. For example, in one implementation example of n=1, the recommendation weight of the historical emotion mark is 0.92 and 0.80, respectively, and the recommendation weight of the new emotion mark is 0.85, and at this time, although it is determined that the recommendation weight of the current latest emotion mark of the terminal account is 0.85 according to the latest acquired data, the current latest emotion mark of the terminal account is still insufficient to be the optimal emotion mark of the recommended content, for example, the terminal account may be only a temporary emotion change, or a slowly-descending stage of the emotion change is processed, but the current emotion mark of the recommended content is not suitable for being changed immediately (the emotion change usually does not change a time content greatly for a plurality of times). Therefore, the recommended content of the emotion mark represented by 0.92 with the highest recommendation weight can still be selected and sent to the client. Of course, if the recommendation weight of the new emotion mark is 0.95 according to the emotion mark algorithm or model, the recommendation content matched with the new emotion mark can be pushed to the client.

As previously mentioned, minimum requirements for recommended weights may also be set in some embodiments. For example, if the recommendation weight is lower than 0.3, it may indicate that the recommended content may not conform to the current emotional state of the terminal account, the value of N may be set to 0, that is, the recommended content may not be recommended according to the emotional tag any more, and the recommended content may be selected according to the normal recommendation policy of age, gender, etc.

Therefore, the embodiment can identify whether the terminal account likes the recommended content according to the recommended content playing time information and the terminal operation information of the terminal account. If not, the weight of the emotion marks corresponding to the recommended content can be reduced, new emotion tags can be redetermined according to vital sign information acquired by the wearable equipment, and then the top N emotion marks with the highest recommended weight are screened out. Therefore, the emotion identification and the corresponding recommendation weight can be continuously updated according to the continuously collected vital sign information, and the emotion state change of the terminal user is tracked, so that the recommended content is more in line with the emotion state of the recommended content watched by the terminal account, the accuracy of the recommended content is improved, and the experience of the terminal account watching the shared content is also improved.

The present disclosure also provides a content recommendation method that may be used on the client side 110, as described with reference to embodiments of the method that may be used on the server side S120. A specific exemplary embodiment is shown in fig. 7, the method may include:

s702: acquiring vital sign information acquired by wearable equipment;

s704: transmitting the playing content information and the vital sign information to a server;

s706: receiving recommended content sent by a server, wherein the recommended content comprises recommended content matched with emotion identifications of played video, and the emotion identifications are determined according to the vital sign information;

s708: and playing the recommended content.

In another exemplary embodiment of the content recommendation method of the present disclosure, the recommended content matched with the emotion identification may include:

shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

FIG. 8 is a flowchart illustrating a content recommendation method according to an exemplary embodiment, as shown in FIG. 8, in another exemplary embodiment of the present disclosure, after playing the recommended content, further comprising:

S802: collecting recommendation feedback information comprising the playing time information of the recommended content and terminal operation information when the recommended content is played;

s804: and sending the recommendation feedback information to the server, wherein the recommendation feedback information can be used for pushing new recommendation content with the emotion identification matching degree reaching the preset requirement to the client when the recommendation result of the recommendation content is determined to be successful according to the recommendation feedback information.

FIG. 9 is a flowchart illustrating a content recommendation method according to an exemplary embodiment, as shown in FIG. 9, in another exemplary embodiment of the present disclosure, after sending the recommendation feedback information to the server, the method may further include:

s902: and receiving the new recommended content sent by the server. The new recommended content is determined by the following method:

FIG. 10 is a flowchart illustrating a content recommendation method according to an exemplary embodiment, as shown in FIG. 10, in another exemplary embodiment of the present disclosure, after playing the recommended content, further comprising:

s1002: collecting recommendation feedback information comprising the playing time information of the recommended content and terminal operation information when the recommended content is played;

s1004: the recommendation feedback information is sent to the server and is used for reducing the recommendation weight of the emotion mark of the recommended content to obtain the recommendation weight of the historical emotion mark when the recommendation result of the recommended content is determined to be failed according to the recommendation feedback information;

s1006: receiving new recommended content sent by a server, wherein the new recommended content is determined by adopting the following method:

The dashed lines in fig. 9, 10 may represent steps that may be repeatedly performed. If the client plays the recommended content, one or more of recommended feedback information, vital sign information, play content information and the like are sent to the server. And the server continues to acquire new recommended content according to the information and then sends the new recommended content to the client. And when the client plays the new recommended content, continuously acquiring vital sign information, sending new recommended feedback information and new acquired information to the server, analyzing the information by the server, determining the new recommended content, and then sending the new recommended content to the client for processing.

The above method embodiments may be used on the client side, and the specific implementation of the relevant steps may refer to the description of the foregoing server side relevant embodiments. According to the embodiment of the method which can be implemented at one side of the client, the client can acquire the vital sign information of the wearable device, predict the emotion of the terminal account according to the vital sign information, display recommended content with the same emotion or similar emotion as the terminal account at the client, improve the accuracy of content recommendation of the client, improve the consumption duration of the terminal account for terminal content sharing application (such as short video application), and improve the viscosity of the terminal account and use/interaction experience.

It should be understood that, in this specification, each embodiment of the client-side or server-side method is described in a progressive manner, and the same/similar parts of each embodiment are referred to each other, where each embodiment focuses on differences from other embodiments. For relevance, reference should be made to the description of other method embodiments.

It should be understood that, although the steps in the flowcharts in fig. 2 to 10 are sequentially shown as indicated by arrows, the steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least a portion of the steps of fig. 2 to 10 may include a plurality of steps or stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages may not necessarily be sequentially performed, but may be performed alternately or alternately with at least a portion of the steps or stages of other steps or other steps.

Based on the description of the embodiments of the content recommendation method, the disclosure further provides a content recommendation device. The apparatus may include a system (including a distributed system), software (applications), modules, components, servers, logic function circuits, clients, etc. that employ the methods described in embodiments of the present disclosure in conjunction with the necessary apparatus to implement the hardware. Based on the same innovative concepts, embodiments of the present disclosure provide for devices in one or more embodiments as described in the following examples. Because the implementation scheme and the method for solving the problem by the device are similar, the implementation of the device in the embodiment of the present disclosure may refer to the implementation of the foregoing method, and the repetition is not repeated. As used in this disclosure, the term "unit" or "module" may be a combination of software and/or hardware that implements the intended function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

Fig. 11 is a block diagram of a content recommendation device, according to an example embodiment. The device may be a server, such as the server 120 described previously. Referring specifically to fig. 11, the apparatus 200 may include:

The first receiving module 1102 may be configured to obtain collected information of a client, where the collected information includes information of content played by the client and vital sign information collected by a wearable device;

the emotion determining module 1104 may be configured to determine, according to the vital sign information, an emotion identifier of the client play content;

a content search module 1106, configured to search for recommended content that matches the emotion identifier;

the sending module 1108 may be configured to send the found recommended content to the client.

In an exemplary embodiment, the recommended content matched with the emotion identification may include:

shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

An exemplary embodiment is shown in fig. 12, and fig. 12 is a block diagram of another content recommendation device, which is shown in accordance with an exemplary embodiment. Referring to fig. 12, the apparatus 200 may further include:

the second receiving module 1202 may be configured to obtain, after sending the found recommended content to the client, recommendation feedback information of the client, where the recommendation feedback information includes at least one of play duration information of the recommended content and terminal operation information when the recommended content is played;

The first pushing module 1204 may be configured to push, to the client, a new recommended content with a degree of matching with the emotion identifier of the recommended content reaching a preset requirement when it is determined that the recommended result of the recommended content is successful according to the recommended feedback information.

An exemplary embodiment is shown in fig. 13, and fig. 13 is a block diagram of a content recommendation device according to an exemplary embodiment. Referring to fig. 13, the apparatus 200 may further include:

the first weight adjustment module 1302 may be configured to maintain or raise a recommendation weight of the emotion mark of the recommended content when the recommendation result of the recommended content is determined to be successful according to the recommendation feedback information, so as to obtain a recommendation weight after the emotion mark is updated;

correspondingly, the pushing, by the first pushing module 1204, the new recommended content that matches with the emotion identifier of the recommended content to reach the preset requirement to the client includes: and selecting the first M emotion identifications with the highest recommendation weight, pushing recommended contents matched with the M emotion identifications to the client, wherein M is a non-zero natural number.

An exemplary embodiment is shown in fig. 14, and fig. 14 is a block diagram of a content recommendation device according to an exemplary embodiment. Referring to fig. 14, the apparatus 200 may further include:

The second receiving module 1202 may be configured to obtain collected information of the client, where the collected information includes information of content played by the client and vital sign information collected by the wearable device;

the second weight adjustment module 1404 may be configured to reduce a recommendation weight of the emotion identifier of the recommended content to obtain a recommendation weight of a historical emotion identifier when determining that the recommendation result of the recommended content is failure according to the recommendation feedback information;

a new emotion determination module 1406, which may be configured to determine a new emotion identification from the acquired new collected data;

the second pushing module 1408 may be configured to select top N emotion identifications with highest recommendation weights from the historical emotion identifications and the new emotion identifications, and push recommended content matched with the N emotion identifications to the client, where N is a non-zero natural number.

Based on the foregoing description of the method embodiment that may be implemented on the client side, the disclosure further provides a content recommendation device. Fig. 15 is a block diagram of a content recommendation device, according to an example embodiment. The apparatus may be a client 110, and in particular, referring to fig. 15, the apparatus 100 may include:

The vital sign acquisition module 1502 may be configured to acquire vital sign information acquired by the wearable device;

an information uploading module 1504, configured to send playing content information and the vital sign information to a server;

the recommended content receiving module 1506 may be configured to receive recommended content sent by a server, where the recommended content includes recommended content that the server finds a mood identifier that matches a playing video, where the mood identifier is determined according to the vital sign information;

a play module 1508 may be used to play the recommended content.

shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

An exemplary embodiment is shown in fig. 16, and fig. 16 is a block diagram of a content recommendation device according to an exemplary embodiment. Referring to fig. 16, the apparatus 100 may further include:

the feedback collection module 1602 may be configured to collect, when the recommended content is played, recommendation feedback information including play duration information of the recommended content and terminal operation information when the recommended content is played;

The first feedback module 1604 may be configured to send the recommendation feedback information to the server, where the recommendation feedback information is configured to push, to the client, new recommended content that matches with the emotion identifier of the recommended content to a preset requirement when determining that the recommendation result of the recommended content is successful according to the recommendation feedback information.

An exemplary embodiment is shown in fig. 17, and fig. 17 is a block diagram of a content recommendation device according to an exemplary embodiment. Referring to fig. 17, the apparatus 100 may further include:

the first new receiving module 1702 may be configured to receive, after sending the recommendation feedback information to the server, new recommended content sent by the server, where the new recommended content is determined by:

An exemplary embodiment is shown in fig. 18, and fig. 18 is a block diagram of a content recommendation device according to an exemplary embodiment. Referring to fig. 18, the apparatus 100 may further include:

a second feedback module 1804, configured to send the recommendation feedback information to the server, where the recommendation feedback information is configured to reduce a recommendation weight of a mood identifier of the recommended content to obtain a recommendation weight of a historical mood identifier when determining, according to the recommendation feedback information, that a recommendation result of the recommended content is failed;

the second new receiving module 1802 may be configured to receive new recommended content sent by the server, where the new recommended content is determined by:

The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for a hardware+program class embodiment, the description is relatively simple, as it is substantially similar to the method embodiment, as relevant see the partial description of the method embodiment.

It should be noted that the descriptions of the apparatus, device, server, etc. according to the method embodiments may further include other implementations, and specific implementations may refer to descriptions of related method embodiments. Meanwhile, new embodiments formed by combining features of the embodiments of the method, the device, the equipment and the server still fall within the implementation scope covered by the disclosure, and are not described in detail herein.

For convenience of description, the above devices are described as being functionally divided into various modules, respectively. Of course, when one or more of the present description is implemented, the functions of each module may be implemented in the same piece or pieces of software and/or hardware, or a module that implements the same function may be implemented by a plurality of sub-modules or a combination of sub-units, or the like. The above-described apparatus embodiments are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another module apparatus/system, or some features may be omitted, or not performed. Alternatively, the coupling, communication connection, etc. of the illustrated or described devices or units to each other may be implemented in a direct and/or indirect coupling/connection manner, and may be implemented in an electrical, mechanical or other form by some standard or custom interface, protocol, etc.

FIG. 19 is a block diagram illustrating a content recommendation processing device Z00, according to an example embodiment. The device Z00 may be an electronic device on the side of a video viewing account, for example, the device Z00 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, or the like.

Referring to fig. 19, device Z00 may include one or more of the following components: a processing component Z02, a memory Z04, a power component Z06, a multimedia component Z08, an audio component Z10, an input/output (I/O) interface Z12, a sensor component Z14, and a communication component Z16.

The processing component Z02 generally controls overall operation of the device Z00, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing component Z02 may include one or more processors Z20 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component Z02 may include one or more modules that facilitate interactions between the processing component Z02 and other components. For example, the processing component Z02 may include a multimedia module to facilitate interaction between the multimedia component Z08 and the processing component Z02.

The memory Z04 is configured to store various types of data to support operations at the device Z00. Examples of such data include instructions for any application or method operating on device Z00, contact data, phonebook data, messages, pictures, video, and the like. The memory Z04 may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as static random access memory (12 RAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

The power supply component Z06 provides power to the various components of the device Z00. Power component Z06 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for device Z00.

The multimedia component Z08 comprises a screen between the device Z00 and the object providing an output interface. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from an object. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or slide action, but also the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component Z08 includes a front camera and/or a rear camera. The front camera and/or the rear camera may receive external multimedia data when the device Z00 is in an operation mode, such as a photographing mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

The audio component Z10 is configured to output and/or input an audio signal. For example, the audio component Z10 includes a Microphone (MIC) configured to receive external audio signals when the device Z00 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may be further stored in the memory Z04 or transmitted via the communication component Z16. In some embodiments, the audio component Z10 further comprises a speaker for outputting audio signals.

The I/O interface Z12 provides an interface between the processing component Z02 and a peripheral interface module, which may be a keyboard, click wheel, button, etc. These buttons may include, but are not limited to: homepage button, volume button, start button, and lock button.

Sensor assembly Z14 includes one or more sensors for providing status assessment of various aspects of device Z00. For example, sensor assembly Z14 may detect the on/off state of device Z00, the relative positioning of the assemblies, such as the display and keypad of device Z00, the sensor assembly Z14 may also detect the change in position of device Z00 or a component of device Z00, the presence or absence of an object in contact with device Z00, the orientation or acceleration/deceleration of device Z00, and the change in temperature of device Z00. The sensor assembly Z14 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly Z14 may also include a light sensor, such as a CMO12 or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly Z14 may also include an acceleration sensor, a gyroscopic sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component Z16 is configured to facilitate wired or wireless communication between the device Z00 and other devices. Device Z00 may access a wireless network based on a communication standard, such as WiFi, an operator network (e.g., 2G, 3G, 4G, or 5G), or a combination thereof. In one exemplary embodiment, the communication component Z16 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component Z16 further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the device Z00 may be implemented by one or more application specific integrated circuits (A12 ICs), digital signal processors (D12 Ps), digital signal processing devices (D12 PDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components for performing the content recommendation method described above that may be implemented on the client side.

It should be noted that, the device Z00 may be an exemplary description of an electronic device on the side of playing the shared content, such as a mobile phone. In some end products it may not be necessary to include all of the components described above or all of the functional units below a certain component.

In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as a memory Z04, comprising instructions executable by the processor Z20 of the device Z00 to perform the content recommendation method described above, which may be implemented on the client side. For example, the non-transitory computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.

Fig. 20 is a block diagram of a content recommendation device S00, according to an exemplary embodiment. For example, device S00 may be a combination of one or more servers, such as a server that analyzes vital sign information to determine emotion tags, a server that looks up matching recommended content based on emotion identifications, a server that adjusts the recommended weights of emotion identifications, and the like, as well as combinations thereof. Referring to fig. 20, device S00 includes a processing component S20 that further includes one or more processors, and memory resources represented by memory S22, for storing instructions, such as applications, executable by processing component S20. The application program stored in the memory S22 may include one or more modules each corresponding to a set of instructions. Further, the processing component S20 is configured to execute instructions to perform the content recommendation method described above, which may be implemented on a server.

Device S00 can also include a power component S24 configured to perform power management of device S00, a wired or wireless network interface S26 configured to connect device S00 to a network, and an input/output (I/O) interface S28. Device S00 may operate based on an operating system stored in memory S22, such as Window12 12erver,Mac O12X,Unix,Linux,FreeB12D or the like.

In an exemplary embodiment, a storage medium is also provided, e.g. a memory S22 comprising instructions executable by a processor of the device S00 to perform the content recommendation method described above, which may be implemented on the server side. The storage medium may be a non-transitory computer readable storage medium, which may be, for example, ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. Readable storage media for other implementations, such as quantum storage, graphene storage, and the like.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof.

Claims

1. A content recommendation method, comprising:

searching recommended content matched with the emotion mark;

sending the searched recommended content to the client;

2. The method of claim 1, wherein the recommended content matching the emotion identification comprises:

Shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

3. The method of claim 1, further comprising, when determining that the recommendation of the recommended content is successful based on the recommendation feedback information:

4. The method of claim 1, further comprising, after transmitting the found recommended content to the client:

Determining a new emotion mark according to the acquired new acquired data;

5. A content recommendation method, comprising:

acquiring vital sign information acquired by wearable equipment;

playing the recommended content;

and sending the recommendation feedback information to the server, wherein the recommendation feedback information is used for pushing new recommended content, the emotion identification matching degree of which meets the preset requirement, to the client when the recommendation result of the recommended content is determined to be successful according to the recommendation feedback information.

6. The method of claim 5, wherein the recommended content matching the emotion identification comprises:

shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

7. The method of claim 5, further comprising receiving new recommended content sent by a server after sending the recommended feedback information to the server, the new recommended content determined by:

8. The method of claim 5, further comprising, after playing the recommended content:

9. A content recommendation device, comprising:

The sending module is used for sending the searched recommended content to the client;

10. The apparatus of claim 9, wherein the recommended content matching the emotion recognition may include:

shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

11. The apparatus of claim 9, wherein the apparatus further comprises:

12. The apparatus of claim 9, wherein the apparatus further comprises:

13. A content recommendation device, the device comprising:

the playing module is used for playing the recommended content;

14. The apparatus of claim 13, wherein the recommended content matching the emotion recognition comprises:

shared content matching the emotional identifier,

or,

and the associated content of the target account matched with the emotion mark.

15. The apparatus of claim 13, wherein the apparatus further comprises:

16. The apparatus of claim 13, wherein the apparatus further comprises:

17. An electronic device, comprising:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the method of any one of claims 1 to 4.

18. A storage medium, characterized in that instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the method of any one of claims 1 to 4.

19. A server, comprising:

at least one processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the method of any one of claims 5 to 8.

20. A storage medium, characterized in that instructions in the storage medium, when executed by a processor of a server, enable the server to perform the method of any one of claims 5 to 8.