CN112967086B - Intelligent marketing promotion method and device and electronic equipment - Google Patents
Intelligent marketing promotion method and device and electronic equipment Download PDFInfo
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Abstract
The embodiment of the specification provides an intelligent marketing promotion method, which comprises the steps of identifying a time fluctuation relation among different behaviors by obtaining a plurality of behaviors and behavior time of a sample user, constructing a biological clock fluctuation model based on the plurality of behaviors, the behavior time and the time fluctuation relation of the sample user, determining attribute information of a current biological clock stage of the user by using the biological clock fluctuation model, screening a plurality of video contents matched with the biological clock fluctuation model, improving the probability of playing videos of the user due to the fact that the video contents give consideration to the current biological clock period fluctuation of the user, selecting a target frame picture for the user by using a frame picture screening model constructed by big data in combination with operation duration, giving consideration to the current urgent state of the user, shortening the time consumed by attracting the user, determining the current content information to be promoted based on the biological clock stage attribute information of the user, implanting the content information into the target frame picture, the frame pictures after being played are popularized by means of the frame pictures matched with the user states, and the popularization effect is improved.
Description
Technical Field
The application relates to the field of internet, in particular to an intelligent marketing promotion method and device and electronic equipment.
Background
With the development of big data and artificial intelligence, marketing means are endlessly developed, and currently, related video content is pushed to the user according to the preference of the user through data mining in the industry, so that accurate marketing is realized.
Some schemes periodically push certain analogy broad content to the user by dividing the period so as to improve the activity of the user on the promotion content by utilizing the periodic habit of the user.
However, although the marketing method can improve the popularization accuracy to a certain extent, the popularization effect still has a space for improvement.
Therefore, it is necessary to provide a new marketing promotion method to further improve the promotion accuracy and promote the promotion effect.
The reason why the improvement space exists is that the state of the user may change or fluctuate, and if the user is periodically pushed with a certain amount of broad content, the promoted content is difficult to match the fluctuated state of the user and attract the user, and the promotion effect is reduced.
The above information disclosed in this background section is only for enhancement of understanding of the background of the disclosure and therefore it may contain information that does not constitute prior art that is already known to a person of ordinary skill in the art.
Disclosure of Invention
The embodiment of the specification provides an intelligent marketing promotion method and device and electronic equipment, and is used for improving the promotion effect.
An embodiment of the present specification provides an intelligent marketing promotion method, including:
acquiring various behaviors and behavior time of a sample user, identifying time fluctuation relations among different behaviors, and constructing a biological clock fluctuation model based on the various behaviors, the behavior time and the time fluctuation relations of the sample user;
searching for target video content in response to a video content request of a current user, comprising:
calling a biological clock fluctuation model to determine the corresponding biological clock phase attribute information of the operation moment triggering the video content request in the fluctuated biological clock cycle, and pre-screening a plurality of video contents matched with the biological clock phase attribute information;
screening target video content from the plurality of video content matched with the biological clock stage attribute information;
acquiring data of a sample user, and constructing and training a frame picture screening model in a supervised learning mode;
determining the associated user of the current user, and collecting the playing result data of the associated user to the target video content;
calling a frame picture screening model, and selecting a target frame picture from the target video content by using the self attribute information of the current user, the operation duration for triggering the video content request and the playing amount of each frame picture in the video content;
determining current content information to be promoted based on the biological clock stage attribute information of the user, and implanting the content information to be promoted into the target frame picture;
and playing the frame picture behind the target frame picture by taking the target frame picture as a first frame.
Optionally, the method further comprises:
acquiring the moment of reference behavior generated by the current user in the current biological clock cycle, and determining the fluctuation characteristic of the reference behavior based on the fluctuation of the moment of the reference behavior compared with the fluctuation of the moment in the historical biological clock cycle;
and determining the fluctuated current biological clock cycle and the predicted time of each behavior in the fluctuated current biological clock cycle according to the fluctuation characteristics of the reference behavior generated by the current user.
Optionally, the determining, according to the fluctuation feature of the reference behavior generated by the current user, the current biological clock cycle after fluctuation and the predicted time of each behavior in the current biological clock cycle after fluctuation includes:
determining the fluctuation direction and amplitude of the current biological clock cycle after fluctuation by combining the relation direction of the reference behavior and the operation triggering the video content request and the fluctuation direction and amplitude of the reference behavior;
and adjusting the current biological clock cycle and the predicted time of each action in the fluctuated current biological clock cycle according to the fluctuation direction and amplitude of the fluctuated current biological clock cycle.
Optionally, the adjusting the current biological clock cycle and the predicted time of each behavior in the fluctuated current biological clock cycle according to the fluctuation direction and the amplitude of the fluctuated current biological clock cycle includes:
if the reference behavior and the operation for triggering the video content request are complementary behaviors, adjusting the prediction time of each behavior in the fluctuated current biological clock cycle according to the fluctuation direction of the reference behavior in time;
if the reference behavior and the operation for triggering the video content request are competitive behaviors, the prediction time of each behavior in the current biological clock cycle after fluctuation is adjusted according to the direction opposite to the fluctuation direction of the reference behavior in time.
Optionally, the biological clock phase attribute information is a predicted time of each behavior in a current biological clock cycle after fluctuation.
Optionally, the screening target video content from the plurality of video contents matched with the biological clock stage attribute information includes:
determining the last video content played by the current user, and determining the playback frequency of the last video content according to the collected playing result data;
if the playback frequency is smaller than a threshold value, determining target video content provided for the current user in the same type of video of the previous video content; and if the playback times are larger than a threshold value, determining the target video content provided for the current user in the heterogeneous video of the previous video content.
Optionally, the invoking a frame screening model, selecting a target frame from the target video content by using the attribute information of the current user, the operation duration for triggering the video content request, and the play amount of each frame in the video content, includes:
selecting a target frame picture by combining the self attribute information of the current user and the playing amount of each frame picture in the video content;
and determining urgent attribute information of the current user according to the operation duration, and adjusting a target frame picture used as a first frame based on the urgent attribute information.
Optionally, the determining the urgent attribute information of the current user according to the operation duration includes:
and determining the action type of the operation, and determining the urgent attribute information of the operation by taking the duration of the same type of operation as a reference.
Optionally, the adjusting a target frame picture based on the urgency attribute information includes:
and if the urgent attribute information meets the preset abundant state identification condition, moving the target frame picture forwards.
Optionally, the moving forward the target frame picture comprises:
determining a plurality of recommended frames set by a provider of the target video content, determining a recommended frame positioned before the target frame picture on a time axis from the plurality of recommended frames, and adjusting the recommended frame to be the target frame picture;
the playing the frame picture after the target frame picture by taking the target frame picture as the head frame comprises the following steps:
and playing the frame picture behind the target frame picture by taking the adjusted target frame picture as a first frame.
Optionally, the method further comprises:
and generating a frame image playing curve according to the playing result data of the target video content, and displaying the frame image playing curve and the operation assembly, wherein the vertical axis of the playing curve is the playing amount of each frame image, so that a user can select the frame image to be played by adjusting the operation assembly.
This specification embodiment still provides an intelligence marketing popularization device, includes:
the biological clock model module is used for acquiring various behaviors and behavior time of a sample user, identifying time fluctuation relations among different behaviors, and constructing a biological clock fluctuation model based on the various behaviors, the behavior time and the time fluctuation relations of the sample user;
the target video module responds to the video content request of the current user and searches the target video content, and comprises:
calling a biological clock fluctuation model to determine the corresponding biological clock phase attribute information of the operation moment triggering the video content request in the fluctuated biological clock cycle, and pre-screening a plurality of video contents matched with the biological clock phase attribute information;
screening target video contents from the plurality of video contents matched with the biological clock stage attribute information;
the target frame module is used for acquiring data of sample users, and constructing and training a frame picture screening model in a supervised learning mode;
determining the associated user of the current user, and collecting the playing result data of the associated user to the target video content;
calling a frame picture screening model, and selecting a target frame picture from the target video content by using the self attribute information of the current user, the operation duration for triggering the video content request and the playing amount of each frame picture in the video content;
the promotion module is used for determining the current content information to be promoted based on the biological clock stage attribute information of the user and implanting the content information to be promoted into the target frame picture;
and playing the frame picture behind the target frame picture by taking the target frame picture as a first frame.
Optionally, the biological clock model module is further configured to:
acquiring the moment of reference behavior generated by the current user in the current biological clock cycle, and determining the fluctuation characteristic of the reference behavior based on the fluctuation of the moment of the reference behavior compared with the fluctuation of the moment in the historical biological clock cycle;
and determining the fluctuated current biological clock cycle and the predicted time of each behavior in the fluctuated current biological clock cycle according to the fluctuation characteristics of the reference behavior generated by the current user.
Optionally, the determining, according to the fluctuation feature of the reference behavior generated by the current user, the current biological clock cycle after fluctuation and the predicted time of each behavior in the current biological clock cycle after fluctuation includes:
determining the fluctuation direction and amplitude of the current biological clock cycle after fluctuation by combining the relation direction of the reference behavior and the operation triggering the video content request and the fluctuation direction and amplitude of the reference behavior;
and adjusting the current biological clock cycle and the prediction time of each action in the fluctuated current biological clock cycle according to the fluctuation direction and the amplitude of the fluctuated current biological clock cycle.
Optionally, the adjusting the current biological clock cycle and the predicted time of each behavior in the fluctuated current biological clock cycle according to the fluctuation direction and the amplitude of the fluctuated current biological clock cycle includes:
if the reference behavior and the operation for triggering the video content request are complementary behaviors, adjusting the prediction time of each behavior in the fluctuated current biological clock cycle according to the fluctuation direction of the reference behavior in time;
if the reference behavior and the operation for triggering the video content request are competitive behaviors, the prediction time of each behavior in the current biological clock cycle after fluctuation is adjusted according to the reverse direction of the fluctuation direction of the reference behavior in time.
Optionally, the biological clock phase attribute information is a predicted time of each behavior in a current biological clock cycle after fluctuation.
Optionally, the screening target video content from the plurality of video contents matched with the biological clock stage attribute information includes:
determining the last video content played by the current user, and determining the playback frequency of the last video content according to the collected playing result data;
if the playback frequency is smaller than a threshold value, determining target video content provided for the current user in the same type of video of the previous video content; and if the playback times are larger than a threshold value, determining the target video content provided for the current user in the heterogeneous video of the previous video content.
Optionally, the invoking the frame picture screening model, selecting a target frame picture from the target video content by using the attribute information of the current user, the operation duration for triggering the video content request, and the play amount of each frame picture in the video content, includes:
selecting a target frame picture by combining the self attribute information of the current user and the playing amount of each frame picture in the video content;
and determining urgent attribute information of the current user according to the operation duration, and adjusting a target frame picture used as a first frame based on the urgent attribute information.
Optionally, the determining the urgent attribute information of the current user according to the operation duration includes:
and determining the action type of the operation, and determining the urgent attribute information of the operation by taking the duration of the same type of operation as a reference.
Optionally, the adjusting a target frame picture based on the urgency attribute information includes:
and if the urgent attribute information meets the preset abundant state identification condition, moving the target frame picture forwards.
Optionally, the moving forward the target frame picture comprises:
determining a plurality of recommended frames set by a provider of the target video content, determining a recommended frame positioned before the target frame picture on a time axis from the plurality of recommended frames, and adjusting the recommended frame to be the target frame picture;
the playing the frame picture after the target frame picture by taking the target frame picture as the head frame comprises the following steps:
and playing the frame picture behind the target frame picture by taking the adjusted target frame picture as a first frame.
Optionally, the playing module is further configured to:
and generating a frame image playing curve according to the playing result data of the target video content, and displaying the frame image playing curve and the operation assembly, wherein the vertical axis of the playing curve is the playing amount of each frame image, so that a user can select the frame image to be played by adjusting the operation assembly.
An embodiment of the present specification further provides an electronic device, where the electronic device includes:
a processor; and the number of the first and second groups,
a memory storing computer-executable instructions that, when executed, cause the processor to perform any of the methods described above.
The present specification also provides a computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement any of the above methods.
The technical proposal provided by the embodiment of the specification identifies the time fluctuation relationship among different behaviors by acquiring the multiple behaviors and behavior time of a sample user, constructs a biological clock fluctuation model based on the multiple behaviors, behavior time and time fluctuation relationship of the sample user, determines the attribute information of the current biological clock stage of the user by using the biological clock fluctuation model, screens out a plurality of video contents matched with the biological clock fluctuation model, improves the probability of playing videos by the user due to the fact that the video contents give consideration to the current biological clock period fluctuation of the user, selects a target frame picture for the user by using a frame picture screening model constructed by big data and combining with the operation duration, shortens the time consumed by attracting the user, determines the current content information to be promoted based on the biological clock stage attribute information of the user, and implants the content information into the target frame picture, the frame pictures after being played are popularized by means of the frame pictures matched with the user states, and the popularization effect is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic diagram illustrating a principle of an intelligent marketing promotion method according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an intelligent marketing promotion device provided in an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. The exemplary embodiments, however, may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals denote the same or similar elements, components, or parts in the drawings, and thus their repetitive description will be omitted.
Features, structures, characteristics or other details described in a particular embodiment do not preclude the fact that the features, structures, characteristics or other details may be combined in a suitable manner in one or more other embodiments in accordance with the technical idea of the invention.
In describing particular embodiments, the present invention has been described with reference to features, structures, characteristics or other details that are within the purview of one skilled in the art to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific features, structures, characteristics, or other details.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The term "and/or" and/or "includes all combinations of any one or more of the associated listed items.
Fig. 1 is a schematic diagram illustrating a method for intelligent marketing and promotion provided in an embodiment of the present disclosure, where the method may include:
s101: the method comprises the steps of obtaining multiple behaviors and behavior time of a sample user, identifying time fluctuation relations among different behaviors, and constructing a biological clock fluctuation model based on the multiple behaviors, the behavior time and the time fluctuation relations of the sample user.
In the embodiment of the present specification, the biological clock fluctuation model is a model that considers the fluctuation of the biological clock cycle of the user, and is used to consider the biological clock fluctuation of the user and adjust the biological clock cycle and the time at which the phase corresponding to each state of the user is located in the cycle according to the fluctuation of the biological clock cycle.
In the embodiment of the specification, in the current biological clock cycle, the fluctuation of the current biological clock cycle can be identified according to the historical behavior of the user in the current biological clock cycle, and the time of the phase corresponding to each state of the user is adjusted according to the fluctuation.
Therefore, when a subsequent user requests video content, the adaptive video content can be searched according to the fluctuated user state corresponding to the current time.
The unstable state of the user, on one hand, shows that the user behavior fluctuates during different time periods, and a certain type of video is pushed to the user for multiple times according to a fixed time period (for example, 20:00 per day), so that the effect of pushing the video pushed to the user is poor when the state of the user on a certain day changes suddenly.
Then, we think of the biological clock principle for how to push the video, not according to a fixed time period.
The biological clock is periodic, if the biological clock period law is utilized to push the video, the state fluctuation of the biological clock of the user is considered, the pushed content is always adapted to the state of the user in the current biological clock, the matching performance of the pushed content and the current state of the user can be improved, the pushing accuracy is improved, and the pushing effect is further improved.
In a practical scenario, the non-sleep time of a user is 14h every day, and during working days, videos of English learning class are browsed in a learning stage (such as 21: 00), and a sleep stage (such as 22:00) starts going to bed, so that the user is pushed with the videos for hypnosis at 22:00 every day. And the user gets up and postpones for 1h by the weekend, at this time, the non-sleep time of the user at 22:00 just reaches 13h, and the user is not sleepy, although the time at this time is 22:00, the user still has 1h of energy in the biological clock cycle of the day, if the video content (hypnotic video) of 22:00 is pushed to the user as usual, the user may feel dislike, at this time, the user delays for 1h by recognizing the day of the weekend, and then, the user calculates the day of the weekend, the learning stage of the user fluctuates to 22:00, and the hypnotic stage fluctuates to 23:00 (by way of example only, not by way of limitation, and also may fluctuate to 22: 30).
Then, a plurality of video contents are screened out according to the biological clock period after fluctuation and the attributes of each biological clock stage in the biological clock period after fluctuation, so that the plurality of video contents can be matched with the biological clock period after fluctuation of the user, and the video popularization effect is improved.
Wherein different biological clock phase attribute information may correspond to different user states. The user state here is an energy consumption state of the user.
Wherein, the fluctuation relation can comprise a fluctuation direction and a fluctuation amplitude, and the fluctuation direction can comprise an opposite direction.
Of course, the same direction may be included.
In real life, this can represent a scenario that after a user gets up for a delay, eating time is delayed, and the time for watching food videos is also delayed; another scenario may be shown where the user has more time to idle on weekends, getting up late in morning exercise time and then watching the fitness video, but where the user is idle and has not much to do, the time to watch the game video is advanced from evening on weekdays to evening on weekends.
S102: searching for target video content in response to a video content request of a current user may include:
calling a biological clock fluctuation model to determine the corresponding biological clock phase attribute information of the operation moment triggering the video content request in the fluctuated biological clock cycle, and pre-screening a plurality of video contents matched with the biological clock phase attribute information;
and screening target video content from the plurality of video contents matched with the biological clock stage attribute information.
Wherein, the video content is non-advertisement video.
The biological clock cycle has a plurality of stages, each stage corresponds to a user state, and the time of the stage corresponding to each user state in the biological clock cycle after fluctuation is adjusted.
And the biological clock phase attribute information is the predicted time of each behavior in the fluctuated current biological clock cycle. In this way, according to the current time, i.e. the operating time that triggered the video content request, the behavior corresponding to the predicted time that matches this time can be determined.
It is also known which action the user has a high probability of needing to perform at that moment, according to the user's biological clock. The behavior here may refer to playing a video.
In order to evaluate the fluctuations of the current biological clock cycle, one or more reference behaviors may be determined, and the fluctuations of the current biological clock cycle may be determined based on the fluctuations of the reference behaviors, considering that the user performs more than one activity or behavior in each cycle, and the time of performing the plurality of behaviors is often related.
In the embodiment of the present specification, the method may further include:
acquiring the moment of reference behavior generated by the current user in the current biological clock cycle, and determining the fluctuation characteristic of the reference behavior based on the fluctuation of the moment of the reference behavior compared with the fluctuation of the moment in the historical biological clock cycle;
and determining the fluctuated current biological clock cycle and the predicted time of each behavior in the fluctuated current biological clock cycle according to the fluctuation characteristics of the reference behavior generated by the current user.
In this embodiment, the determining, according to the fluctuation feature of the reference behavior generated by the current user, a fluctuated current biological clock cycle and a predicted time of each behavior in the fluctuated current biological clock cycle may include:
determining the fluctuation direction and amplitude of the current biological clock cycle after fluctuation by combining the relation direction of the reference behavior and the operation triggering the video content request and the fluctuation direction and amplitude of the reference behavior;
and adjusting the current biological clock cycle and the predicted time of each action in the fluctuated current biological clock cycle according to the fluctuation direction and amplitude of the fluctuated current biological clock cycle.
In this embodiment, the adjusting the current biological clock cycle and the predicted time of each behavior in the fluctuated current biological clock cycle according to the fluctuation direction and amplitude of the fluctuated current biological clock cycle may include:
if the reference behavior and the operation for triggering the video content request are complementary behaviors, adjusting the prediction time of each behavior in the fluctuated current biological clock cycle according to the fluctuation direction of the reference behavior in time;
if the reference behavior and the operation for triggering the video content request are competitive behaviors, the prediction time of each behavior in the current biological clock cycle after fluctuation is adjusted according to the reverse direction of the fluctuation direction of the reference behavior in time.
The complementary behavior is a behavior in which an equivalence relation exists, and the competitive behavior is a behavior in which a competitive relation exists in time allocation.
For example, breakfast and lunch both result in allaying hunger and enable the user to be in a state of the belly within a certain time period after meals. Then, after breakfast is delayed, lunch is usually delayed. Therefore, the time fluctuation of lunch in the biological clock cycle can be adjusted according to the time fluctuation of the user watching the eating and broadcasting video in the morning, and the eating and broadcasting video is pushed according to the lunch time after the fluctuation.
If the learning and working time is advanced, the time is short, and at the moment, the entertainment time is generally pushed backward, and because the entertainment behavior and the learning behavior have a competitive relationship in time distribution, the time for pushing the entertainment video to the user can be reversely adjusted according to the time fluctuation direction of the user watching the learning video.
In one scenario, a push page has multiple video areas, and a user can refresh the push page through a swipe down action, at this time, the front-end program sends a random request to the server to request to acquire video content.
Considering that when a user watches a video, the user often needs to meet a certain requirement, for example, watching a food video, and needs to obtain a cooking skill, when the user has obtained a certain cooking skill according to the food video, the user often does not have interest or need to continue browsing the video, at this time, if the server continues to push the cooking video of the food to the user, the user often does not open the playing, which obviously results in an opportunity cost of pushing a page, and if we can recognize that the user has met the requirement by watching the video at present, and then pushes other types of videos to the user, the user has a high possibility of clicking the video to play.
Then, how to identify whether the user has satisfied such a requirement. Applicants have contemplated considering a scenario: when watching the cooking video, the user often exits by playing the video once or half if the user is not interested, and often plays back the video many times to obtain the details of the video if the user is interested in the video. Therefore, if a user plays back a certain video for a plurality of times, we can judge that the played back video currently meets the requirements of the user with high probability, and at this time, we can provide the user with other types of video contents.
In this embodiment, the screening target video content from the plurality of video contents matched with the biological clock stage attribute information may include:
determining the last video content played by the current user, and determining the playback frequency of the last video content according to the collected playing result data;
if the playback frequency is smaller than a threshold value, determining target video content provided for the current user in the same type of video of the previous video content; and if the playback times are larger than a threshold value, determining the target video content provided for the current user in the heterogeneous video of the previous video content.
S103: and acquiring data of a sample user, and constructing and training a frame picture screening model by using a supervised learning mode.
The data of the sample user can be attribute information of the sample user, video content browsed by the sample user, and the playing times of each frame of picture of the video content.
S104: and determining the associated user of the current user, and collecting the playing result data of the associated user to the target video content.
In this embodiment of the present specification, the play result data of the target video content by the associated user may be collected in a front end point burying manner, where the play result data may include a video content category, a return visit number, and a play number of each frame picture.
S105: and calling a frame picture screening model, and selecting a target frame picture from the target video content by utilizing the self attribute information of the current user, the operation duration for triggering the video content request and the playing amount of each frame picture in the video content.
In this embodiment of the present specification, the invoking a frame picture screening model, selecting a target frame picture from the target video content by using the attribute information of the current user, the operation duration for triggering the video content request, and the play amount of each frame picture in the video content, may include:
selecting a target frame picture by combining the self attribute information of the current user and the playing amount of each frame picture in the video content;
and determining urgent attribute information of the current user according to the operation duration, and adjusting a target frame picture used as a first frame based on the urgent attribute information.
In this embodiment of the present specification, the determining the urgent attribute information of the current user according to the operation duration may include:
and determining the action type of the operation, and determining the urgent attribute information of the operation by taking the duration of the same type of operation as a reference.
In an application scene, a user refreshes a video menu page quickly, which often indicates that the current time of the user is urgent, at this time, a plurality of pictures before a target frame picture can be omitted, and the target frame is directly used as a first frame for playing, so that the user can browse a key picture in a short time and further decide to continue playing the video or searching other videos.
Therefore, in the embodiment of the present specification, resource slots may be further added in the target frame picture and a plurality of frame pictures after the target frame picture, and marketing promotion content is displayed in the resource slots.
In another scenario, the user has more time, and it is not necessary to remove all the frames before the target frame, but only to move the target frame forward to remove a part of the frames before the target frame.
Therefore, a plurality of pictures in front of the original target frame picture can be used for laying video contents, the smoothness of cleaning is improved, and the user experience is improved.
In this embodiment, the adjusting the target frame picture based on the urgency attribute information may include:
and if the urgent attribute information meets the preset abundant state identification condition, moving the target frame picture forwards. In this embodiment, the moving forward the target frame picture may include:
determining a plurality of recommended frames set by a provider of the target video content, determining a recommended frame positioned before the target frame picture on a time axis from the plurality of recommended frames, and adjusting the recommended frame to be the target frame picture;
the playing the frame picture after the target frame picture with the target frame picture as the head frame may include:
and playing the frame picture behind the target frame picture by taking the adjusted target frame picture as a first frame.
The recommended frame may be a frame picture with a resource position, and the resource position has marketing promotion content.
In this embodiment of the present specification, we may also configure a drainage component in the resource location, and when a user operates the drainage component, obtain an activity page of the promoted content according to a link request pointed by the drainage component.
The recommended frame is adjusted to be the target frame picture, so that the drainage efficiency is improved.
In this way, the pre-screening of the plurality of video contents matching the biological clock stage attribute information may be the screening of the marketing video contents matching the biological clock stage attribute information. The plurality of video content is marketing video content.
By combining with the biological clock fluctuation of the user, the marketing video content adaptive to the attribute information of the current biological clock stage of the user is screened, so that the recommended video content can adapt to the biological clock fluctuation of the user, the defect of low matching performance existing in recommending videos to the user according to fixed time of a fixed period is overcome, and the mode is adaptive to the state of the user, so that the interest of the user can be aroused, the participation rate of the user is improved, and the drainage effect is improved.
In the embodiment of the present specification, the method may further include:
and determining the current content information to be promoted based on the biological clock stage attribute information of the user, and implanting the content information into the target frame picture.
The promotion content is adapted to the state of the user on the biological clock.
The promotional content may be a marketing campaign advertisement.
In practical application, a user can obtain the popularization content of learning materials in a learning stage, and can obtain the popularization content of entertainment activities in an entertainment stage.
S106: determining current content information to be promoted based on the biological clock stage attribute information of the user, implanting the content information to be promoted into the target frame picture, and playing a frame picture behind the target frame picture by taking the target frame picture as a first frame.
The method comprises the steps of identifying the time fluctuation relationship among different behaviors by acquiring various behaviors and behavior time of a sample user, constructing a biological clock fluctuation model based on various behaviors, behavior time and time fluctuation relationship of the sample user, determining attribute information of the current biological clock stage of the user by using the biological clock fluctuation model, screening out a plurality of video contents matched with the biological clock fluctuation model, improving the probability of playing videos of the user due to the fact that the video contents give consideration to the current biological clock period fluctuation of the user, selecting a target frame picture for the user by using a frame picture screening model constructed by big data in combination with operation duration, giving consideration to the current urgent state of the user, shortening the time consumed by attracting the user, determining the current content information to be promoted based on the biological clock stage attribute information of the user, implanting the content information into the target frame picture, playing the frame picture after playing, promoting by using the frame picture matched with the state of the user, the popularization effect is improved.
In the embodiment of the present specification, the method may further include:
and generating a frame image playing curve according to the playing result data of the target video content, and displaying the frame image playing curve and the operation assembly, wherein the vertical axis of the playing curve is the playing amount of each frame image, so that a user can select the frame image to be played by adjusting the operation assembly.
Fig. 2 is a schematic structural diagram of an intelligent marketing promotion device provided in an embodiment of this specification, where the device may include:
the biological clock model module 201 is used for acquiring various behaviors of a sample user and behavior time thereof, identifying time fluctuation relations among different behaviors, and constructing a biological clock fluctuation model based on the various behaviors, the behavior time and the time fluctuation relations of the sample user;
the target video module 202, which responds to the video content request of the current user to search for the target video content, may include:
calling a biological clock fluctuation model to determine the corresponding biological clock phase attribute information of the operation moment triggering the video content request in the fluctuated biological clock cycle, and pre-screening a plurality of video contents matched with the biological clock phase attribute information;
screening target video content from the plurality of video content matched with the biological clock stage attribute information;
the target frame module 203 is used for acquiring data of sample users, and constructing and training a frame picture screening model in a supervised learning mode;
determining the associated user of the current user, and collecting the playing result data of the associated user to the target video content;
calling a frame picture screening model, and selecting a target frame picture from the target video content by using the self attribute information of the current user, the operation duration for triggering the video content request and the playing amount of each frame picture in the video content;
the promotion module 204 is used for determining the current content information to be promoted based on the biological clock stage attribute information of the user and implanting the content information to be promoted into the target frame picture;
and playing the frame picture behind the target frame picture by taking the target frame picture as a first frame.
In an embodiment of the present specification, the biological clock model module is further configured to:
acquiring the moment of reference behavior generated by the current user in the current biological clock cycle, and determining the fluctuation characteristic of the reference behavior based on the fluctuation of the moment of the reference behavior compared with the fluctuation of the moment in the historical biological clock cycle;
and determining the fluctuated current biological clock cycle and the predicted time of each behavior in the fluctuated current biological clock cycle according to the fluctuation characteristics of the reference behavior generated by the current user.
In this embodiment, the determining, according to the fluctuation feature of the reference behavior generated by the current user, a fluctuated current biological clock cycle and a predicted time of each behavior in the fluctuated current biological clock cycle may include:
determining the fluctuation direction and amplitude of the current biological clock cycle after fluctuation by combining the relation direction of the reference behavior and the operation triggering the video content request and the fluctuation direction and amplitude of the reference behavior;
and adjusting the current biological clock cycle and the prediction time of each action in the fluctuated current biological clock cycle according to the fluctuation direction and the amplitude of the fluctuated current biological clock cycle.
In this embodiment of the present specification, the adjusting the predicted time of the current biological clock cycle and each behavior in the fluctuated current biological clock cycle according to the fluctuation direction and the amplitude of the fluctuated current biological clock cycle may include:
if the reference behavior and the operation for triggering the video content request are complementary behaviors, adjusting the prediction time of each behavior in the fluctuated current biological clock cycle according to the fluctuation direction of the reference behavior in time;
if the reference behavior and the operation for triggering the video content request are competitive behaviors, the prediction time of each behavior in the current biological clock cycle after fluctuation is adjusted according to the direction opposite to the fluctuation direction of the reference behavior in time.
In an embodiment of the present specification, the biological clock phase attribute information is a predicted time of the behaviors in a current biological clock cycle after fluctuation.
In this embodiment, the screening target video content from the plurality of video contents matched with the biological clock stage attribute information may include:
determining the last video content played by the current user, and determining the playback frequency of the last video content according to the collected playing result data;
if the playback frequency is smaller than a threshold value, determining target video content provided for the current user in the same type of video of the previous video content; and if the playback times are larger than a threshold value, determining the target video content provided for the current user in the heterogeneous video of the previous video content.
In this embodiment of the present specification, the invoking a frame picture screening model, selecting a target frame picture from the target video content by using the attribute information of the current user, the operation duration for triggering the video content request, and the play amount of each frame picture in the video content, may include:
selecting a target frame picture by combining the self attribute information of the current user and the playing amount of each frame picture in the video content;
and determining urgent attribute information of the current user according to the operation duration, and adjusting a target frame picture used as a first frame based on the urgent attribute information.
In this embodiment of the present specification, the determining the urgent attribute information of the current user according to the operation duration may include:
and determining the action type of the operation, and determining the urgent attribute information of the operation by taking the duration of the same type of operation as a reference.
In this embodiment, the adjusting the target frame picture based on the urgency attribute information may include:
and if the urgent attribute information meets the preset abundant state identification condition, moving the target frame picture forwards.
In this embodiment, the moving forward the target frame picture may include:
determining a plurality of recommended frames set by a provider of the target video content, determining a recommended frame positioned before the target frame picture on a time axis from the plurality of recommended frames, and adjusting the recommended frame to be the target frame picture;
the playing the frame picture after the target frame picture with the target frame picture as the head frame may include:
and playing the frame picture behind the target frame picture by taking the adjusted target frame picture as a first frame.
In an embodiment of this specification, the playing module is further configured to:
and generating a frame image playing curve according to the playing result data of the target video content, and displaying the frame image playing curve and the operation assembly, wherein the vertical axis of the playing curve is the playing amount of each frame image, so that a user can select the frame image to be played by adjusting the operation assembly.
The device identifies the time fluctuation relation among different behaviors by acquiring various behaviors and behavior time of a sample user, constructs a biological clock fluctuation model based on the various behaviors, the behavior time and the time fluctuation relation of the sample user, determines the attribute information of the current biological clock stage of the user by using the biological clock fluctuation model, screens out a plurality of video contents matched with the biological clock fluctuation model, improves the probability of playing videos by the user due to the fact that the video contents give consideration to the fluctuation of the current biological clock period of the user, selects a target frame picture for the user by using a frame picture screening model constructed by big data in combination with operation duration, gives consideration to the current urgent state of the user, shortens the time consumed by attracting the user, determines the current content information to be promoted based on the biological clock stage attribute information of the user, implants the content information into the target frame picture, plays the frame picture after playing, and promotes by means of the frame picture matched with the state of the user, the popularization effect is improved.
Based on the same inventive concept, the embodiment of the specification further provides the electronic equipment.
In the following, embodiments of the electronic device of the present invention are described, which may be regarded as specific physical implementations for the above-described embodiments of the method and apparatus of the present invention. Details described in the embodiments of the electronic device of the invention should be considered supplementary to the embodiments of the method or apparatus described above; for details which are not disclosed in embodiments of the electronic device of the invention, reference may be made to the above-described embodiments of the method or the apparatus.
Fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure. An electronic device 300 according to this embodiment of the invention is described below with reference to fig. 3. The electronic device 300 shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 3, electronic device 300 is embodied in the form of a general purpose computing device. The components of electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one memory unit 320, a bus 330 connecting the various system components (including the memory unit 320 and the processing unit 310), a display unit 340, and the like.
Wherein the storage unit stores program code that can be executed by the processing unit 310 to cause the processing unit 310 to perform the steps according to various exemplary embodiments of the present invention described in the above-mentioned processing method section of the present specification. For example, the processing unit 310 may perform the steps as shown in fig. 1.
The storage unit 320 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM)3201 and/or a cache storage unit 3202, and may further include a read only memory unit (ROM) 3203.
The storage unit 320 may also include a program/utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 300 may also communicate with one or more external devices 400 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 300, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 300 to communicate with one or more other computing devices. Such communication may occur through input/output (I/O) interface 350. Also, the electronic device 300 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 360. Network adapter 360 may communicate with other modules of electronic device 300 via bus 330. It should be appreciated that although not shown in FIG. 3, other hardware and/or software modules may be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the description of the above embodiments, those skilled in the art will readily understand that the exemplary embodiments described in the present invention may be implemented by software, and may also be implemented by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention. The computer program, when executed by a data processing apparatus, enables the computer readable medium to implement the above-described method of the invention, namely: such as the method shown in fig. 1.
Fig. 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
A computer program implementing the method shown in fig. 1 may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In situations involving remote computing devices, the remote computing devices may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to external computing devices (e.g., through the internet using an internet service provider).
In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in embodiments in accordance with the invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP). The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. An intelligent marketing promotion method is characterized by comprising the following steps:
acquiring various behaviors and behavior time of a sample user, identifying time fluctuation relations among different behaviors, and constructing a biological clock fluctuation model based on the various behaviors, the behavior time and the time fluctuation relations of the sample user;
searching for target video content in response to a video content request of a current user, comprising:
calling a biological clock fluctuation model to determine the corresponding biological clock phase attribute information of the operation moment triggering the video content request in the fluctuated biological clock cycle, and pre-screening a plurality of video contents matched with the biological clock phase attribute information;
screening target video content from the plurality of video content matched with the biological clock stage attribute information;
acquiring data of a sample user, and constructing and training a frame picture screening model in a supervised learning mode;
determining the associated user of the current user, and collecting the playing result data of the associated user to the target video content;
calling a frame picture screening model, and selecting a target frame picture from the target video content by using the self attribute information of the current user, the operation duration for triggering the video content request and the playing amount of each frame picture in the video content;
determining current content information to be promoted based on the biological clock stage attribute information of the user, implanting the content information to be promoted into the target frame picture, and playing a frame picture behind the target frame picture by taking the target frame picture as a first frame.
2. The method of claim 1, further comprising:
acquiring the moment of reference behavior generated by the current user in the current biological clock cycle, and determining the fluctuation characteristic of the reference behavior based on the fluctuation of the moment of the reference behavior compared with the fluctuation of the moment in the historical biological clock cycle;
and determining the fluctuated current biological clock cycle and the predicted time of each behavior in the fluctuated current biological clock cycle according to the fluctuation characteristics of the reference behavior generated by the current user.
3. The method of claim 2, wherein determining the fluctuated current biological clock cycle and the predicted time of each behavior in the fluctuated current biological clock cycle according to the fluctuation characteristics of the current user-generated reference behavior comprises:
determining the fluctuation direction and amplitude of the current biological clock cycle after fluctuation by combining the relation direction of the reference behavior and the operation for triggering the video content request and the fluctuation direction and amplitude of the reference behavior;
and adjusting the current biological clock cycle and the predicted time of each action in the fluctuated current biological clock cycle according to the fluctuation direction and amplitude of the fluctuated current biological clock cycle.
4. The method of claim 2, wherein the biological clock phase attribute information is a predicted time of day of the respective behavior in a current biological clock cycle after the fluctuation.
5. The method of claim 1, wherein the screening target video content from the plurality of video content matched with the biological clock stage attribute information comprises:
determining the last video content played by the current user, and determining the playback frequency of the last video content according to the collected playing result data;
if the playback frequency is smaller than a threshold value, determining target video content provided for the current user in the same type of video of the previous video content; and if the playback times are larger than a threshold value, determining the target video content provided for the current user in the heterogeneous video of the previous video content.
6. The method according to claim 1, wherein the invoking the frame screening model to select a target frame from the target video content by using the self-attribute information of the current user, the operation duration for triggering the video content request, and the playing amount of each frame in the video content comprises:
selecting a target frame picture by combining the self attribute information of the current user and the playing amount of each frame picture in the video content;
and determining urgent attribute information of the current user according to the operation duration, and adjusting a target frame picture used as a first frame based on the urgent attribute information.
7. The method of claim 1, further comprising:
and generating a frame image playing curve according to the playing result data of the target video content, and displaying the frame image playing curve and the operation assembly, wherein the vertical axis of the playing curve is the playing amount of each frame image, so that a user can select the frame image to be played by adjusting the operation assembly.
8. The utility model provides an intelligence marketing popularization device which characterized in that includes:
the biological clock model module is used for acquiring various behaviors and behavior time of a sample user, identifying time fluctuation relations among different behaviors, and constructing a biological clock fluctuation model based on the various behaviors, the behavior time and the time fluctuation relations of the sample user;
the target video module responds to the video content request of the current user and searches the target video content, and comprises:
the target frame module is used for acquiring data of sample users, and constructing and training a frame picture screening model in a supervised learning mode;
the promotion module is used for determining the current content information to be promoted based on the biological clock stage attribute information of the user and implanting the content information to be promoted into the target frame picture;
and playing the frame picture behind the target frame picture by taking the target frame picture as a first frame.
9. An electronic device, wherein the electronic device comprises:
a processor; and a memory storing computer-executable instructions that, when executed, cause the processor to perform the method of any of claims 1-7.
10. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the method of any of claims 1-7.
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