CN117459798A - Big data-based information display method, device, equipment and storage medium - Google Patents
Big data-based information display method, device, equipment and storage medium Download PDFInfo
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Abstract
The application relates to a big data-based information presentation method, a big data-based information presentation device, a big data-based information presentation computer device, a big data-based information presentation storage medium and a big data-based information presentation computer program product. The method comprises the following steps: acquiring corresponding historical recommendation elements based on the user identity information and pushing corresponding recommendation videos based on the historical recommendation elements; acquiring feedback information of a recommended video; if the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity, the recommended video is set as the verification video; acquiring videos with video playing time longer than preset average playing time and video playing integrity longer than preset average playing integrity, and setting the videos as comparison videos; and if the comparison video and the verification video do not belong to similar videos, pushing and displaying the corresponding recommended video according to the comparison video. The method and the device can respond to the demands of the user rapidly and conveniently, so that the matching degree of the demands of the user and the video content is improved.
Description
Technical Field
The present disclosure relates to the field of big data technologies, and in particular, to an information display method, apparatus, device, and storage medium based on big data.
Background
Along with the development of big data and network age, the information pushing aiming at users gradually evolves from the traditional exclusive manual pushing to the intelligent and informationized angle, and along with the development of intelligent AI, an information pushing party can directionally push the demand content of the users aiming at the personal information disclosed by the users and the interests of the users.
The existing information pushing carries out relevant pushing by acquiring personal information disclosed by a user and the interest field set by the user, and meanwhile, the pushing content is further optimized by a feedback result corresponding to the pushing content, so that the accurate pushing of the user demand content is finally realized.
However, in the pushing of the existing information content, there is a situation that the user demand and the video content are not matched, but the user does not stop the pushing of the video due to subjective factors, so that the system mistakenly pushes the related video content, and then the watching experience of the client is affected, so that the user demand and the video content are poorly matched; for example, in the recommendation of the algorithm, the related videos of the well-related B members are pushed based on the personal relationship of the A members, and the user does not directly reject the push based on the relationship of the A members when receiving the videos of the B members for the first time, so that the subsequent system can push the videos of the B members at the same time, but the user only wants to pay attention to the A members, and then the user watching experience is poor.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a big data based information presentation method, apparatus, computer device, computer readable storage medium, and computer program product that can accurately match user requirements with video content.
In a first aspect, the present application provides an information display method based on big data. The method comprises the following steps:
acquiring corresponding historical recommendation elements based on the user identity information and pushing corresponding recommendation videos based on the historical recommendation elements;
acquiring feedback information of recommended videos, wherein the feedback information at least comprises video playing time, video playing integrity, video watching times and the like;
if the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity, the recommended video is set as the verification video;
acquiring videos with video playing time longer than preset average playing time and video playing integrity longer than preset average playing integrity, and setting the videos as comparison videos;
and if the comparison video and the verification video do not belong to similar videos, pushing and displaying the corresponding recommended videos according to the comparison video, wherein the similar videos are videos containing the same recommended elements.
In one embodiment, the pushing and displaying the corresponding recommended video according to the comparison video includes:
acquiring comparison videos and identifying voice information based on the comparison videos;
matching corresponding voice elements in a preset element library based on voice information, wherein different voice elements and voice keywords corresponding to the voice elements are stored in the element library;
comparing the voice element with the recommended element, and if the voice element and the recommended element belong to similar elements, pushing and displaying the corresponding recommended video according to the recommended video;
if the voice element and the recommended element do not belong to similar elements, the corresponding recommended video is pushed and displayed according to the comparison.
In one embodiment, before the step of acquiring the corresponding historical recommendation element based on the user identity information and pushing the corresponding recommended video based on the historical recommendation element, the method further includes:
acquiring login area information based on user identity information;
acquiring historical login area information;
if the login area information is different from the history login area information, acquiring a recommendation history area corresponding to the history recommendation element;
when the login area information is matched with the recommendation history area, acquiring a history recommendation element corresponding to the recommendation history area and pushing a corresponding recommendation video according to the history recommendation element.
In one embodiment, a user shared video is acquired;
extracting sharing recommendation elements according to the sharing video of the user;
pushing the corresponding recommended video according to the sharing recommended element;
obtaining the sharing time corresponding to the video shared by the user;
if the sharing time corresponding to the user sharing video is within the preset standard sharing time range, sending and displaying the recommended video corresponding to the sharing recommended element;
and if the sharing time corresponding to the user sharing video is out of the preset standard sharing time range, sending and displaying the recommended video corresponding to the history recommended element.
In one embodiment, different sharing users and corresponding sharing times are counted;
setting the longest sharing time corresponding to the sharing user as a target sharing time;
setting the target sharing time as standard sharing time corresponding to the sharing user and replacing a corresponding standard sharing time range;
and when the video playing time of the recommended video corresponding to the sharing recommended element is lower than the preset standard video playing time or the video playing integrity is lower than the preset standard video playing integrity, sending and displaying the recommended video corresponding to the historical recommended element.
In one embodiment, the sending and displaying the recommended video corresponding to the historical recommended element further includes:
counting chat frequencies corresponding to sharing users, wherein the chat frequencies are times in preset time when video playing time of recommended videos corresponding to sharing recommendation elements is higher than preset standard video playing time and video playing integrity is higher than preset standard video playing integrity;
if the chat frequency is greater than the preset standard chat frequency, transmitting and displaying the recommended video corresponding to the sharing recommended element;
if the chat frequency is not greater than the preset standard chat frequency, counting the effective communication times corresponding to the chat frequency, wherein the effective communication times are times that the chat frequency does not drop in the preset time;
if the effective communication times are greater than the preset standard communication times, transmitting and displaying the recommended video corresponding to the sharing recommended element;
and if the effective communication times are not more than the preset standard communication times, transmitting and displaying the recommended video corresponding to the history recommended element.
In a second aspect, the application also provides an information display device based on big data. The device comprises:
acquiring corresponding historical recommendation elements based on the user identity information and pushing corresponding recommendation videos based on the historical recommendation elements;
Acquiring feedback information of recommended videos, wherein the feedback information at least comprises video playing time, video playing integrity, video watching times and the like;
if the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity, the recommended video is set as the verification video;
acquiring videos with video playing time longer than preset average playing time and video playing integrity longer than preset average playing integrity, and setting the videos as comparison videos;
and if the comparison video and the verification video do not belong to similar videos, pushing and displaying the corresponding recommended videos according to the comparison video, wherein the similar videos are videos containing the same recommended elements.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:
acquiring corresponding historical recommendation elements based on the user identity information and pushing corresponding recommendation videos based on the historical recommendation elements;
acquiring feedback information of recommended videos, wherein the feedback information at least comprises video playing time, video playing integrity, video watching times and the like;
If the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity, the recommended video is set as the verification video;
acquiring videos with video playing time longer than preset average playing time and video playing integrity longer than preset average playing integrity, and setting the videos as comparison videos;
and if the comparison video and the verification video do not belong to similar videos, pushing and displaying the corresponding recommended videos according to the comparison video, wherein the similar videos are videos containing the same recommended elements.
In a fourth aspect, the present application also provides a computer-readable storage medium. A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring corresponding historical recommendation elements based on the user identity information and pushing corresponding recommendation videos based on the historical recommendation elements;
acquiring feedback information of recommended videos, wherein the feedback information at least comprises video playing time, video playing integrity, video watching times and the like;
if the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity, the recommended video is set as the verification video;
Acquiring videos with video playing time longer than preset average playing time and video playing integrity longer than preset average playing integrity, and setting the videos as comparison videos;
and if the comparison video and the verification video do not belong to similar videos, pushing and displaying the corresponding recommended videos according to the comparison video, wherein the similar videos are videos containing the same recommended elements.
In a fifth aspect, the present application also provides a computer program product. Computer program product comprising a computer program which, when executed by a processor, realizes the steps of:
acquiring corresponding historical recommendation elements based on the user identity information and pushing corresponding recommendation videos based on the historical recommendation elements;
acquiring feedback information of recommended videos, wherein the feedback information at least comprises video playing time, video playing integrity, video watching times and the like;
if the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity, the recommended video is set as the verification video;
acquiring videos with video playing time longer than preset average playing time and video playing integrity longer than preset average playing integrity, and setting the videos as comparison videos;
And if the comparison video and the verification video do not belong to similar videos, pushing and displaying the corresponding recommended videos according to the comparison video, wherein the similar videos are videos containing the same recommended elements.
The information display method, the information display device, the computer equipment, the storage medium and the computer program product based on big data acquire corresponding historical recommendation elements based on user identity information and push corresponding recommendation videos based on the historical recommendation elements; acquiring feedback information of recommended videos, wherein the feedback information at least comprises video playing time, video playing integrity, video watching times and the like; if the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity, the recommended video is set as the verification video; acquiring videos with video playing time longer than preset average playing time and video playing integrity longer than preset average playing integrity, and setting the videos as comparison videos; and if the comparison video and the verification video do not belong to similar videos, pushing and displaying the corresponding recommended videos according to the comparison video, wherein the similar videos are videos containing the same recommended elements. According to the method, the historical recommended elements of the user are positioned according to the identity information of the user, the corresponding recommended videos are pushed according to the historical recommended elements, meanwhile, the satisfaction degree of the recommended videos is directly monitored according to the feedback information of the recommended videos, under the condition that the pushed videos do not meet the user requirements, the recommended elements corresponding to the recommended videos required by the user are obtained at the first time, then the corresponding recommended videos are pushed and displayed according to the required elements of the user, the requirements of the user can be responded quickly and conveniently, and accordingly the matching degree of the user requirements and video content is improved.
Drawings
FIG. 1 is an application environment diagram of a big data based information presentation method in one embodiment;
FIG. 2 is a flow diagram of a big data based information presentation method in one embodiment;
FIG. 3 is a flow chart of an embodiment of a push of an alignment video and a recommendation video;
FIG. 4 is a flow diagram of pushing different recommended videos based on a login area in one embodiment;
FIG. 5 is a flow chart of pushing shared video according to user communication in one embodiment;
FIG. 6 is a flowchart of how to accurately determine whether to push a shared video or a historical video in one embodiment;
FIG. 7 is a flow chart of feedback information anomalies for shared video in one embodiment;
FIG. 8 is a block diagram of the information presentation device based on big data in one embodiment;
FIG. 9 is an internal block diagram of a computer device in one embodiment;
fig. 10 is an internal structural view of a computer device in another embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The big data-based information display method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the terminal communicates with the server through a network. The data storage system may store data that the server needs to process. The data storage system may be integrated on a server or may be placed on a cloud or other network server. The terminal can be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things equipment and portable wearable equipment, and the internet of things equipment can be smart speakers, smart televisions, smart air conditioners, smart vehicle-mounted equipment and the like. The portable wearable device may be a smart watch, smart bracelet, headset, or the like. The server may be implemented as a stand-alone server or as a server cluster composed of a plurality of servers.
In one embodiment, as shown in fig. 2, the method is illustrated as applied to the terminal in fig. 1, and it is understood that the method may also be applied to a server, and may also be applied to a system including the terminal and the server, and implemented through interaction between the terminal and the server. In this embodiment, the video may be recommended based on the user, or other forms of information may be recommended based on the user, where no excessive limitation is made, and the method includes the following steps:
Step 202, acquiring corresponding historical recommendation elements based on the user identity information and pushing corresponding recommendation videos based on the historical recommendation elements.
The method comprises the steps that a user firstly sends user identity information through a terminal, a server receives the user identity information sent by the user, verifies the user identity information and obtains a history recommendation element corresponding to the user identity information, wherein the history recommendation element is extracted from a history recommendation video.
It is worth mentioning that when the user identity information is a new user, that is, the user identity information has no history recommendation element, the video category information of the recommended video is pushed, after the user selects one or more pieces of video category information of interest, the server classifies the video category information according to the video category information of interest uploaded by the user, and sequentially pushes the high-quality users corresponding to the video category information, wherein the high-quality users are users with the interest proportion being greater than the preset proportion in the corresponding video category information, and if the users pay close attention to the high-quality users, the video information of the high-quality users is pushed mainly and similar videos are pushed in an auxiliary manner; if the video playing time and the video playing integrity of the video of the high-quality user by the user are lower than the preset threshold, pushing the video information of the related field. Through the secondary positioning of the initial user, whether the initial user has larger requirements on video categories or high-quality user requirements in the video categories aiming at the interest are rapidly distinguished, so that the matching degree of the user requirements and video pushing is further improved.
Step 204, obtaining feedback information of the recommended video.
The feedback information at least comprises video playing time, video playing integrity, video watching times and the like, and the server acquires the feedback information such as the video playing time, the video playing integrity, the video watching times and the like of the recommended video in real time after pushing the recommended video.
In step 206, if the video playing time is less than the preset average playing time and the video playing integrity is less than the preset average playing integrity, the recommended video is set as the verification video.
The server compares the video playing time with a preset average playing time and the video playing integrity with a preset average playing integrity respectively, and if the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity, the recommended video is set as the verification video.
Step 208, obtaining a video with a video playing time greater than a preset average playing time and a video playing integrity greater than a preset average playing integrity, and setting the video as a comparison video.
And if the comparison video and the verification video do not belong to similar videos, pushing and displaying the corresponding recommended videos according to the comparison video, wherein the similar videos are videos containing the same recommended elements.
According to the information display method based on big data, the historical recommended elements of the user are positioned according to the identity information of the user, the corresponding recommended videos are directly pushed according to the historical recommended elements, meanwhile, the satisfaction degree of the recommended videos is directly monitored according to the feedback information of the recommended videos, under the condition that the pushed videos do not meet the user requirements, the recommended elements corresponding to the recommended videos required by the user are obtained at the first time, then the corresponding recommended videos are directly pushed according to the requirement elements of the user and displayed, the requirements of the user can be responded quickly and conveniently, and accordingly the matching degree of the user requirements and the video content is improved.
In one embodiment, as shown in fig. 3, pushing and presenting the corresponding recommended video according to the comparison includes:
step 302, a comparison video is obtained and voice information is recognized based on the comparison video.
Step 304, matching corresponding voice elements in a preset element library based on the voice information.
Wherein, the element library stores different voice elements and voice keywords corresponding to the voice elements.
Step 306, the voice element is compared with the recommended element.
If the voice element and the recommended element belong to similar elements, pushing and displaying the corresponding recommended video according to the recommended video; if the voice element and the recommended element do not belong to similar elements, the corresponding recommended video is pushed and displayed according to the comparison.
In one embodiment, as shown in fig. 4, before the step of acquiring the corresponding historical recommendation element based on the user identity information and pushing the corresponding recommended video based on the historical recommendation element, the method further includes:
step 402, acquiring login area information and historical login area information based on user identity information.
Step 404, it is determined whether the login area information is the same as the history login area information.
If the login area information is different from the history login area information, acquiring a recommendation history area corresponding to the history recommendation element; and if the login area information is matched with the recommendation history area, acquiring a history recommendation element corresponding to the recommendation history area and pushing a corresponding recommendation video according to the history recommendation element.
In one embodiment, as shown in fig. 5, during the communication process, the user changes the video requirement according to the communication requirement, and then, how to respond to the video requirement conversion of the user quickly according to the sharing video during the communication process, the specific response process may be executed as follows:
step 502, extracting a sharing recommendation element according to the user sharing video.
When the server monitors that feedback information of a user initiating video sharing operation or recommending video is abnormal, the video playing time is lower than a preset standard playing time; and the video playing integrity is lower than the preset standard playing integrity, and the like, the shared video of the user is obtained, and the corresponding sharing recommendation element is extracted according to the shared video.
Step 504, pushing the corresponding recommended video according to the sharing recommended element.
The server inquires corresponding recommended videos in the recommendation library according to the acquired sharing recommended elements and performs pushing operation.
Step 506, obtaining a sharing time corresponding to the video shared by the user.
If the sharing time corresponding to the user sharing video is within a preset standard sharing time range, sending and displaying the recommended video corresponding to the sharing recommended element; and if the sharing time corresponding to the user sharing video is out of the preset standard sharing time range, sending and displaying the recommended video corresponding to the history recommended element.
In this embodiment, through the sharing operation or abnormal feedback information of the user, the server may push the sharing video required by the user at the first time, and may simultaneously push the recommended video required by the user after the communication is finished at the first time according to the sharing time corresponding to the sharing video of the user, so as to improve the matching degree between the user requirement and the sharing video in the process of communicating with the user.
In one embodiment, as shown in fig. 6, since the sharing frequency between different users is different, in the determining for different users how to accurately push the shared video or push the history video, the determining process includes:
Step 602, different sharing users and corresponding sharing times are counted.
The server acquires all corresponding sharing times according to different sharing users respectively, and if the users do not share the video, the server directly sends prompt information of the users which do not share the video; if the sharing user comprises a plurality of sharing times, counting all the sharing times; it is worth mentioning that staff can carry out screening operation through setting up the sharing frequency that the sharing user corresponds for the server can only be to chat frequency up to standard user just carry out the recommendation operation of sharing video.
In step 604, the longest sharing time corresponding to the sharing user is set as the target sharing time.
After counting the sharing time corresponding to the sharing user, the server sets the longest sharing time as a target sharing time, sets the target sharing time as a standard sharing time corresponding to the sharing user, and replaces a corresponding standard sharing time range.
For example, for the sharing user a, the corresponding sharing time is 2min, 5min, and 10min, and then 10min is set as the standard sharing time corresponding to the sharing user, that is, after the sharing video is pushed to the sharing user a, the standard sharing time ranges of the sharing user a are all within the range of 10 min.
Step 606, the video playing time and the video playing integrity of the recommended video are respectively compared with preset standard values.
The preset standard value is preset standard video playing time and preset standard video playing integrity, and if the video playing time of the recommended video corresponding to the sharing recommended element is lower than the preset standard video playing time or the video playing integrity is lower than the preset standard video playing integrity, the recommended video corresponding to the historical recommended element is sent and displayed.
In the embodiment, the feedback information of the shared video is monitored together by the video playing time of the shared video or the video playing integrity of the shared video, and the time occupation ratio of the chat in the video sharing process is considered to be smaller than the video requirement of the user, so that the feedback information of the shared video is monitored in a mode of OR, and the recommended video corresponding to the history recommended element is further promoted when the user returns to the self video requirement after the shared video is finished.
In one embodiment, as shown in fig. 7, in the process of sharing video by the user, there is a situation that the sharing object has seen the sharing video, so that feedback information of the sharing video is lower than a preset standard value, and correction needs to be performed for the situation that feedback information of the sharing video is abnormal due to false triggering, and specific corrective measures may be executed as follows:
Step 702, statistics is performed on chat frequencies corresponding to the sharing users.
The chat frequency is the number of times that the video playing time of the recommended video corresponding to the sharing recommended element is higher than the preset standard video playing time and the video playing integrity is higher than the preset standard video playing integrity in the preset time.
Step 704, comparing the chat frequency with a preset chat frequency.
If the chat frequency is greater than the preset standard chat frequency, sending and displaying the recommended video corresponding to the shared recommended element; if the chat frequency is not greater than the preset standard chat frequency, counting the effective communication times corresponding to the chat frequency, wherein the effective communication times are times that the chat frequency does not drop in the preset time.
Step 706, comparing the effective communication times with the preset standard communication times.
If the effective communication times are greater than the preset standard communication times, sending and displaying the recommended video corresponding to the shared recommended element; and if the effective communication times are not more than the preset standard communication times, transmitting and displaying the recommended video corresponding to the history recommended element.
In this embodiment, through secondary screening of the chat frequency and the effective communication frequency, firstly, users meeting the chat communication frequency are screened out, so that the server continues to push the sharing video corresponding to the sharing element under the condition that feedback information of the users meeting the chat frequency is abnormal; on the basis that the chat frequency does not reach the standard, the monitoring of the effective communication times can be further increased, so that the server can screen out the abnormal situation of the feedback information of the shared video of the user with the effective communication times reaching the standard again, and the user can screen out the abnormal situation of the feedback information caused by the shared video when the sharing object has seen the shared video, thereby indirectly improving the matching degree of the user requirement and the recommended video.
According to the method, the corresponding recommended video is positioned to the historical recommended elements of the user according to the identity information of the user, the corresponding recommended video is directly pushed according to the historical recommended elements, meanwhile, the satisfaction degree of the recommended video is directly monitored according to the feedback information of the recommended video, under the condition that the pushed video does not meet the user requirement, the recommended elements corresponding to the recommended video required by the user are obtained at the first time, then the corresponding recommended video is directly pushed according to the requirement elements of the user and displayed, the requirement of the user can be responded quickly and conveniently, and accordingly the matching degree of the user requirement and the video content is improved.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these 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 some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of 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 is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a big data-based information display device for realizing the above mentioned big data-based information display method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the information display device based on big data provided below may refer to the limitation of the information display method based on big data hereinabove, and will not be repeated herein.
In one embodiment, as shown in fig. 8, there is provided an information presentation apparatus based on big data, including: the system comprises a history recommendation element acquisition module, a video feedback information acquisition module, a verification video setting module, a comparison video setting module and a recommendation video display module, wherein:
the history recommendation element acquisition module is used for acquiring corresponding history recommendation elements based on the user identity information and pushing corresponding recommendation videos based on the history recommendation elements;
the video feedback information acquisition module is used for acquiring feedback information of the recommended video, wherein the feedback information at least comprises video playing time, video playing integrity, video watching times and the like;
The verification video setting module is used for setting the recommended video as the verification video if the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity;
the comparison video setting module is used for obtaining videos with video playing time being longer than preset average playing time and video playing integrity being longer than preset average playing integrity and setting the videos as comparison videos;
and the recommended video display module is used for pushing and displaying the corresponding recommended video according to the comparison video if the comparison video and the verification video do not belong to the similar video, wherein the similar video is a video containing the same recommended element.
In one embodiment, the recommended video presentation module is further to: acquiring comparison videos and identifying voice information based on the comparison videos; matching corresponding voice elements in a preset element library based on voice information, wherein different voice elements and voice keywords corresponding to the voice elements are stored in the element library; comparing the voice element with the recommended element, and if the voice element and the recommended element belong to similar elements, pushing and displaying the corresponding recommended video according to the recommended video; if the voice element and the recommended element do not belong to similar elements, the corresponding recommended video is pushed and displayed according to the comparison.
In one embodiment, the history recommended element acquisition module is further configured to: acquiring login area information based on user identity information; acquiring historical login area information; if the login area information is different from the history login area information, acquiring a recommendation history area corresponding to the history recommendation element; when the login area information is matched with the recommendation history area, acquiring a history recommendation element corresponding to the recommendation history area and pushing a corresponding recommendation video according to the history recommendation element.
In one embodiment, the shared video push module is further configured to: acquiring a user sharing video; extracting sharing recommendation elements according to the sharing video of the user; pushing the corresponding recommended video according to the sharing recommended element; obtaining the sharing time corresponding to the video shared by the user; if the sharing time corresponding to the user sharing video is within the preset standard sharing time range, sending and displaying the recommended video corresponding to the sharing recommended element; and if the sharing time corresponding to the user sharing video is out of the preset standard sharing time range, sending and displaying the recommended video corresponding to the history recommended element.
In one embodiment, the shared video push module is further configured to: different sharing users and corresponding sharing time are counted; setting the longest sharing time corresponding to the sharing user as a target sharing time; setting the target sharing time as standard sharing time corresponding to the sharing user and replacing a corresponding standard sharing time range; and when the video playing time of the recommended video corresponding to the sharing recommended element is lower than the preset standard video playing time or the video playing integrity is lower than the preset standard video playing integrity, sending and displaying the recommended video corresponding to the historical recommended element.
In one embodiment, the shared video push module is further configured to: the sending and displaying of the recommended video corresponding to the historical recommended element further comprises: counting chat frequencies corresponding to sharing users, wherein the chat frequencies are times in preset time when video playing time of recommended videos corresponding to sharing recommendation elements is higher than preset standard video playing time and video playing integrity is higher than preset standard video playing integrity; if the chat frequency is greater than the preset standard chat frequency, transmitting and displaying the recommended video corresponding to the sharing recommended element; if the chat frequency is not greater than the preset standard chat frequency, counting the effective communication times corresponding to the chat frequency, wherein the effective communication times are times that the chat frequency does not drop in the preset time; if the effective communication times are greater than the preset standard communication times, transmitting and displaying the recommended video corresponding to the sharing recommended element; and if the effective communication times are not more than the preset standard communication times, transmitting and displaying the recommended video corresponding to the history recommended element.
The above-described modules in the big data based information presentation apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 9. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a big data based information presentation method.
In one embodiment, a computer device is provided, which may be a terminal, and an internal structure diagram thereof may be as shown in fig. 10. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program, when executed by a processor, implements a big data based information presentation method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 10 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method embodiments described above.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
It should be noted that, user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (9)
1. An information display method based on big data, which is characterized by comprising the following steps:
acquiring corresponding historical recommendation elements based on the user identity information and pushing corresponding recommendation videos based on the historical recommendation elements;
acquiring feedback information of recommended videos, wherein the feedback information at least comprises video playing time, video playing integrity, video watching times and the like;
If the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity, the recommended video is set as the verification video;
acquiring videos with video playing time longer than preset average playing time and video playing integrity longer than preset average playing integrity, and setting the videos as comparison videos;
if the comparison video and the verification video do not belong to similar videos, pushing and displaying the corresponding recommended videos according to the comparison video, wherein the similar videos are videos containing the same recommended elements;
acquiring comparison videos and identifying voice information based on the comparison videos;
matching corresponding voice elements in a preset element library based on voice information, wherein different voice elements and voice keywords corresponding to the voice elements are stored in the element library;
comparing the voice element with the recommended element, and if the voice element and the recommended element belong to similar elements, pushing and displaying the corresponding recommended video according to the recommended video;
if the voice element and the recommended element do not belong to similar elements, the corresponding recommended video is pushed and displayed according to the comparison.
2. The method of claim 1, further comprising, prior to the obtaining the corresponding historical recommendation element based on the user identity information and pushing the corresponding recommended video based on the historical recommendation element:
acquiring login area information based on user identity information;
acquiring historical login area information;
if the login area information is different from the history login area information, acquiring a recommendation history area corresponding to the history recommendation element;
when the login area information is matched with the recommendation history area, acquiring a history recommendation element corresponding to the recommendation history area and pushing a corresponding recommendation video according to the history recommendation element.
3. The method according to claim 1, wherein the method further comprises:
acquiring a user sharing video;
extracting sharing recommendation elements according to the sharing video of the user;
pushing the corresponding recommended video according to the sharing recommended element;
obtaining the sharing time corresponding to the video shared by the user;
if the sharing time corresponding to the user sharing video is within the preset standard sharing time range, sending and displaying the recommended video corresponding to the sharing recommended element;
and if the sharing time corresponding to the user sharing video is out of the preset standard sharing time range, sending and displaying the recommended video corresponding to the history recommended element.
4. A method according to claim 3, characterized in that the method further comprises:
different sharing users and corresponding sharing time are counted;
setting the longest sharing time corresponding to the sharing user as a target sharing time;
setting the target sharing time as standard sharing time corresponding to the sharing user and replacing a corresponding standard sharing time range;
and when the video playing time of the recommended video corresponding to the sharing recommended element is lower than the preset standard video playing time or the video playing integrity is lower than the preset standard video playing integrity, sending and displaying the recommended video corresponding to the historical recommended element.
5. The method of claim 4, wherein the sending and presenting the recommended video corresponding to the historical recommendation element further comprises:
counting chat frequencies corresponding to sharing users, wherein the chat frequencies are times in preset time when video playing time of recommended videos corresponding to sharing recommendation elements is higher than preset standard video playing time and video playing integrity is higher than preset standard video playing integrity;
if the chat frequency is greater than the preset standard chat frequency, transmitting and displaying the recommended video corresponding to the sharing recommended element;
If the chat frequency is not greater than the preset standard chat frequency, counting the effective communication times corresponding to the chat frequency, wherein the effective communication times are times that the chat frequency does not drop in the preset time;
if the effective communication times are greater than the preset standard communication times, transmitting and displaying the recommended video corresponding to the sharing recommended element;
and if the effective communication times are not more than the preset standard communication times, transmitting and displaying the recommended video corresponding to the history recommended element.
6. An information presentation apparatus based on big data, the apparatus comprising:
the history recommendation element acquisition module is used for acquiring corresponding history recommendation elements based on the user identity information and pushing corresponding recommendation videos based on the history recommendation elements;
the video feedback information acquisition module is used for acquiring feedback information of the recommended video, wherein the feedback information at least comprises video playing time, video playing integrity, video watching times and the like;
the verification video setting module is used for setting the recommended video as the verification video if the video playing time is smaller than the preset average playing time and the video playing integrity is smaller than the preset average playing integrity;
The comparison video setting module is used for obtaining videos with video playing time being longer than preset average playing time and video playing integrity being longer than preset average playing integrity and setting the videos as comparison videos;
and the recommended video display module is used for pushing and displaying the corresponding recommended video according to the comparison video if the comparison video and the verification video do not belong to the similar video, wherein the similar video is a video containing the same recommended element.
7. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 5 when the computer program is executed.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 5.
9. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 5.
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