Media content analysis method and device, equipment, storage medium and program product

Abstract

The invention relates to the technical field of data processing, and discloses a media content analysis method and device, equipment, a storage medium and a program product.The method comprises the steps that in response to interaction operation in an analysis condition area of an analysis page, a target analysis condition and target media content meeting the target analysis condition are determined, the target media content is associated with the target demander; the target media content and a search analysis result corresponding to the target media content are displayed in the analysis page, the search analysis result is obtained after statistical analysis is conducted on search data obtained after the target media content is displayed, and the search data is related to a target demand side; the search data comprises at least one of search terms and search results of the search terms. The problem that it is difficult to determine the media content recommendation effect can be solved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of data processing, and particularly to a method, apparatus, device, storage medium, and program product for media content analysis. Background Art

[0002] With the rapid development of media applications, more and more demanders (such as brand owners) begin to use media content to showcase the features of brands or products, so that the outside world can better understand the brands or products. However, in the process of media content recommendation, it is difficult to determine the recommendation effect of media content. Summary of the Invention

[0003] In view of this, the present disclosure provides a method, apparatus, device, storage medium, and program product for media content analysis to solve the problem of difficult determination of the recommendation effect of media content.

[0004] In a first aspect, the present disclosure provides a method for media content analysis, the method comprising:

[0005] responding to an interaction operation in an analysis condition area of an analysis page to determine a target analysis condition and target media content that meets the target analysis condition, the target media content being associated with a target demander;

[0006] displaying the target media content and a search analysis result corresponding to the target media content in the analysis page, the search analysis result being obtained by performing statistical analysis on search data obtained after the target media content is displayed, the search data being related to the target demander, and the search data including at least one of a search term and search results of the search term.

[0007] In a second aspect, the present disclosure provides a device for media content analysis, the device comprising:

[0008] an interaction module, configured to respond to an interaction operation in an analysis condition area of an analysis page to determine a target analysis condition and target media content that meets the target analysis condition, the target media content being associated with a target demander;

[0009] a display module, configured to display the target media content and a search analysis result corresponding to the target media content in the analysis page, the search analysis result being obtained by performing statistical analysis on search data obtained after the target media content is displayed, the search data being related to the target demander, and the search data including at least one of a search term and search results of the search term.

[0010] In a third aspect, the present disclosure provides an electronic device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the media content analysis method according to the first aspect or any corresponding embodiment thereof.

[0011] In a fourth aspect, the present disclosure provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to perform the media content analysis method according to the first aspect or any corresponding embodiment thereof.

[0012] In a fifth aspect, the present disclosure provides a computer program product, including computer instructions, and the computer instructions are used to cause a computer to perform the media content analysis method according to the first aspect or any corresponding embodiment thereof.

[0013] The media content analysis method provided by the embodiments of the present disclosure displays the search analysis result corresponding to the target media content while displaying the target media content. Among them, the search analysis result is obtained by statistically analyzing the search data obtained after displaying the target media content. Therefore, in the process of recommending the target media content, the search analysis result can be used to reflect the recommendation effect of the target media content, so as to adjust the recommendation method of the target media content according to the recommendation effect, thereby effectively improving the recommendation effect of the target media content. In addition, the search data used for statistical analysis includes not only search terms but also the search results of the search terms. Therefore, in the case where the search terms do not contain information about the target requester, the relevance between the search results of the search terms and the target requester can be used to supplement the search data related to the target requester, thereby improving the accuracy of the search analysis result and enabling the search analysis result to more accurately reflect the recommendation effect of the target media content.

[0014] Regarding the beneficial effects of the media content analysis device, electronic device, storage medium, and program product, they correspond to the beneficial effects of the media content analysis method and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the specific embodiments of the present disclosure or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 is a flowchart of a media content analysis method according to an embodiment of the present disclosure;

[0017] Figure 2 It is a schematic diagram of an analysis page according to an embodiment of the present disclosure;

[0018] Figure 3 It is a flowchart of a method for determining a search analysis result according to an embodiment of the present disclosure;

[0019] Figure 4 It is a flowchart of another media content analysis method according to an embodiment of the present disclosure;

[0020] Figure 5 It is a structural block diagram of a media content analysis device according to an embodiment of the present disclosure;

[0021] Figure 6 It is a structural block diagram of an electronic device according to an embodiment of the present disclosure. Detailed implementation manners

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present disclosure without creative efforts shall fall within the protection scope of the present disclosure.

[0023] It can be understood that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, usage scopes, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0024] For example, when receiving a user's active request, a prompt message is sent to the user to clearly prompt the user that the operation requested by the user will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, an application program, a server, or a storage medium that executes the operations of the technical solutions of the present disclosure according to the prompt message.

[0025] As an optional but non-limiting implementation manner, the manner of sending a prompt message to the user in response to receiving the user's active request may be, for example, a pop-up window manner, and the prompt message may be presented in text in the pop-up window. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0026] It can be understood that the above process of notifying and obtaining the user's authorization is only illustrative and does not limit the implementation manners of the present disclosure. Other manners that meet relevant laws and regulations can also be applied to the implementation manners of the present disclosure.

[0027] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of the corresponding laws, regulations and relevant provisions.

[0028] With the rapid development of media applications, more and more demanders (such as brand owners) begin to use media content to showcase the features of brands or products, so that the outside world can better understand the brands or products. However, in the process of media content recommendation, it is difficult to determine the recommendation effect of media content.

[0029] In view of this, according to an embodiment of the present disclosure, an embodiment of a media content analysis method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0030] In this embodiment, a media content analysis method is provided, which can be used in electronic devices such as computers, mobile terminals, etc. Figure 1 is a flowchart of a media content analysis method according to an embodiment of the present disclosure, as Figure 1 shown, the process includes the following steps:

[0031] Step S101, in response to an interaction operation in the analysis condition area of the analysis page, determine the target analysis condition and the target media content that meets the target analysis condition, and the target media content is associated with the target demander.

[0032] Specifically, configuration controls for at least one analysis condition are displayed in the analysis condition area. Among them, at least one analysis condition includes at least one of the demander associated with the media content and the industry. The demander is a brand owner or other users who use media content to showcase their brands, products, or services. In addition, the analysis condition can also include the release time, content volume, etc. of the media content, which can be adjusted according to the actual situation.

[0033] Furthermore, in response to an interaction operation on the configuration control in the analysis condition area, determine the target analysis condition and the target media content that meets the target analysis condition.

[0034] Specifically, in addition to having the associated target demander, the target media content is also associated with information related to the analysis condition such as the industry to which it belongs.

[0035] Optionally, the target media content is a video. In addition to this, the target media content can also be media content such as pictures and articles.

[0036] Step S102: Display the target media content and the search analysis results corresponding to the target media content on the analysis page. The search analysis results are obtained through statistical analysis based on the search data acquired after the display of the target media content. The search data is related to the target requester and includes at least one of the search terms and the search results of the search terms.

[0037] Among them, the search analysis results corresponding to the target media content are related to the target requester, and these search analysis results are used to characterize the search behavior of relevant content for the target requester triggered by the target media content. For example, the search behavior for the name of the target requester, the search behavior for the products of the target requester, etc.

[0038] Specifically, the search analysis results include the analysis results of at least one search metric. Among them, at least one search metric includes at least one of the number of searches, search rate, and the number of users performing the search. The number of searches characterizes the searches triggered by the target media content, and the search results display the number of searches for the relevant content of the target requester. The search rate characterizes the ratio of the number of searches for the target media content to the number of exposures of the target media content. The number of users performing the search characterizes the number of users who search for the relevant content of the target requester due to the target media content. In addition, other search metrics can also be adopted according to the actual situation, which is not limited here.

[0039] Specifically, the search data obtained in the above step S102 is the search data for the relevant content of the target requester triggered by the display of the target media content.

[0040] Exemplarily, taking the target media content as video video1 and the target requester as brand A, and video video1 is used to introduce product1 of brand A as an example. If a certain user user1 searches for "product1" as a search term immediately after the playback of video video1 and retrieves the relevant content of product1, then the search term "product1" and the search result "the relevant content of product1" are used as the search data obtained after the display of video video1.

[0041] The media content analysis method provided in this embodiment displays the search analysis results corresponding to the target media content while displaying the target media content. Among them, the search analysis results are obtained through statistical analysis based on the search data obtained after the target media content is displayed. Therefore, in the process of recommending the target media content, the search analysis results can be used to reflect the recommendation effect of the target media content, so as to adjust the recommendation method of the target media content according to the recommendation effect, thereby effectively improving the recommendation effect of the target media content. In addition, the search data used for statistical analysis includes not only search terms but also the search results of the search terms. Therefore, in the case where the search terms do not contain information about the target requester, the relevance between the search results of the search terms and the target requester can be used to supplement the search data related to the target requester, thereby improving the accuracy of the search analysis results and enabling the search analysis results to more accurately reflect the recommendation effect of the target media content.

[0042] Exemplarily, taking the media content as a video as an example, refer to Figure 2 the analysis page shown. If the target analysis conditions input by the user through the condition analysis area are: beauty industry, brand A, released from January 1, 2025 to January 10, 2025, then the target media content that meets the target analysis conditions and the search analysis results corresponding to the target media content are displayed in the display area of the analysis page. For example, the target media content is Figure 2 the videos video1 and video2 shown. The search analysis results of video1 are that the number of searches for brand A triggered by the display of video1 is 282 times, the search rate for brand A triggered by the display of video1 is 0.03%, and the number of users who performed searches for brand A triggered by the display of video1 is 227. The search analysis results of video2 are that the number of searches for brand A triggered by the display of video2 is 625 times, the search rate for brand A triggered by the display of video2 is 0.09%, and the number of users who performed searches for brand A triggered by the display of video2 is 572 times.

[0043] In some alternative embodiments, as Figure 3 shown, the media content analysis method of the present disclosure further includes:

[0044] Step S301, obtaining first requester information associated with at least one optional media content, and second requester information associated with at least one first search data, where the target media content belongs to the optional media content, and the first search data includes the search data obtained after the optional media content is displayed.

[0045] Among them, the target media content is the optional media content that meets the target analysis conditions.

[0046] Optionally, the optional media content is a video. In addition, the optional media content can also be media content such as pictures and articles.

[0047] Optionally, the first requester information is the identifier of the requester associated with the optional media content, and the second requester information is the identifier of the requester associated with the first search data. In addition, the first requester information and the second requester information can also be information such as the name of the associated requester, which is not limited here.

[0048] Specifically, the first search data is obtained in the following way: obtain the log data of the server, and perform data extraction, transformation, and loading (Extract-Transform-Load, ETL) on the log data to obtain the first search data.

[0049] Furthermore, after the user browses the optional media content, search operations can be performed through non-manual search and manual search and other methods.

[0050] In the non-manual search method, one or more optional candidate words are displayed in the target area of the search page or the display page of the optional media content. Among them, the target area of the display page includes at least one of the top area of the comment area, the area where the comment data in the comment area is located, the related search area (located at the bottom of the page), the area where the display copywriting is located, and the area where the topic content in the comment area is located. The target area of the search page includes at least one of the area where the search control is located and the area where the recommended search content is located. Further, the optional search words include at least one of the sticky words at the top of the comment area in the top area of the comment area, the search words in the comment data, the search words in the related search area (also known as the bottom Bar words), the topic words in the display copywriting, the topic words in the topic content, the recommended search words in the search control, and the search words in the recommended search content. The user can perform a search operation by selecting the optional search words.

[0051] Furthermore, by performing point position recognition on the above target area, the optional candidate words for performing interaction after the optional media content is displayed can be determined as the first search data.

[0052] In the manual search method, the user can input a search word through the search control on the search page to perform a search. After the optional media content is displayed, in response to the search word input on the search page, the relevance between the search word and the optional media content is analyzed by a language model, and the search words related to the optional media content are used as the first search data according to the analysis result. Among them, the language model is located in the search middle platform.

[0053] Step S302: Based on the matching situation between the first requester information and the second requester information, associate the optional media content with the first search data to obtain the second search data corresponding to the optional media content. The second search data is related to the requester represented by the first requester information.

[0054] Specifically, if the first requester information is the same as the second requester information, associate the corresponding optional media content with the first search data.

[0055] It should be noted that the second search data represents the search data for the requester associated with the optional media content triggered by the display of the optional media content.

[0056] Step S303: Conduct statistical analysis on the second search data to obtain the search analysis result corresponding to the optional media content.

[0057] Specifically, conduct statistical analysis based on the second search data to obtain the analysis results of at least one search metric corresponding to the optional media content, so as to obtain the search analysis result corresponding to the optional media content. The relevant steps can refer to the description of the search analysis result corresponding to the target media content above and will not be elaborated here.

[0058] In the media content analysis method provided in this embodiment, by matching the first requester information of the optional media content and the second requester information of the first search data, determine the second search data related to the optional media content and the requester represented by the first requester information in the first search data, so as to analyze and obtain the search analysis result corresponding to the optional media content. Therefore, it can avoid misattributing the first search data unrelated to the optional media content to the optional media content, thereby accurately screening out the second search data triggered by the display of the optional media content, so as to improve the accuracy of the search analysis result. At the same time, it is also convenient to disclose the search analysis result corresponding to the target media content in real time during the subsequent analysis process.

[0059] In some optional implementation manners, obtaining the first requester information associated with at least one optional media content in step S301 above includes:

[0060] Step a1: Obtain the target identification information and the content identification of the optional media content. The target identification information is used to represent the content identification corresponding to different requesters.

[0061] Wherein, if the optional media content is a video, the content identification is the video identification.

[0062] Step a2: Determine the first requester information based on the target identification information and the content identification of the optional media content.

[0063] Among them, if the content identifier of the optional media content is consistent with the content identifier in the target identifier information, the first requester information is obtained through the requester corresponding to the consistent content identifier in the target identifier information.

[0064] In the media content analysis method provided in this embodiment, since the media application is connected to multiple data analysis links, it is difficult to carry all the information required by the data analysis link in the reported information of each optional media content. Therefore, in this embodiment, by combining the target identifier information and the content identifier of the optional media content provided by the media application in the reported information, the first requester information is determined, which can effectively reduce the difficulty of obtaining the first requester information.

[0065] In some optional implementation manners, the optional media content is used to display a product, and the optional media content and the product it displays are both associated with the same requester. The obtaining of the first requester information associated with at least one optional media content in step S301 above includes:

[0066] Step b1, based on the operation link of the display page of the optional media content, determine the target product accessed from the display page.

[0067] Specifically, the access link of the displayed product is displayed on the display page, and the product page of the displayed product can be accessed through the interaction operation with the access link. Therefore, when the optional media content is displayed on the media application, the operation link of the display page can be obtained for the continuous operations of the user on the media application. Then, the target product accessed from the display page is determined according to the operation link to determine the product displayed by the optional media content.

[0068] Step b2, obtain the requester associated with the target product to obtain the first requester information.

[0069] It can be understood that since the optional media content and the product it displays are both associated with the same requester, after the product displayed by the optional media content (i.e., the target product) is determined through the operation link, the requester associated with the optional media content can be determined through the requester associated with the target product, and then the first requester information is obtained.

[0070] It should be noted that for the same optional media content, steps a1, a2, b1, and b2 can be executed simultaneously, and the first requester information of the optional media content is determined by combining the first requester information determined by the two methods. Or, only one of the determination methods is selected to determine the first requester information of the optional media content. Or, when the first requester information cannot be determined through steps a1 and a2, the first requester information of the optional media content is determined through steps b1 and b2.

[0071] The media content analysis method provided in this embodiment determines a target product accessed from a display page by means of an operation link on the display page of optional media content, and determines first requester information according to the requesters associated with the target product. Therefore, it is possible to assist in obtaining the first requester information of the optional media content in the case where it is difficult to directly obtain the first requester information.

[0072] In some alternative embodiments, obtaining the second requester information associated with at least one first search data in step S301 includes:

[0073] Step c1, obtaining a target search term obtained after displaying optional media content.

[0074] It should be noted that the target search term includes the search term corresponding to the target media content. The manner of obtaining the target search term can refer to the manner of obtaining the first search data under the above non-manual search and manual search, and will not be elaborated here.

[0075] Step c2, determining the presence of requester information in the target search term.

[0076] Specifically, perform semantic recognition on the target search term to determine whether the target search term contains words used to represent requester information. If not, it is determined that there is no requester information in the target search term. If so, it is determined that there is requester information in the target search term.

[0077] Step c3, if there is no requester information in the target search term, obtain the search result of the target search term. The first search data includes at least one of the target search term and the search result of the target search term.

[0078] Optionally, the search result includes at least one of the searched media content and products. In addition, the search result may also include an introduction card of the requester, etc., which is not limited here.

[0079] Step c4, determining the requester associated with the search result of the target search term to obtain the second requester information.

[0080] Specifically, relevant content information of different requesters can be preset in advance, such as product information and media content information (such as content identifiers) of different requesters, and the search result is marked according to the relevant content information to determine the requester associated with the search result.

[0081] Exemplarily, taking the demand side as a brand as an example, if the target search term is "search for lipsticks", it can be determined that there is no demand side information in the target search term. At this time, the search results can be further obtained. For example, "lipsticks of brand A", then it can be determined that the search results of the target search term are associated with "brand A". Therefore, the information of "brand A" can be used as the second demand side information.

[0082] The media content analysis method provided in this embodiment further determines the second demand side information through the search results of the target search term when there is no demand side information in the target search term. Therefore, the first search data can be supplemented by the search results to further improve the accuracy of the search analysis results.

[0083] In some alternative embodiments, obtaining the second demand side information associated with at least one first search data in step S301 further includes:

[0084] Step c5, if there is demand side information in the target search term, then based on the demand side information in the target search term, determine the demand side associated with the target search term to obtain the second demand side information.

[0085] Specifically, label the target search term according to the above relevant content information to determine the demand side associated with the target search term.

[0086] Exemplarily, taking the demand side as a brand as an example, if the target search term is "search for lipsticks of brand A", it can be determined that there is demand side information in the target search term and the demand side associated with the target search term is determined to be "brand A". Therefore, the information of "brand A" can be used as the second demand side information.

[0087] The media content analysis method provided in this embodiment determines the demand side associated with the target search term through the demand side information to obtain the second demand side information when there is demand side information in the target search term. Therefore, the second demand side information can be quickly determined.

[0088] In some alternative embodiments, step S302 includes:

[0089] Step d1, based on the matching situation between the first demand side information and the second demand side information, associate the optional media content and the first search data.

[0090] Specifically, judge the consistency between the first demand side information and the second demand side information. If the first demand side information is consistent with the second demand side information, then associate the corresponding optional media content and the first search data.

[0091] Step d2, if the first search data does not meet the preset attribution stop condition, write the first search data that has not been successfully attributed into the message queue, and for the first search data in the message queue, attribute the optional media content that triggered the first search data based on the association result to obtain an attribution result.

[0092] Specifically, write the first search data that has not been successfully attributed into the Message Queue (MQ). The window for processing the first search data in the message queue, according to a preset duration (such as 5 minutes), attributes the optional media content that triggered the first search data among the associated optional media content, that is, searches for the optional media content of the last interaction before the generation of the first search data among the associated optional media content to obtain an attribution result. If the optional media content that triggered the first search data is not found within the preset duration, write the first search data back into the message queue to perform real-time loop attribution on the first search data.

[0093] Specifically, configure data collection points in the media application to collect interaction data of the optional media content to obtain interaction data of the optional media content, such as interaction time. And configure data collection points in the media application or the source of the search data to collect interaction data of the first search data to obtain interaction data of the first search data, such as search time. Then, based on the interaction data of the first search data and the interaction data of the optional media content, attribute the optional media content that triggered the first search data to obtain an attribution result.

[0094] Optionally, the preset attribution stop condition includes that the first search data is successfully attributed, and / or the number of loop attributions of the first search data (i.e., the number of times written into the message queue) reaches a preset number of times (such as 5 times). In practical applications, the preset attribution stop condition can be adjusted according to the actual situation.

[0095] Step d3, determine the second search data corresponding to the optional media content based on the attribution result.

[0096] Specifically, based on the attribution result, determine the first search data triggered by the optional media content as the second search data.

[0097] The media content analysis method provided in this embodiment, when the first search data does not meet the preset attribution stop condition, writes the first search data that has not been successfully attributed into the message queue, and attributes the optional media content that triggered the first search data based on the association result to determine the second search data corresponding to the optional media content. Therefore, it can perform loop attribution on the first search data when the first search data is not successfully attributed, and ensure the real-time nature of the attribution result.

[0098] In some alternative embodiments, the media content analysis method of the present disclosure further includes:

[0099] Step d4, if the first search data meets the preset attribution stop condition, delete the first search data that has not been successfully attributed.

[0100] For the media content analysis method provided in this embodiment, if the first search data meets the preset attribution stop condition, the first search data is deleted. Therefore, the real-time nature of the attribution result can be ensured, and at the same time, waste of computing resources can be avoided.

[0101] As one specific application example, as Figure 4 shown, the acquisition process of the second search data mainly includes the following steps: Obtain the log data of the server, perform data extraction, transformation, and loading (Extract-Transform-Load, ETL) on the log data to obtain the first search data. Obtain the first requester information of the optional media content; wherein, the first requester is obtained in real time based on the requester associated with the target product (i.e., the product accessed through the display page of the optional media content), and / or, obtained offline based on the content identifier corresponding to different requesters and the content identifier of the optional media content. And, obtain the second requester information of the first search data; wherein, the second requester information is determined based on the requester associated with the target search term (i.e., the search term obtained after the optional media content is displayed), and / or, determined based on the requester associated with the search result of the target search term. Then, based on the matching situation between the first requester information and the second requester information, associate the optional media content and the first search data to obtain the first association result. Obtain the interaction data of the first search data and the interaction data of the optional media content, and associate the interaction data of the two to obtain the second association result. Write the first search data into the message queue, and perform cyclic attribution on the first search data in the message queue through the first association result and the second association result to obtain the second search data of the optional media content.

[0102] As a specific application example, a target application is installed on a computer, and the target application is used to analyze media content such as videos. Through interaction with the target application, an analysis page is displayed in the target application. The user can input target analysis conditions in the analysis condition area of the analysis page, for example, industry, brand, video release time, etc. The target application uses the media content analysis method of the present disclosure to query videos that meet the target analysis conditions, and displays the queried videos and the search analysis results of the videos in the analysis page, for example, analysis results of search metrics such as the number of searches, search rate, and number of users who perform searches for the associated brand party caused by the display of the video. The user can determine the recommendation effect of the queried videos through the search analysis results displayed in the analysis page.

[0103] In this embodiment, a media content analysis device is further provided. This device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have been described will not be elaborated again. As used hereinafter, the term "module" may be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware is also possible and contemplated.

[0104] This embodiment provides a media content analysis device, as Figure 5 shown, including:

[0105] An interaction module 501, configured to determine a target analysis condition and target media content that meets the target analysis condition in response to an interaction operation in the analysis condition area of the analysis page, where the target media content is associated with a target demander;

[0106] A display module 502, configured to display the target media content and the search analysis result corresponding to the target media content on the analysis page, where the search analysis result is obtained by performing statistical analysis on the search data obtained after presenting the target media content, the search data is related to the target demander, and the search data includes at least one of a search term and the search result of the search term.

[0107] In some alternative implementation manners, the media content analysis device of the present disclosure further includes:

[0108] An acquisition module, configured to acquire first demander information associated with at least one optional media content, and second demander information associated with at least one first search data, where the target media content belongs to the optional media content, and the first search data includes the search data obtained after presenting the optional media content;

[0109] A first analysis module, configured to associate the optional media content and the first search data based on the matching situation between the first demander information and the second demander information, so as to obtain second search data corresponding to the optional media content, where the second search data is related to the demander characterized by the first demander information;

[0110] A second analysis module, configured to perform statistical analysis on the second search data to obtain a search analysis result corresponding to the optional media content.

[0111] In some alternative implementation manners, the acquisition module includes:

[0112] A first acquisition unit, configured to acquire target identification information and the content identification of the optional media content, where the target identification information is used to represent the content identification corresponding to different demanders;

[0113] A first processing unit, configured to determine first requester information based on target identification information and content identification of optional media content.

[0114] In some alternative embodiments, the optional media content is used to display a product, and both the optional media content and the product it displays are associated with the same requester. The obtaining module includes:

[0115] A link analysis unit, configured to determine a target product accessed from the display page based on an operation link of the display page of the optional media content;

[0116] A second processing unit, configured to obtain a requester associated with the target product to obtain first requester information.

[0117] In some alternative embodiments, the obtaining module includes:

[0118] A second obtaining unit, configured to obtain a target search term obtained after the optional media content is displayed;

[0119] A search term analysis unit, configured to determine the presence of requester information in the target search term;

[0120] A third obtaining unit, configured to, if no requester information exists in the target search term, obtain search results of the target search term, where the first search data includes at least one of the target search term and the search results of the target search term;

[0121] A third processing unit, configured to determine a requester associated with the search results of the target search term to obtain second requester information.

[0122] In some alternative embodiments, the obtaining module includes:

[0123] A fourth processing unit, configured to, if requester information exists in the target search term, determine a requester associated with the target search term based on the requester information in the target search term to obtain second requester information.

[0124] In some alternative embodiments, the first analysis module includes:

[0125] A data association unit, configured to associate the optional media content and the first search data based on the matching situation between the first requester information and the second requester information;

[0126] A first attribution analysis unit, configured to, if the first search data does not meet a preset attribution stop condition, write the first search data that has not been successfully attributed into a message queue, and for the first search data in the message queue, attribute the optional media content that triggers the generation of the first search data based on the association result to obtain an attribution result;

[0127] A data statistics unit, configured to determine second search data corresponding to optional media content based on the attribution result.

[0128] In some optional embodiments, the first analysis module further includes:

[0129] A second attribution analysis unit, configured to delete the first search data that has not been successfully attributed if the first search data meets a preset attribution stop condition.

[0130] The further function descriptions of the above-mentioned various modules and units are the same as those in the corresponding embodiments above, and will not be elaborated here.

[0131] The media content analysis device in this embodiment is presented in the form of functional units. Here, the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0132] This embodiment of the present disclosure further provides an electronic device having the above-mentioned Figure 5 shown media content analysis device.

[0133] Please refer to Figure 6 , Figure 6 which is a structural block diagram of an electronic device provided by an optional embodiment of the present disclosure. As shown in Figure 6 , the electronic device includes: one or more processors 601, a memory 602, and an interface for connecting each component, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed within the electronic device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a set of blade servers, or a multi-processor system). Figure 6 Take one processor 601 as an example in

[0134] The processor 601 can be a central processor, a network processor, or a combination thereof. Among them, the processor 601 can further include a hardware chip. The above-mentioned hardware chip can be an application specific integrated circuit, a programmable logic device, or a combination thereof. The above-mentioned programmable logic device can be a complex programmable logic device, a field programmable gate array, a general array logic, or any combination thereof.

[0135] Among them, the memory 602 stores instructions that can be executed by at least one processor 601, so that the at least one processor 601 executes the method shown in the above embodiments.

[0136] The memory 602 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the electronic device, etc. In addition, the memory 602 may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 602 may optionally include a memory remotely provided with respect to the processor 601, and these remote memories can be connected to the electronic device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0137] The memory 602 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk, or a solid-state drive; the memory 602 may also include a combination of the above types of memories.

[0138] The electronic device further includes an input device 603 and an output device 604. The processor 601, the memory 602, the input device 603, and the output device 604 may be connected through a bus or other means. Figure 6 Taking the connection through the bus as an example.

[0139] The input device 603 can receive input digital or character information, and generate key signal inputs related to the user settings and function controls of the electronic device, such as a touch screen, a keypad, a mouse, a trackpad, a touchpad, a pointing stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 604 may include a display device, an auxiliary lighting device (such as an LED), and a haptic feedback device (such as a vibration motor), etc. The above display device includes but is not limited to a liquid crystal display, a light-emitting diode, a display, and a plasma display. In some alternative embodiments, the display device may be a touch screen.

[0140] Embodiments of the present disclosure also provide a computer-readable storage medium. The methods according to the embodiments of the present disclosure can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented as computer code that is originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the methods described herein can be processed by such software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code, and when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the methods shown in the above embodiments are implemented.

[0141] A part of the present disclosure can be applied as a computer program product, for example, computer program instructions, which when executed by a computer, can call or provide the methods and / or technical solutions according to the present disclosure through the operation of the computer. Those skilled in the art should understand that the forms of existence of computer program instructions in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Herein, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0142] Although the embodiments of the present disclosure have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present disclosure, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A media content analysis method, characterized in that: The method comprises: In response to an interactive operation in the analysis condition area of ​​the analysis page, determining a target analysis condition and target media content that meets the target analysis condition, wherein the target media content is associated with a target demander; The target media content and the search analysis results corresponding to the target media content are displayed in the analysis page, and the search analysis results are obtained after statistical analysis of search data obtained after displaying the target media content. The search data is related to the target demander, and the search data includes at least one of a search term and a search result of the search term.

2. The media content analysis method according to claim 1, characterized in that: The method further comprises: Acquire first demander information associated with at least one optional media content and second demander information associated with at least one first search data, wherein the target media content belongs to the optional media content, and the first search data includes search data obtained after displaying the optional media content; Based on the matching between the first demander information and the second demander information, the selectable media content and the first search data are associated to obtain second search data corresponding to the selectable media content, where the second search data is related to the demander represented by the first demander information; Statistical analysis is performed on the second search data to obtain search analysis results corresponding to the selectable media content.

3. The media content analysis method according to claim 2, characterized in that: The obtaining of first demander information associated with at least one selectable media content includes: Acquire target identification information and content identification of the selectable media content, wherein the target identification information is used to represent content identifications corresponding to different demand parties; The first demander information is determined based on the target identification information and the content identification of the selectable media content.

4. The media content analysis method according to claim 2, characterized in that: The selectable media content is used to display a product, and the selectable media content and the product displayed by the selectable media content are associated with the same demander; and obtaining first demander information associated with at least one selectable media content includes: Determining a target product accessed from the display page based on an operation link of the display page of the selectable media content; Obtain the demander associated with the target product to obtain the first demander information.

5. The media content analysis method according to claim 2, characterized in that: Acquiring second demander information associated with at least one first search data includes: Acquire a target search term obtained after displaying the selectable media content; Determine the existence of demander information in the target search term; If the demander information does not exist in the target search term, obtaining the search result of the target search term, wherein the first search data includes at least one of the target search term and the search result of the target search term; Determine the demand side associated with the search result of the target search term to obtain the second demand side information.

6. The media content analysis method according to claim 5, characterized in that: The obtaining of the second demander information associated with the at least one first search data further includes: If demander information exists in the target search term, the demander associated with the target search term is determined based on the demander information in the target search term to obtain the second demander information.

7. The media content analysis method according to claim 2, characterized in that: The associating the selectable media content and the first search data based on the matching condition between the first demander information and the second demander information to obtain the second search data corresponding to the selectable media content includes: Associating the selectable media content with the first search data based on a match between the first demander information and the second demander information; If the first search data does not meet the preset attribution stop condition, the first search data that has not been successfully attributed is written into the message queue, and for the first search data in the message queue, the optional media content that triggers the first search data is attributed based on the association result to obtain an attribution result; Second search data corresponding to the selectable media content is determined based on the attribution result.

8. The media content analysis method according to claim 7, characterized in that: The method further comprises: If the first search data meets the preset attribution stop condition, the first search data that has not been successfully attributed will be deleted.

9. A media content analysis device, characterized in that: The device comprises: An interactive module, configured to determine a target analysis condition and target media content satisfying the target analysis condition in response to an interactive operation in the analysis condition area of ​​the analysis page, wherein the target media content is associated with a target demander; A display module is used to display the target media content and the search analysis results corresponding to the target media content in the analysis page, wherein the search analysis results are obtained after statistical analysis of search data obtained after displaying the target media content, the search data is related to the target demander, and the search data includes at least one of a search term and a search result of the search term.

10. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the media content analysis method according to any one of claims 1 to 8 by executing the computer instructions.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the media content analysis method according to any one of claims 1 to 8.

12. A computer program product, characterized in that The method comprises computer instructions, wherein the computer instructions are used to cause a computer to execute the media content analysis method according to any one of claims 1 to 8.

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