CN113761332A - Data processing method, device, equipment and computer readable storage medium - Google Patents
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Abstract
The invention provides a data processing method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: acquiring a path analysis request sent by terminal equipment; according to the path analysis request, acquiring an article to be analyzed and historical browsing data corresponding to a plurality of candidate articles related to the article to be analyzed from a preset data server; analyzing a browsing path corresponding to an article to be analyzed according to the historical browsing data to obtain an analysis result; and establishing an analysis report comprising the visual drawing according to the analysis result, and sending the analysis report to the terminal equipment. Therefore, the path corresponding to the user-defined object to be analyzed can be analyzed, an analysis result is obtained, and the personalized requirements of the user can be met. After the analysis result is obtained, an analysis report including a visual figure can be generated according to the analysis result, so that a user can know the analysis result more intuitively, and the user experience is improved.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a data processing method, apparatus, device, and computer readable storage medium.
Background
With the development of networks, the use of websites or application software by users is more and more frequent, and users can browse information, socialize, shop and the like in the websites or the application software. In order to realize the understanding of the user behavior preference and the measurement of the optimization effect or the marketing promotion effect during the website or application software optimization, the access behavior path of the user in the website or application software needs to be analyzed.
In the prior art, all historical data corresponding to a certain article or a certain user are generally obtained, and a preset analysis model is adopted to perform data analysis on all historical data.
However, the path analysis method is often based only on data analysis of specific data, and the analysis content and result are relatively fixed. The actual requirements of the user on the path analysis cannot be met.
Disclosure of Invention
The invention provides a data processing method, a data processing device, data processing equipment and a computer readable storage medium, which are used for solving the technical problems that the existing path analysis method is only based on data analysis of specific data, the analysis content and result are relatively fixed, and the actual requirements of a user on path analysis cannot be met.
A first aspect of the present invention provides a data processing method, including:
acquiring a path analysis request sent by terminal equipment, wherein the path analysis request comprises brand information, category information, shop information and a time range selected by a user, which correspond to an article to be analyzed;
acquiring historical browsing data corresponding to the to-be-analyzed object and a plurality of candidate objects related to the to-be-analyzed object in a preset data server according to the path analysis request;
analyzing a browsing path corresponding to the to-be-analyzed object according to the historical browsing data to obtain an analysis result;
and establishing an analysis report comprising a visual figure according to the analysis result, and sending the analysis report to the terminal equipment.
A second aspect of the present invention provides a data processing apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a path analysis request sent by terminal equipment, and the path analysis request comprises brand information, category information, shop information and a time range selected by a user and corresponding to an article to be analyzed;
the screening module is used for acquiring the to-be-analyzed object and historical browsing data corresponding to a plurality of candidate objects related to the to-be-analyzed object in a preset data server according to the path analysis request;
the analysis module is used for analyzing the browsing path corresponding to the to-be-analyzed object according to the historical browsing data to obtain an analysis result;
and the sending module is used for establishing an analysis report comprising a visual figure according to the analysis result and sending the analysis report to the terminal equipment.
A third aspect of the present invention provides a data processing apparatus comprising: a memory, a processor;
a memory; a memory for storing the processor-executable instructions;
wherein the processor is configured to invoke program instructions in the memory to perform the method of the first aspect.
A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer-executable instructions for implementing the method according to the first aspect when executed by a processor.
According to the data processing method, the data processing device, the data processing equipment and the computer readable storage medium, the path analysis request sent by the terminal equipment is obtained, so that the path corresponding to the user-defined object to be analyzed can be analyzed, the analysis result is obtained, and the personalized requirements of the user can be met. In addition, after the analysis result is obtained, the analysis report comprising the visual figure can be generated according to the analysis result, so that the user can know the analysis result more intuitively, and the user experience is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art according to the drawings.
FIG. 1 is a schematic diagram of a network architecture on which the present invention is based;
fig. 2 is a schematic flowchart of a data processing method according to a first embodiment of the disclosure;
FIG. 3 is a schematic diagram of a display interface provided by an embodiment of the present disclosure;
fig. 4 is a schematic flowchart of a data processing method according to a second embodiment of the disclosure;
fig. 5 is a schematic flowchart of a data processing method according to a third embodiment of the disclosure;
FIG. 6 is a schematic diagram of a set of users in at least one category provided by an embodiment of the present disclosure;
fig. 7 is a schematic flowchart of a data processing method according to a fourth embodiment of the disclosure;
fig. 8 is a schematic flowchart of a data processing method according to a fifth embodiment of the disclosure;
fig. 9 is a schematic structural diagram of a data processing apparatus according to a sixth embodiment of the present disclosure;
fig. 10 is a schematic structural diagram of a data processing apparatus according to a seventh embodiment of the present disclosure;
fig. 11 is a schematic structural diagram of a data processing apparatus according to an eighth embodiment of the present disclosure;
fig. 12 is a schematic structural diagram of a data processing apparatus according to a ninth embodiment of the present disclosure;
fig. 13 is a schematic structural diagram of a data processing apparatus according to a tenth embodiment of the present disclosure;
fig. 14 is a schematic structural diagram of a data processing apparatus according to an eleventh embodiment of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other examples obtained based on the examples in the present invention are within the scope of the present invention.
The invention provides a data processing method, a device, equipment and a computer readable storage medium, aiming at the technical problems that the existing path analysis method is only based on the data analysis of specific data, the analysis content and the result are relatively fixed, and the actual requirements of a user on the path analysis cannot be met.
It should be noted that the data processing method, apparatus, device, and computer-readable storage medium provided in the present application may be applied in various scenarios of path analysis.
The existing path analysis method generally aims at a certain article or a certain user to acquire all browsing data corresponding to the article or the user from a database for path analysis. However, the above method can only perform path analysis based on all browsing data, and the obtained analysis result is often fixed and not comprehensive enough, and cannot meet the personalized requirements of users.
In the process of solving the technical problems, the inventor finds, through research, that in order to improve the pertinence of path analysis and meet the personalized requirements of users, a path analysis request customized by the users can be obtained, and the path analysis is performed according to the path analysis request customized by the users, so that the fixed data corresponding to a certain product is not limited any more. Therefore, the obtained path analysis result can better meet the actual requirements of users.
Fig. 1 is a schematic diagram of a network architecture based on the present invention, and as shown in fig. 1, the network architecture based on the present invention at least includes: terminal device 1, server 2 and data server 3. Wherein, the server 2 is provided with a data analysis device which is written by C/C + +, Java, Shell or Python and other languages; the terminal device 1 may be a desktop computer, a tablet computer, or the like. The data server 3 may be a cloud server or a server cluster, and a large amount of data is stored therein. The server 2 is in communication connection with the terminal device 1 and the data server 3, respectively, so that information interaction with the terminal device 1 and the data server 3 can be performed, respectively.
Fig. 2 is a schematic flow chart of a data processing method according to a first embodiment of the disclosure, as shown in fig. 2, the method includes:
The execution subject of the present embodiment is a data processing apparatus. The data device may be coupled to a server. The server is respectively connected with the terminal equipment and the data server in a communication mode. Therefore, information interaction can be respectively carried out with the terminal equipment and the server.
In this embodiment, in order to analyze the browsing path of a certain object to be analyzed, a user may input information such as brand information, category information, store information, and a time range selected by the user of the object to be analyzed on a terminal device according to actual needs, and the terminal device may generate a path analysis request according to the information input by the user and transmit the path analysis request to the data processing apparatus, so that the data processing apparatus performs a data processing operation. Accordingly, the data processing apparatus can acquire the path analysis request transmitted by the terminal device.
Fig. 3 is a schematic view of a display interface provided in the embodiment of the present disclosure, and as shown in fig. 3, an input box which can be used for inputting a time range, category information corresponding to an object to be analyzed, and store information is provided on the display interface, and a user can input corresponding data in the input box to generate a path analysis request.
For example, in practical applications, the object to be analyzed may be a commodity in an e-commerce platform, and accordingly, the category information corresponding to the object to be analyzed may include brand information corresponding to the commodity, a specific category of the commodity under the brand information, price information of an item to be competed corresponding to the commodity, and the like.
In the present embodiment, each object to be analyzed corresponds to a plurality of candidate objects related thereto. For example, the candidate object may be a competitive product corresponding to the commodity, taking the object to be analyzed as the commodity in the e-commerce platform. For example, it may be a different brand, same efficacy commodity from the analyte item.
In order to implement path analysis of an object to be analyzed, after acquiring a path analysis request, the data processing device may acquire the object to be analyzed and historical browsing data corresponding to a plurality of candidate objects related to the object to be analyzed from a preset data server. The historical browsing data can be browsing records of a plurality of users who have historically browsed the to-be-analyzed object, and can also include purchase records, collection information, shopping cart adding information and the like corresponding to the to-be-analyzed object.
And 103, analyzing the browsing path corresponding to the to-be-analyzed object according to the historical browsing data to obtain an analysis result.
In this embodiment, after the historical browsing data is acquired, the analysis operation of the browsing path on the article to be analyzed can be performed according to the historical browsing data, so as to obtain the analysis result. Since the historical browsing data includes all the browsed information of the object to be analyzed in the preset time range, the analysis operation of the browsing path can be accurately performed according to the historical browsing data.
And 104, establishing an analysis report comprising a visual figure according to the analysis result, and sending the analysis report to the terminal equipment.
In the present embodiment, in order to make the user understand the analysis result more intuitively, after obtaining the analysis result, a visualization may be generated based on the analysis result, and an analysis report including the visualization may be further generated. In addition, the analysis report can be sent to the terminal equipment of the user, so that the user can directly view the analysis report on the terminal equipment.
According to the data processing method provided by the embodiment, the path analysis request sent by the terminal device is obtained, so that the path corresponding to the user-defined object to be analyzed can be analyzed, the analysis result is obtained, and the personalized requirements of the user can be met. In addition, after the analysis result is obtained, the analysis report comprising the visual figure can be generated according to the analysis result, so that the user can know the analysis result more intuitively, and the user experience is improved.
Fig. 4 is a schematic flow chart of a data processing method according to a second embodiment of the present disclosure, and on the basis of the first embodiment, as shown in fig. 4, before step 102, the method further includes:
In the present embodiment, each object to be analyzed corresponds to a plurality of candidate objects related thereto. For example, the candidate object may be a competitive product corresponding to the commodity, taking the object to be analyzed as the commodity in the e-commerce platform. For example, it may be a different brand, same efficacy commodity from the analyte item.
Therefore, before acquiring the historical browsing data, a plurality of candidate items corresponding to the to-be-analyzed item need to be determined first.
Specifically, a target vector corresponding to the object to be analyzed may be calculated. And respectively calculating the similarity between the target vector and the vectors of all preset candidate objects, and determining a plurality of candidate objects related to the object to be analyzed according to the similarity.
Further, step 201 specifically includes:
determining an initial vector of the object to be analyzed according to a preset word vector and the attribute information of the object to be analyzed;
acquiring historical behavior data corresponding to the to-be-analyzed object from a preset data server, and screening a target entity pair from the historical data;
and calculating the target vector according to the initial vector and the target entity pair.
In this embodiment, the matching may be specifically performed according to the preset word vector and the attribute information of the object to be analyzed, and the vector combination is performed to obtain the initial vector of the object to be analyzed. The attribute information of the object to be analyzed includes, but is not limited to, main product words, function attributes, style attributes, material attributes, style attributes, crowd attributes, region attributes, color attributes, scene attributes, taste attributes, season attributes, and size attributes.
Historical behavior data corresponding to the to-be-analyzed object is acquired from a preset data server, wherein the historical behavior data comprises but is not limited to clicking, adding a shopping cart, purchasing and the like of a user. And screening the target entity pair according to the historical behavior data. And calculating a target vector according to the initial vector and the target entity pair.
According to the data processing method provided by the embodiment, before the historical browsing data is acquired, the plurality of candidate objects corresponding to the object to be analyzed are determined according to the target vector of the object to be analyzed, so that the accuracy of subsequent path analysis can be improved.
On the basis of any of the above embodiments, before the step 102, the method further includes:
and calculating a set of items effectively released by the user in the time range through a preset network model, wherein the item combination comprises the candidate items.
In this embodiment, a preset network model may be used to calculate a set of items that are effectively delivered by the user within a time range, where the item combination includes the plurality of candidate items. Specifically, the network model can perform statistics according to four dimensions of time, shops, categories and brands, and calculate consumption corresponding to the user. Counting the data of which the total consumption ranking exceeds a preset threshold value in the time range, and adding a statistical index to each piece of data according to the four dimensions: average consumption, single user identification maximum consumption, store ranking, and consumption ratio to rank first under the same dimension. The user may be an advertiser who puts an advertisement.
Specifically, the network model includes the following admission conditions:
1. in the above four dimensions, consumption of a single user identifier is equal to minimum consumption of the single user identifier;
2. if the user's consumption is greater than the average consumption or minimum consumption requirement, the higher the user's consumption and the first-ranked consumption ratio, the higher the user's admission can be.
3. The plan of the user is time-ranged, some fluctuation periods or even empty windows exist in the release of stores, categories and brands, therefore, the idea of a flow control leaky bucket algorithm can be adopted, when the user meets the conditions 1 and 2, a certain credit value is given, when the user does not meet the conditions, deduction is carried out according to the current credit value, if the credit value is zero, inquiry admission is forbidden, if the conditions are met again, the credit value is reset, and the steps are repeatedly executed according to actual requirements.
According to the data processing method provided by the embodiment, the preset network model is adopted to calculate the item set effectively put in by the user in the time range, so that the access experience can be improved, and the data leakage risk is reduced.
Fig. 5 is a schematic flow chart of a data processing method according to a third embodiment of the present disclosure, where on the basis of any of the foregoing embodiments, as shown in fig. 5, step 103 specifically includes:
And 303, analyzing the browsing path corresponding to the to-be-analyzed object according to the analysis time interval corresponding to each user set to obtain an analysis result.
In this embodiment, after determining the set of effectively delivered items, the user type may be further classified.
Optionally, it may be detected whether a plurality of users in the historical browsing data trigger a preset target operation on the item to be analyzed and/or the candidate item, so as to obtain a detection result. The detection result may specifically include target triggering operation on the object to be analyzed, target triggering operation on the object not to be analyzed, target triggering operation on the candidate object, target triggering operation on the object to be analyzed and the candidate object, and target triggering operation on the object not to be analyzed and the candidate object.
And then classifying the plurality of users according to the detection result to obtain a user set of at least one category.
In particular, the target operation may be a purchase operation of the item to be analyzed. Fig. 6 is a schematic diagram of a user set of at least one category provided by the embodiment of the present disclosure, and as shown in fig. 6, the user set may specifically include a user set 1 for purchasing an item to be analyzed, a user set 2 for purchasing a candidate item, a user set 3 for purchasing the item to be analyzed and the candidate item, and a user set 4 for purchasing neither the item to be analyzed nor the candidate item.
Further, different analysis time intervals may be set for each set of users, respectively. Therefore, the browsing path corresponding to the article to be analyzed can be analyzed according to the analysis time interval corresponding to the user set, and an analysis result is obtained.
Specifically, the starting point of the analysis time interval corresponding to the user set purchasing the article to be analyzed is the backward retroactive time length of the first purchasing behavior, and the ending point is the current day of the last purchasing behavior. For example, the time interval of the analysis is two days before the first purchase to the day of the last purchase, taking the tracing time length as 2 days. The starting point of the analysis time interval corresponding to the user set which does not purchase the to-be-analyzed object is the time of backward tracing of the first advertisement exposure time, and the ending point is the day of the last advertisement exposure. For example, the trace-back time duration is 2 days, and the analysis time interval is two days before the first advertisement exposure to the last advertisement exposure day.
According to the data processing method provided by the embodiment, the users are classified, and the browsing paths corresponding to the articles to be analyzed are analyzed according to the analysis time intervals corresponding to the classified user sets, so that the accuracy of path analysis can be further improved.
Fig. 7 is a schematic flow chart of a data processing method according to a fourth embodiment of the present disclosure, and based on any of the above embodiments, as shown in fig. 7, step 103 specifically includes:
In this embodiment, after obtaining the historical browsing data, the page browsing amount of each page corresponding to the object to be analyzed and the candidate object may be determined according to the historical browsing data. And according to the page browsing amount, calculating browsing rate scores of the candidate items and the items to be analyzed viewed by the user, and obtaining the analysis result. Specifically, the browsing rate score is calculated according to the number of the to-be-analyzed articles and the number of the candidate articles browsed by the user before purchase, and the score reflects interest and loyalty of the user on the brand.
If the browsing ratio score is larger than 0, the number of the articles to be analyzed browsed by the user is larger than the number of the candidate articles, and the higher the score is, the higher the interest degree of the user in the brand is represented. On the contrary, if the browsing rate score is less than 0, the number of the candidate items browsed by the user is more than that of the to-be-analyzed items, and the lower the score is, the lower the interest degree of the user in the brand is represented.
According to the data processing method provided by the embodiment, the page browsing amount of each page corresponding to the to-be-analyzed object and the candidate object is respectively determined according to the historical browsing data, and the browsing rate scores of the to-be-analyzed object and the candidate object viewed by the user are calculated according to the page browsing amount, so that the behavior path of the user can be accurately analyzed.
Specifically, on the basis of any of the above embodiments, the visualization drawings include one or more of a path flow diagram, a hotspot path diagram, a path funnel diagram and an article awareness diagram.
The path flow diagram can be a mor-base diagram, and the mor-base diagram can visually display main conversion flow directions of user groups such as users purchasing the object to be analyzed, users purchasing the candidate object, users purchasing the object to be analyzed and the candidate object at the same time, potential purchasing users and the like between the advertisement and the page path.
The hot spot path diagram can visually display the exposure combination of the advertisement or the page with the most popular browsing or conversion times among different user groups.
The user can customize the path funnel graph in a personalized mode so as to rapidly analyze the circulation situation of the key nodes of the user circulation situation under the appointed behavior path in the user page and the advertisement path.
The article cognition map can visually show the brand interest distribution degree of user groups such as users purchasing the articles to be analyzed, users purchasing the candidate articles, users purchasing the articles to be analyzed simultaneously, users of the candidate articles, potential purchasing users and the like.
And calculating to obtain a commodity browsing rate score based on the number of the to-be-analyzed objects and the number of the candidate objects browsed by the user, dividing the cognitive degree intervals of the to-be-analyzed object brands and the candidate object brands of the user, reflecting the interest and loyalty degree of the user to the brands, and mastering the cognitive conditions of the to-be-analyzed objects and the candidate object brands so as to measure the relative loyalty of the to-be-analyzed objects and the candidate object users.
Fig. 8 is a schematic flow chart of a data processing method according to a fifth embodiment of the present disclosure, and on the basis of any of the foregoing embodiments, as shown in fig. 8, the method further includes:
In this embodiment, the user may also perform a trigger operation on a preset element in the visualization drawing in an interface interaction manner. Correspondingly, feedback information corresponding to the preset element can be determined according to the trigger operation, and the feedback information is sent to the terminal equipment.
Specifically, when the visual attached drawing is a path circulation drawing, the feedback information can be behavior paths of different user groups, and the user purchasing the article to be analyzed can drill down to the stages of old and new customers, different sexes and different ages to analyze the behavior paths of the specific group; run-off rate and user ratio to candidate item/to-be-analyzed item and candidate item; the circulation information and the inflow and outflow of each contact form a structure; the customized analytical transformation pathway funnel.
When the visual attached drawing is a hot spot path drawing, the feedback information can be specifically the behavior paths of different user groups, and the user purchasing the article to be analyzed can drill down to the stages of old and new customers, different sexes and different ages to analyze the behavior paths of the specific group.
When the visualization drawing is a path funnel drawing, the feedback information may specifically be behavior paths of different user groups.
According to the data processing method provided by the embodiment, the feedback information corresponding to the preset element is determined according to the trigger operation, and the feedback information is sent to the terminal equipment, so that a user can check the current analysis result more clearly, and the user experience is improved.
Fig. 9 is a schematic structural diagram of a data processing apparatus according to a sixth embodiment of the present disclosure, and as shown in fig. 9, the apparatus includes: the system comprises an acquisition module 61, a screening module 62, an analysis module 63 and a sending module 64, wherein the acquisition module 61 is configured to acquire a path analysis request sent by a terminal device, and the path analysis request includes brand information, category information, store information and a time range selected by a user and corresponding to an article to be analyzed. And a screening module 62, configured to obtain, in a preset data server, the to-be-analyzed object and historical browsing data corresponding to the multiple candidate objects related to the to-be-analyzed object according to the path analysis request. And the analysis module 63 is configured to analyze the browsing path corresponding to the to-be-analyzed object according to the historical browsing data to obtain an analysis result. And the sending module 64 is configured to establish an analysis report including the visualization drawing according to the analysis result, and send the analysis report to the terminal device.
The data processing device provided by the embodiment can analyze the path corresponding to the user-defined object to be analyzed by acquiring the path analysis request sent by the terminal device, so as to obtain an analysis result, and can meet the personalized requirements of the user. In addition, after the analysis result is obtained, the analysis report comprising the visual figure can be generated according to the analysis result, so that the user can know the analysis result more intuitively, and the user experience is improved.
Fig. 10 is a schematic structural diagram of a data processing apparatus according to a seventh embodiment of the present disclosure, and based on the sixth embodiment, as shown in fig. 10, the apparatus further includes: a target vector calculation module 71, a similarity calculation module 72, and a determination module 73, where the target vector calculation module 71 is configured to calculate a target vector corresponding to the object to be analyzed; a similarity calculation module 72, configured to calculate similarities between the target vector and all preset candidate articles respectively; a determining module 73, configured to determine the plurality of candidate items related to the object to be analyzed according to the similarity.
Further, on the basis of the sixth embodiment, the target vector calculation module is configured to:
determining an initial vector of the object to be analyzed according to a preset word vector and the attribute information of the object to be analyzed;
acquiring historical behavior data corresponding to the to-be-analyzed object from a preset data server, and screening a target entity pair from the historical data;
and calculating the target vector according to the initial vector and the target entity pair.
Further, on the basis of the sixth embodiment, the apparatus further includes:
and the item set calculating module is used for calculating an item set effectively released by the user in the time range through a preset network model, wherein the item combination comprises the candidate items.
Fig. 11 is a schematic structural diagram of a data processing apparatus according to an eighth embodiment of the present disclosure, where on the basis of any of the foregoing embodiments, as shown in fig. 11, the analysis module includes: the device comprises a detection unit 81, a classification unit 82 and an analysis unit 83, wherein the detection unit 81 is used for detecting whether a plurality of users trigger preset target operations on the object to be analyzed and/or the candidate object in the historical browsing data to obtain a detection result; a classifying unit 82, configured to perform a classifying operation on the multiple users according to the detection result, so as to obtain a user set of at least one category; and the analyzing unit 83 is configured to analyze, for each user set, the browsing path corresponding to the to-be-analyzed object according to the analysis time interval corresponding to the user set, respectively, so as to obtain an analysis result.
Fig. 12 is a schematic structural diagram of a data processing apparatus according to a ninth embodiment of the present disclosure, where on the basis of any of the foregoing embodiments, as shown in fig. 12, the analysis module includes: the device comprises a page browsing amount determining unit 91 and a calculating unit 92, wherein the page browsing amount determining unit 91 is used for determining the page browsing amount of each page corresponding to the object to be analyzed and the candidate object respectively according to the historical browsing data; and the calculating unit 92 is configured to calculate browsing rate scores of the to-be-analyzed object and the candidate object viewed by the user according to the page browsing amount, and obtain the analysis result.
Further, on the basis of any of the above embodiments, the visualization drawings include one or more of a path flow diagram, a hotspot path diagram, a path funnel diagram, and an item awareness diagram.
Fig. 13 is a schematic structural diagram of a data processing apparatus provided in a tenth embodiment of the present disclosure, and on the basis of any of the foregoing embodiments, as shown in fig. 13, the data processing apparatus further includes: the visual image display device comprises a trigger request acquisition module 111, a feedback information determination module 112 and a feedback module 113, wherein the trigger request acquisition module 111 is configured to acquire a trigger request sent by a terminal device, and the trigger request is generated according to a trigger operation of a user on the terminal device on a preset element in the visual image; a feedback information determining module 112, configured to determine, according to the trigger operation, feedback information corresponding to the preset element; a feedback module 113, configured to send the feedback information to the terminal device.
Fig. 14 is a schematic structural diagram of a data processing apparatus according to an eleventh embodiment of the present disclosure, and as shown in fig. 14, the data processing apparatus includes: memory 121, processor 122;
a memory 121; a memory 121 for storing instructions executable by the processor 122;
wherein, the processor 122 is used for calling the program instructions in the memory 121 to execute the method according to any one of the above embodiments.
The memory 121 stores programs. In particular, the program may include program code comprising computer operating instructions. The memory 121 may comprise a high-speed RAM memory, and may further comprise a non-volatile memory (non-volatile memory), such as at least one disk memory.
The processor 122 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present invention.
Alternatively, in a specific implementation, if the memory 121 and the processor 122 are implemented independently, the memory 121 and the processor 122 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 14, but this is not intended to represent only one bus or type of bus.
Alternatively, in a specific implementation, if the memory 121 and the processor 122 are integrated on a chip, the memory 121 and the processor 122 may perform the same communication through an internal interface.
Yet another embodiment of the present disclosure further provides a computer-readable storage medium having stored thereon computer-executable instructions for implementing the method according to any one of the above embodiments when executed by a processor.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working process of the apparatus described above may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (18)
1. A data processing method, comprising:
acquiring a path analysis request sent by terminal equipment, wherein the path analysis request comprises brand information, category information, shop information and a time range selected by a user, which correspond to an article to be analyzed;
acquiring historical browsing data corresponding to the to-be-analyzed object and a plurality of candidate objects related to the to-be-analyzed object in a preset data server according to the path analysis request;
analyzing a browsing path corresponding to the to-be-analyzed object according to the historical browsing data to obtain an analysis result;
and establishing an analysis report comprising a visual figure according to the analysis result, and sending the analysis report to the terminal equipment.
2. The method according to claim 1, wherein before acquiring, in a preset data server, historical browsing data corresponding to the object to be analyzed and a plurality of candidate objects related to the object to be analyzed, the method further comprises:
calculating a target vector corresponding to the to-be-analyzed object;
respectively calculating the similarity between the target vector and all preset candidate articles;
determining the plurality of candidate items related to the to-be-analyzed item according to the similarity.
3. The method of claim 2, wherein the calculating a target vector corresponding to the object to be analyzed comprises:
determining an initial vector of the object to be analyzed according to a preset word vector and the attribute information of the object to be analyzed;
acquiring historical behavior data corresponding to the to-be-analyzed object from a preset data server, and screening a target entity pair from the historical data;
and calculating the target vector according to the initial vector and the target entity pair.
4. The method according to any one of claims 1 to 3, wherein before acquiring, according to the path analysis request, historical browsing data corresponding to the object to be analyzed and a plurality of candidate objects related to the object to be analyzed in a preset data server, the method further comprises:
and calculating an item set which is effectively released by the user in the time range through a preset network model, wherein the item set comprises the candidate items.
5. The method according to any one of claims 1 to 3, wherein the analyzing the browsing path corresponding to the to-be-analyzed object according to the historical browsing data to obtain an analysis result comprises:
detecting whether a plurality of users in the historical browsing data trigger preset target operation on the object to be analyzed and/or the candidate object to obtain a detection result;
classifying the plurality of users according to the detection result to obtain a user set of at least one category;
and analyzing the browsing path corresponding to the to-be-analyzed object according to the analysis time interval corresponding to each user set to obtain an analysis result.
6. The method according to any one of claims 1 to 3, wherein the analyzing the browsing path corresponding to the to-be-analyzed object according to the historical browsing data to obtain an analysis result comprises:
respectively determining the object to be analyzed and the page browsing amount of each page corresponding to the candidate object according to the historical browsing data;
and according to the page browsing amount, calculating browsing rate scores of the candidate items and the items to be analyzed viewed by the user, and obtaining the analysis result.
7. The method of any one of claims 1-3, wherein the visualization graph comprises one or more of a path-flow graph, a hotspot path graph, a path-funnel graph, an item-awareness graph.
8. The method of claim 7, further comprising:
acquiring a trigger request sent by terminal equipment, wherein the trigger request is generated according to trigger operation of a user on preset elements in the visual figure on the terminal equipment;
determining feedback information corresponding to the preset elements according to the triggering operation;
and sending the feedback information to the terminal equipment.
9. A data processing apparatus, comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a path analysis request sent by terminal equipment, and the path analysis request comprises brand information, category information, shop information and a time range selected by a user and corresponding to an article to be analyzed;
the screening module is used for acquiring the to-be-analyzed object and historical browsing data corresponding to a plurality of candidate objects related to the to-be-analyzed object in a preset data server according to the path analysis request;
the analysis module is used for analyzing the browsing path corresponding to the to-be-analyzed object according to the historical browsing data to obtain an analysis result;
and the sending module is used for establishing an analysis report comprising a visual figure according to the analysis result and sending the analysis report to the terminal equipment.
10. The apparatus of claim 9, further comprising:
the target vector calculation module is used for calculating a target vector corresponding to the to-be-analyzed object;
the similarity calculation module is used for calculating the similarity between the target vector and all preset candidate articles respectively;
a determining module, configured to determine the multiple candidate items related to the object to be analyzed according to the similarity.
11. The apparatus of claim 10, wherein the target vector calculation module is configured to:
determining an initial vector of the object to be analyzed according to a preset word vector and the attribute information of the object to be analyzed;
acquiring historical behavior data corresponding to the to-be-analyzed object from a preset data server, and screening a target entity pair from the historical data;
and calculating the target vector according to the initial vector and the target entity pair.
12. The apparatus according to any one of claims 9-11, further comprising:
and the item set calculating module is used for calculating an item set effectively released by the user in the time range through a preset network model, wherein the item combination comprises the candidate items.
13. The apparatus of any one of claims 9-11, wherein the analysis module comprises:
the detection unit is used for detecting whether a plurality of users trigger preset target operation on the object to be analyzed and/or the candidate object in the historical browsing data to obtain a detection result;
the classification unit is used for performing classification operation on the plurality of users according to the detection result to obtain a user set of at least one category;
and the analysis unit is used for analyzing the browsing path corresponding to the to-be-analyzed object according to the analysis time interval corresponding to each user set to obtain an analysis result.
14. The apparatus of any one of claims 9-11, wherein the analysis module comprises:
the page browsing amount determining unit is used for respectively determining the page browsing amount of the object to be analyzed and each page corresponding to the candidate object according to the historical browsing data;
and the calculating unit is used for calculating the browsing rate scores of the to-be-analyzed object and the candidate object viewed by the user according to the page browsing amount to obtain the analysis result.
15. The apparatus of any one of claims 9-11, wherein the visualization graph comprises one or more of a path-flow graph, a hotspot path graph, a path-funnel graph, an item-awareness graph.
16. The apparatus of claim 15, further comprising:
the trigger request acquisition module is used for acquiring a trigger request sent by terminal equipment, wherein the trigger request is generated according to the trigger operation of the user on the terminal equipment on a preset element in the visual figure;
a feedback information determining module, configured to determine, according to the trigger operation, feedback information corresponding to the preset element;
and the feedback module is used for sending the feedback information to the terminal equipment.
17. A data processing apparatus, characterized by comprising: a memory, a processor;
a memory; a memory for storing the processor-executable instructions;
wherein the processor is configured to invoke program instructions in the memory to perform the method of any of claims 1-8.
18. A computer-readable storage medium having computer-executable instructions stored thereon, which when executed by a processor, perform the method of any one of claims 1-8.
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