CN112132664A

CN112132664A - Shopping data sharing method and system based on big data and electronic mall platform

Info

Publication number: CN112132664A
Application number: CN202011067600.1A
Authority: CN
Inventors: 刘秋杏; 其他发明人请求不公开姓名
Original assignee: Guangzhou Smart Internet Technology Co ltd
Current assignee: Shanghai aipai Technology Group Co.,Ltd.
Priority date: 2020-10-06
Filing date: 2020-10-06
Publication date: 2020-12-25
Anticipated expiration: 2040-10-06
Also published as: CN112132664B

Abstract

The invention relates to the technical field of big data and electronic commerce, in particular to a shopping data sharing method and system based on big data and an electronic mall platform. After the shopping commodity label information is generated, the shopping commodity sharing information in the shopping commodity label information can be divided into a plurality of shopping commodity sharing events based on the sharing configuration service, and then the sharing characteristic sequence corresponding to each shopping commodity sharing event is extracted and the sharing push space of each shopping commodity sharing event is determined. According to the method and the device, different shared characteristic sequences can be shared and added according to a plurality of shared pushing spaces to obtain a shared adding result, a shopping data sharing queue based on big data and an electronic mall platform is generated according to shopping commodity label information, and sharing configuration is carried out, so that shared access information and shared updating information are monitored, the sharing operation efficiency is improved, and the information accuracy in the sharing application process is further improved.

Description

Shopping data sharing method and system based on big data and electronic mall platform

Technical Field

The invention relates to the technical field of big data and electronic commerce, in particular to a shopping data sharing method and system based on big data and an electronic mall platform.

Background

With the rapid development of the internet, the communication between people is largely transferred to the social platform, so a great amount of supply and demand information is generated in the social process, but according to the prior art, it can be known that: the supply and demand information is scattered and disordered, the demand party cannot obtain quick and accurate supply information, the supplier cannot find a proper demand party and also cannot predict the available demand, so that purchasing, production and supply plans cannot be arranged, thereby the delay of various commodities and services to be sold in the market is caused, and the inconvenience in life is brought to the demand party.

Based on this, the targeted sharing of a large amount of shopping data becomes a selective behavior of a large number of users, how to reduce the time for other users to search for key commodities and save the calculation pressure and the pushing pressure of the server by a data sharing mode is a technical problem to be solved urgently.

Disclosure of Invention

In order to overcome at least the above-mentioned deficiencies in the prior art, an object of the present invention is to provide a shopping data sharing method and system based on big data and an electronic mall platform, which can divide shopping commodity sharing information in the shopping commodity tag information into a plurality of shopping commodity sharing events based on a sharing configuration service after generating the shopping commodity tag information, further extract a sharing feature sequence corresponding to each shopping commodity sharing event and determine a sharing push space of each shopping commodity sharing event. The method can share and add different sharing characteristic sequences according to a plurality of sharing pushing spaces to obtain sharing and adding results, and generates a shopping data sharing queue based on big data and an electronic mall platform according to shopping commodity label information and carries out sharing configuration so as to monitor sharing access information and sharing updating information. Therefore, correlation analysis can be carried out based on the shopping commodity label information, information sharing addition and confirmation can be automatically achieved through the shared pushing space, the information accuracy in the sharing application process is further improved while the sharing operation efficiency is improved, the time for other users to search for key commodities can be reduced through a data sharing mode, and the calculation pressure and the pushing pressure of the server are saved.

In a first aspect, the present invention provides a shopping data sharing method based on big data and an electronic mall platform, applied to a sharing server communicating with a user terminal, the method including:

generating corresponding shopping commodity label information according to the shopping order information initiated by the user terminal;

dividing shopping commodity sharing information in the shopping commodity label information into a plurality of shopping commodity sharing events based on a sharing configuration service;

the method comprises the steps of extracting sharing characteristics of each shopping commodity sharing event to obtain a sharing characteristic sequence corresponding to each shopping commodity sharing event, determining a sharing push space corresponding to each shopping commodity sharing event obtained through division, and sharing and adding each group of sharing characteristic sequences by adopting the sharing push space corresponding to each group of sharing characteristic sequences to obtain a sharing and adding result;

and when all the obtained sharing addition results are successfully added, generating a shopping data sharing queue based on big data and an electronic mall platform according to a sharing configuration object corresponding to all the sharing addition results, sharing and configuring the shopping data sharing queue based on the big data and the electronic mall platform, and monitoring sharing access information and sharing update information of the shopping data sharing queue based on the big data and the electronic mall platform.

In a possible implementation manner of the first aspect, generating corresponding shopping item tag information according to shopping order information initiated by the user terminal includes:

determining a plurality of shopping order browsing history information analyzed based on the shopping order information;

for current shopping order browsing history information in the plurality of shopping order browsing history information, determining browsing key business information of the current shopping order browsing history information in a key business segment based on a first browsing behavior frequency of the current shopping order browsing history information in the key business segment and a second browsing behavior frequency of each shopping order browsing history information in the plurality of shopping order browsing history information in the key business segment;

determining key business track information of the browsing history information of the current shopping order between two adjacent key business segments according to the browsing key business information of the browsing history information of the current shopping order in the two adjacent key business segments;

and extracting the shopping commodity label information from the shopping order information based on the key business track information.

In a possible implementation manner of the first aspect, dividing the shopping item sharing information in the shopping item tag information into a plurality of shopping item sharing events based on a sharing configuration service includes:

determining a plurality of shopping item sharing information in the shopping item tag information based on the sharing configuration service;

listing the sharing adding link parameters of the sharing information of each shopping commodity to establish a link parameter distribution queue; the link parameter distribution queue is a multi-stage queue, each stage of queue corresponds to one queue identifier, each queue identifier corresponds to at least one shared link parameter, and each stage of queue of the link parameter distribution queue has a conduction relation from a high priority to a low priority;

reading the shared configuration history information of the shared configuration service, and extracting a shared label list corresponding to the shared configuration service from the shared configuration history information according to the link parameter distribution queue;

establishing a mapping service between the shared label list and the link parameter distribution queue, and generating a shared addition event division list according to the mapping service; wherein, generating a sharing addition event partition list according to the mapping service comprises:

converting the shared label list into a plurality of shared label service node sequences, and respectively generating at least one shopping commodity shared event track characteristic of each shared label service node sequence;

acquiring non-repetitive shopping commodity sharing event track characteristics of the shared label list to form a shopping commodity sharing event transmission set, and mapping each shopping commodity sharing event track characteristic in the shopping commodity sharing event transmission set to the link parameter distribution queue to form a sharing addition event division list;

comparing the sharing adding link parameters contained in the sharing configuration history information of the sharing configuration service with the sharing adding link parameters in the sharing adding event division list one by one in sequence;

in the process of comparing one by one in sequence, if all sharing addition link parameters of the shopping commodity sharing event track characteristic are contained in the sharing configuration history information of the sharing configuration service, recording the shopping commodity sharing event track characteristic as an event dividing path of the sharing configuration service;

and dividing the shopping commodity sharing information into a plurality of shopping commodity sharing events according to each event dividing path of the sharing configuration service.

In a possible implementation manner of the first aspect, performing shared feature extraction on each shopping commodity shared event to obtain a shared feature sequence corresponding to each shopping commodity shared event, determining a shared pushing space corresponding to each shopping commodity shared event obtained by division, and performing shared addition on the group of shared feature sequences by using the shared pushing space corresponding to each group of shared feature sequences to obtain a shared addition result, including:

determining a sharing behavior event and a sharing extended event of each shopping commodity sharing event, and after the sharing behavior event and the sharing extended event are obtained, obtaining a first sharing added object of the sharing behavior event and a second sharing added object of the sharing extended event, wherein the sharing behavior event comprises first event tracing information, and the sharing extended event comprises second event tracing information;

acquiring an interactive shared adding data set in the first shared adding object and an interactive shared adding data set in the second shared adding object to obtain an interactive shared adding list;

determining an interactive sharing key value between any two associated data sets in the interactive sharing addition list to obtain interactive sharing key value distribution information;

adjusting the interaction sharing key values smaller than the preset interaction sharing key value in the interaction sharing key value distribution information into the preset interaction sharing key value to obtain modified interaction sharing key value distribution information;

extracting a sharing characteristic sequence corresponding to each shopping commodity sharing event according to the modified interactive sharing key value distribution information, the first event tracing information and the second event tracing information;

determining a shared pushing space corresponding to the sharing intensity from a plurality of preset databases according to the sharing intensity in the shared adding time sequence list of each shopping commodity sharing event; wherein the shopping commodity sharing event, the shared pushing space and the shared characteristic sequence are in one-to-one correspondence with each other;

determining shared addition index information between each group of shared characteristic sequences and a corresponding shared pushing space, and inquiring a shared matching information list corresponding to each group of shared characteristic sequences in the shared pushing space through the shared addition index information;

carrying out relevance comparison on each group of shared characteristic sequences and a corresponding shared matching information list to obtain a relevance value, and determining a shared adding result of each group of shared characteristic sequences according to the relevance value; and when the relevance value reaches the set relevance value, determining that the corresponding sharing addition result is successfully added.

In a possible implementation manner of the first aspect, generating a shopping data sharing queue based on big data and an electronic mall platform according to a sharing configuration object corresponding to all sharing addition results, and performing sharing configuration on the shopping data sharing queue based on big data and the electronic mall platform includes:

extracting a first label attribute, a second label attribute and a third label attribute in the shopping commodity label information; the first tag attribute is an attribute corresponding to the sharing duration of the shopping commodity tag information, the second tag attribute is an attribute corresponding to the sharing applicable object set of the shopping commodity tag information, and the third tag attribute is an attribute corresponding to the sharing form of the shopping commodity tag information;

determining first sentence vector coding information between a first sentence vector expression corresponding to the first tag attribute and a second sentence vector expression corresponding to the second tag attribute and second sentence vector coding information between a second sentence vector expression corresponding to the second tag attribute and a third sentence vector expression corresponding to the third tag attribute;

for the first tag attribute, updating the first tag attribute by taking the first sentence vector expression as reference according to the first sentence vector coding information to obtain a fourth tag attribute;

for the second tag attribute, updating the second tag attribute by taking the second sentence vector expression as reference according to the second sentence vector coding information to obtain a fifth tag attribute;

respectively carrying out verification service operation on the first label attribute and the second label attribute, the first label attribute and the fourth label attribute, the second label attribute and the third label attribute, and the second label attribute and the fifth label attribute to obtain a first verification service operation result, a second verification service operation result, a third verification service operation result and a fourth verification service operation result;

determining a first check service coverage between the first check service operation result and the second check service operation result and a second check service coverage between the third check service operation result and the fourth check service operation result;

judging whether the first check service coverage and the second check service coverage both fall into a coverage interval;

if yes, determining intersection allocation logic information for performing intersection allocation of a shared queue on the shopping commodity label information according to the first verification service operation result and the third verification service operation result, and performing attribute feature extraction on the first label attribute, the second label attribute and the third label attribute according to the intersection allocation logic information corresponding to the shopping commodity label information to obtain shared queue attribute features;

if not, respectively determining a first correlation difference and a second correlation difference between the coverage of the first check service and the coverage of the second check service and the coverage interval;

comparing the first relevance difference value with the second relevance difference value, when the first relevance difference value is smaller than the second relevance difference value, determining intersection allocation logic information for performing intersection allocation of a shared queue for the shopping commodity label information according to the first verification service operation result and the second verification service operation result, and performing attribute feature extraction on the first label attribute, the second label attribute and the third label attribute according to the intersection allocation logic information corresponding to the shopping commodity label information to obtain shared queue attribute features;

when the first correlation difference is larger than the second correlation difference, determining intersection allocation logic information for performing intersection allocation of a shared queue for the shopping commodity label information according to the third verification service operation result and the fourth verification service operation result, and performing attribute feature extraction on the first label attribute, the second label attribute and the third label attribute according to the intersection allocation logic information corresponding to the shopping commodity label information to obtain shared queue attribute features;

and performing shared queue intersection allocation on the shopping commodity label information based on the shared queue attribute characteristics to obtain a shopping data shared queue based on big data and an electronic mall platform, and performing shared configuration on the shopping data shared queue based on the big data and the electronic mall platform according to queue execution priority.

In a second aspect, an embodiment of the present invention further provides a shopping data sharing system based on big data and an electronic mall platform, which is applied to a sharing server communicating with a user terminal, where the system includes:

the generating module is used for generating corresponding shopping commodity label information according to the shopping order information initiated by the user terminal;

the dividing module is used for dividing the shopping commodity sharing information in the shopping commodity label information into a plurality of shopping commodity sharing events based on sharing configuration service;

the shared adding module is used for extracting shared features of each shopping commodity shared event to obtain a shared feature sequence corresponding to each shopping commodity shared event, determining a shared pushing space corresponding to each shopping commodity shared event obtained through division, and sharing and adding the shared feature sequences in the group by adopting the shared pushing space corresponding to each group of shared feature sequences to obtain a shared adding result;

and the shared configuration module is used for generating a shopping data sharing queue based on the big data and the electronic mall platform according to the shared configuration object corresponding to all the shared addition results when all the obtained shared addition results are successfully added, performing shared configuration on the shopping data sharing queue based on the big data and the electronic mall platform, and monitoring shared access information and shared update information of the shopping data sharing queue based on the big data and the electronic mall platform.

In a third aspect, an embodiment of the present invention further provides a sharing server, where the sharing server includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is configured to be communicatively connected to at least one user terminal, the machine-readable storage medium is configured to store a program, an instruction, or a code, and the processor is configured to execute the program, the instruction, or the code in the machine-readable storage medium to perform the shopping data sharing method based on big data and an e-mall platform in any one possible implementation manner of the first aspect or the first aspect.

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are executed, the computer executes the shopping data sharing method based on big data and an electronic mall platform in the first aspect or any one of the possible implementations of the first aspect.

Based on any one of the above aspects, in the embodiments of the present invention, after the shopping commodity label information is generated, the shopping commodity sharing information in the shopping commodity label information can be divided into a plurality of shopping commodity sharing events based on the sharing configuration service, and further, the sharing feature sequence corresponding to each shopping commodity sharing event is extracted and the sharing push space of each shopping commodity sharing event is determined. The method can share and add different sharing characteristic sequences according to a plurality of sharing pushing spaces to obtain sharing and adding results, and generates a shopping data sharing queue based on big data and an electronic mall platform according to shopping commodity label information and carries out sharing configuration so as to monitor sharing access information and sharing updating information. Therefore, correlation analysis can be carried out based on the shopping commodity label information, information sharing addition and confirmation can be automatically achieved through the shared pushing space, the information accuracy in the sharing application process is further improved while the sharing operation efficiency is improved, the time for other users to search for key commodities can be reduced through a data sharing mode, and the calculation pressure and the pushing pressure of the server are saved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

Fig. 1 is a schematic application scenario diagram of a shopping data sharing system based on big data and an electronic mall platform according to an embodiment of the present invention;

FIG. 2 is a schematic flowchart of a shopping data sharing method based on big data and an electronic mall platform according to an embodiment of the present invention;

FIG. 3 is a functional block diagram of a shopping data sharing system based on big data and an electronic mall platform according to an embodiment of the present invention;

fig. 4 is a schematic block diagram of a structure of a sharing server for implementing the shopping data sharing method based on big data and an electronic mall platform according to an embodiment of the present invention.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only examples or embodiments of the present description, and that for a person skilled in the art, the present description can also be applied to other similar scenarios on the basis of these drawings without inventive effort. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

It should be understood that "system", "unit" and/or "module" as used in this specification is a method for distinguishing different components, elements, parts or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.

As used in this specification and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

Flow charts are used in this description to illustrate operations performed by a system according to embodiments of the present description. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.

FIG. 1 is an interaction diagram of a shopping data sharing system 10 based on big data and an electronic mall platform according to an embodiment of the present invention. The shopping data sharing system 10 based on big data and electronic mall platform may include a sharing server 100 and a user terminal 200 communicatively connected with the sharing server 100. The big data and electronic mall platform based shopping data sharing system 10 shown in fig. 1 is only one possible example, and in other possible embodiments, the big data and electronic mall platform based shopping data sharing system 10 may include only a part of the components shown in fig. 1 or may also include other components.

In this embodiment, the sharing server 100 and the user terminal 200 in the shopping data sharing system 10 based on the big data and the e-mall platform can cooperatively perform the shopping data sharing method based on the big data and the e-mall platform described in the following method embodiments, and the following detailed description of the method embodiments can be referred to for the specific steps performed by the sharing server 100 and the user terminal 200.

To solve the technical problem in the foregoing background art, fig. 2 is a flowchart illustrating a shopping data sharing method based on big data and an electronic mall platform according to an embodiment of the present invention, where the shopping data sharing method based on big data and an electronic mall platform according to the present embodiment may be executed by the sharing server 100 shown in fig. 1, and the shopping data sharing method based on big data and an electronic mall platform is described in detail below.

Step S110, generating corresponding shopping item label information according to the shopping order information initiated by the user terminal 200.

Step S120, the shopping commodity sharing information in the shopping commodity label information is divided into a plurality of shopping commodity sharing events based on the sharing configuration service.

Step S130, performing shared feature extraction on each shopping commodity shared event to obtain a shared feature sequence corresponding to each shopping commodity shared event, determining a shared pushing space corresponding to each shopping commodity shared event obtained through division, and performing shared addition on the group of shared feature sequences by adopting the shared pushing space corresponding to each group of shared feature sequences to obtain a shared addition result.

Step S140, when all the obtained sharing addition results are successfully added, a shopping data sharing queue based on the big data and the electronic mall platform is generated according to the sharing configuration objects corresponding to all the sharing addition results, sharing configuration is carried out on the shopping data sharing queue based on the big data and the electronic mall platform, and sharing access information and sharing update information of the shopping data sharing queue based on the big data and the electronic mall platform are monitored.

In this embodiment, during the use of the shopping service, the user terminal 200 may generate many shopping behaviors, such as, but not limited to, a click behavior, a browsing behavior, a sharing adding behavior, and the like. When the user terminal 200 initiates the shopping order information, corresponding shopping item tag information may be generated.

In this embodiment, the shopping commodity sharing event may be understood as a sharing event in a single shopping process, and a plurality of shopping commodity sharing events may be generated in the using process of the shopping service.

In this embodiment, the sharing feature may be understood as attribute field information of each record included in each shopping commodity sharing event.

Based on the above steps, after the shopping commodity label information is generated, the present embodiment can divide the shopping commodity sharing information in the shopping commodity label information into a plurality of shopping commodity sharing events based on the sharing configuration service, and further extract the sharing feature sequence corresponding to each shopping commodity sharing event and determine the sharing push space of each shopping commodity sharing event. The method can share and add different sharing characteristic sequences according to a plurality of sharing pushing spaces to obtain sharing and adding results, and generates a shopping data sharing queue based on big data and an electronic mall platform according to shopping commodity label information and carries out sharing configuration so as to monitor sharing access information and sharing updating information. Therefore, correlation analysis can be carried out based on the shopping commodity label information, information sharing addition and confirmation can be automatically achieved through the shared pushing space, the information accuracy in the sharing application process is further improved while the sharing operation efficiency is improved, the time for other users to search for key commodities can be reduced through a data sharing mode, and the calculation pressure and the pushing pressure of the server are saved.

In one possible implementation manner, for step S110, in the process of generating corresponding shopping item label information according to the shopping order information initiated by the user terminal 200, the following exemplary sub-steps may be implemented.

Substep S111 determines a plurality of shopping order browsing history information parsed based on the shopping order information.

And a substep S112, determining browsing key business information of the current shopping order browsing history information in the key business segment based on a first browsing behavior frequency of the current shopping order browsing history information in the key business segment and a second browsing behavior frequency of each shopping order browsing history information in the plurality of shopping order browsing history information in the key business segment, aiming at the current shopping order browsing history information in the plurality of shopping order browsing history information.

And a substep S113, determining key business track information of the browsing history information of the current shopping order between two adjacent key business segments according to the browsing key business information of the browsing history information of the current shopping order in the two adjacent key business segments.

And a substep S114 of extracting the shopping commodity label information from the shopping order information based on the key business track information.

Based on the substeps, in the process of extracting the shopping commodity label information, the embodiment also considers the associated shopping order browsing history information, and further tracks and identifies the key information based on the browsing behavior frequency, so that the accuracy of the extracted shopping commodity label information is improved.

In one possible implementation, with respect to step S120, in dividing the shopping item sharing information in the shopping item tag information into a plurality of shopping item sharing events based on the sharing configuration service, the following exemplary sub-steps may be implemented.

The substep S121 determines a plurality of shopping item sharing information among the shopping item tag information based on the sharing configuration service.

And a substep S122, listing the sharing and adding link parameters of the sharing information of the shopping commodities so as to establish a link parameter distribution queue.

The link parameter distribution queue is a multi-stage queue, each stage of queue corresponds to one queue identifier, each queue identifier corresponds to at least one shared added link parameter, and each stage of queue of the link parameter distribution queue has a conduction relation from a high priority to a low priority.

And a substep S123 of reading the shared configuration history information of the shared configuration service, and extracting a shared tag list corresponding to the shared configuration service from the shared configuration history information according to the link parameter distribution queue.

And a substep S124, establishing a mapping service between the shared label list and the link parameter distribution queue, and generating a shared addition event partition list according to the mapping service.

For example, the shared tag list may be converted into a plurality of shared tag service node sequences, and at least one shopping commodity sharing event track feature of each shared tag service node sequence may be generated.

Then, obtaining the non-repetitive shopping commodity sharing event track characteristics of the sharing label list to form a shopping commodity sharing event transmission set, mapping each shopping commodity sharing event track characteristic in the shopping commodity sharing event transmission set to a link parameter distribution queue, and forming a sharing addition event division list.

On the basis, the sharing and adding link parameters contained in the sharing and configuring historical information of the sharing and configuring service are compared with the sharing and adding link parameters in the sharing and adding event dividing list one by one in sequence. In the process of comparing one by one in sequence, if all sharing addition link parameters of the shopping commodity sharing event track characteristic are contained in the sharing configuration history information of the sharing configuration service, recording the shopping commodity sharing event track characteristic as an event dividing path of the sharing configuration service. In this way, the shopping commodity sharing information can be divided into a plurality of shopping commodity sharing events according to the event division paths of the sharing configuration service.

In a possible implementation manner, for step S130, in the process of performing shared feature extraction on each shopping commodity shared event to obtain a shared feature sequence corresponding to each shopping commodity shared event, determining a shared pushing space corresponding to each shopping commodity shared event obtained through division, and performing shared addition on the group of shared feature sequences by using the shared pushing space corresponding to each group of shared feature sequences to obtain a shared addition result, the following exemplary sub-steps may be implemented.

And a substep S131, determining a sharing behavior event and a sharing extension event of each shopping commodity sharing event, and acquiring a first sharing addition object of the sharing behavior event and a second sharing addition object of the sharing extension event after acquiring the sharing behavior event and the sharing extension event.

The shared behavior event comprises first event tracing information, and the shared extended event comprises second event tracing information.

And a substep S132, obtaining an interactive sharing addition data set in the first sharing addition object and an interactive sharing addition data set in the second sharing addition object to obtain an interactive sharing addition list.

And a substep S133, determining an interaction sharing key value between any two associated data sets in the interaction sharing addition list, and obtaining interaction sharing key value distribution information.

And a substep S134, adjusting the interactive sharing key value smaller than the preset interactive sharing key value in the interactive sharing key value distribution information to the preset interactive sharing key value, so as to obtain modified interactive sharing key value distribution information.

And a substep S135, extracting a sharing characteristic sequence corresponding to each shopping commodity sharing event according to the modified interactive sharing key value distribution information, the first event tracing information and the second event tracing information.

And a substep S136, determining a shared pushing space corresponding to the shared intensity from a plurality of preset databases according to the shared intensity in the shared adding time sequence list of each shopping commodity shared event. The shopping commodity sharing event, the sharing pushing space and the sharing characteristic sequence are in one-to-one correspondence with each other.

And a substep S137, determining shared added index information between each group of shared feature sequences and the corresponding shared pushing space, and querying a shared matching information list corresponding to each group of shared feature sequences in the shared pushing space through the shared added index information.

And a substep S138, comparing the relevance of each group of shared characteristic sequences with the corresponding shared matching information list to obtain a relevance value, and determining the shared addition result of each group of shared characteristic sequences according to the relevance value.

And when the relevance value reaches the set relevance value, determining that the corresponding sharing addition result is successfully added.

In a possible implementation manner, for step S140, in the process of generating a shopping data sharing queue based on big data and an electronic mall platform according to the sharing configuration object corresponding to all sharing addition results, and performing sharing configuration on the shopping data sharing queue based on big data and the electronic mall platform, the following exemplary sub-steps may be implemented.

The substep S141 is to extract a first tag attribute, a second tag attribute, and a third tag attribute from the shopping item tag information. The first tag attribute is an attribute corresponding to the sharing duration of the shopping commodity tag information, the second tag attribute is an attribute corresponding to the sharing applicable object set of the shopping commodity tag information, and the third tag attribute is an attribute corresponding to the sharing form of the shopping commodity tag information.

In the substep S142, first sentence vector coding information between the first sentence vector expression corresponding to the first tag attribute and the second sentence vector expression corresponding to the second tag attribute and second sentence vector coding information between the second sentence vector expression corresponding to the second tag attribute and the third sentence vector expression corresponding to the third tag attribute are determined.

And a substep S143, for the first tag attribute, updating the first tag attribute according to the first sentence vector coding information with the first sentence vector expression as a reference to obtain a fourth tag attribute, and for the second tag attribute, updating the second tag attribute according to the second sentence vector coding information with the second sentence vector expression as a reference to obtain a fifth tag attribute.

And a substep S144, performing verification service operation on the first tag attribute and the second tag attribute, the first tag attribute and the fourth tag attribute, the second tag attribute and the third tag attribute, and the second tag attribute and the fifth tag attribute respectively to obtain a first verification service operation result, a second verification service operation result, a third verification service operation result, and a fourth verification service operation result.

The substep S145 determines a first checking service coverage between the first checking service operation result and the second checking service operation result and a second checking service coverage between the third checking service operation result and the fourth checking service operation result.

And a substep S146 of determining whether the first check service coverage and the second check service coverage both fall within the coverage interval. If the first check service coverage and the second check service coverage both fall into the coverage interval, determining intersection allocation logic information for performing intersection allocation of the shared queue aiming at the shopping commodity label information according to the first check service operation result and the third check service operation result, and performing attribute feature extraction on the first label attribute, the second label attribute and the third label attribute according to the intersection allocation logic information corresponding to the shopping commodity label information to obtain shared queue attribute features. And if the first check service coverage and the second check service coverage do not fall into the coverage interval, respectively determining a first association difference and a second association difference between the first check service coverage and the coverage interval and between the second check service coverage and the coverage interval.

And a substep S147, comparing the first correlation difference value with the second correlation difference value, determining intersection allocation logic information for performing intersection allocation of the shared queue for the shopping commodity label information according to the first verification service operation result and the second verification service operation result when the first correlation difference value is smaller than the second correlation difference value, and performing attribute feature extraction on the first label attribute, the second label attribute and the third label attribute according to the intersection allocation logic information corresponding to the shopping commodity label information to obtain shared queue attribute features.

And a substep S148, when the first correlation difference is greater than the second correlation difference, determining intersection allocation logic information for performing intersection allocation of the shared queue for the shopping commodity label information according to the third verification service operation result and the fourth verification service operation result, and performing attribute feature extraction on the first label attribute, the second label attribute and the third label attribute according to the intersection allocation logic information corresponding to the shopping commodity label information to obtain shared queue attribute features.

And S149, performing shared queue intersection allocation on the shopping commodity label information based on the shared queue attribute characteristics to obtain a shopping data shared queue based on the big data and the electronic mall platform, and performing shared configuration on the shopping data shared queue based on the big data and the electronic mall platform according to the queue execution priority.

Fig. 3 is a schematic functional module diagram of a shopping data sharing system 300 based on big data and an electronic mall platform according to an embodiment of the present invention, and in this embodiment, functional modules of the shopping data sharing system 300 based on big data and an electronic mall platform may be divided according to the method embodiment executed by the sharing server 100, that is, the following functional modules corresponding to the shopping data sharing system 300 based on big data and an electronic mall platform may be used to execute the method embodiments executed by the sharing server 100. The shopping data sharing system 300 based on big data and electronic mall platform may include a generating module 310, a dividing module 320, a sharing adding module 330 and a sharing configuration module 340, and the functions of the functional modules of the shopping data sharing system 300 based on big data and electronic mall platform are described in detail below.

The generating module 310 is configured to generate corresponding shopping commodity label information according to the shopping order information initiated by the user terminal 200. The generating module 310 may be configured to execute the step S110, and the detailed implementation of the generating module 310 may refer to the detailed description of the step S110.

A dividing module 320, configured to divide the shopping commodity sharing information in the shopping commodity label information into a plurality of shopping commodity sharing events based on the sharing configuration service. The dividing module 320 may be configured to perform the step S120, and the detailed implementation of the dividing module 320 may refer to the detailed description of the step S120.

The sharing and adding module 330 is configured to extract a sharing feature of each shopping commodity sharing event to obtain a sharing feature sequence corresponding to each shopping commodity sharing event, determine a sharing push space corresponding to each shopping commodity sharing event obtained through division, and share and add the group of sharing feature sequences by using the sharing push space corresponding to each group of sharing feature sequences to obtain a sharing and adding result. The sharing and adding module 330 may be configured to perform the step S130, and the detailed implementation of the sharing and adding module 330 may refer to the detailed description of the step S130.

And the sharing configuration module 340 is configured to, when all the obtained sharing addition results are successfully added, generate a shopping data sharing queue based on the big data and the electronic mall platform according to the sharing configuration object corresponding to all the sharing addition results, share and configure the shopping data sharing queue based on the big data and the electronic mall platform, and monitor sharing access information and sharing update information of the shopping data sharing queue based on the big data and the electronic mall platform. The sharing configuration module 340 may be configured to perform the step S140, and the detailed implementation manner of the sharing configuration module 340 may refer to the detailed description of the step S140.

In a possible implementation manner, the generating module 310 is specifically configured to:

and determining a plurality of shopping order browsing history information analyzed based on the shopping order information.

And determining browsing key business information of the current shopping order browsing history information in the key business segment based on a first browsing behavior frequency of the current shopping order browsing history information in the key business segment and a second browsing behavior frequency of each piece of shopping order browsing history information in the plurality of shopping order browsing history information in the key business segment aiming at the current shopping order browsing history information in the plurality of shopping order browsing history information.

And determining key business track information of the browsing history information of the current shopping order between two adjacent key business segments according to the browsing key business information of the browsing history information of the current shopping order in the two adjacent key business segments.

In a possible implementation manner, the dividing module 320 is specifically configured to:

a plurality of shopping item sharing information in the shopping item tag information is determined based on the sharing configuration service.

And listing the sharing addition link parameters of the sharing information of the shopping commodities to establish a link parameter distribution queue. The link parameter distribution queue is a multi-stage queue, each stage of queue corresponds to one queue identifier, each queue identifier corresponds to at least one shared added link parameter, and each stage of queue of the link parameter distribution queue has a conduction relation from a high priority to a low priority.

Reading the shared configuration history information of the shared configuration service, and extracting a shared label list corresponding to the shared configuration service from the shared configuration history information according to the link parameter distribution queue.

And establishing a mapping service between the shared label list and the link parameter distribution queue, and generating a shared addition event division list according to the mapping service. Wherein, generating a sharing addition event partition list according to the mapping service comprises:

and converting the shared label list into a plurality of shared label service node sequences, and respectively generating at least one shopping commodity shared event track characteristic of each shared label service node sequence.

Obtaining the non-repetitive shopping commodity sharing event track characteristics of the sharing label list to form a shopping commodity sharing event transmission set, mapping each shopping commodity sharing event track characteristic in the shopping commodity sharing event transmission set to a link parameter distribution queue, and forming a sharing addition event division list.

And comparing the sharing adding link parameters contained in the sharing configuration history information of the sharing configuration service with the sharing adding link parameters in the sharing adding event division list one by one in sequence.

In the process of comparing one by one in sequence, if all sharing addition link parameters of the shopping commodity sharing event track characteristic are contained in the sharing configuration history information of the sharing configuration service, recording the shopping commodity sharing event track characteristic as an event dividing path of the sharing configuration service.

And dividing the shopping commodity sharing information into a plurality of shopping commodity sharing events according to each event division path of the sharing configuration service.

In a possible implementation manner, the sharing adding module 330 is specifically configured to:

determining a sharing behavior event and a sharing extended event of each shopping commodity sharing event, and after the sharing behavior event and the sharing extended event are obtained, obtaining a first sharing added object of the sharing behavior event and a second sharing added object of the sharing extended event, wherein the sharing behavior event comprises first event tracing information, and the sharing extended event comprises second event tracing information.

And acquiring an interactive shared adding data set in the first shared adding object and an interactive shared adding data set in the second shared adding object to obtain an interactive shared adding list.

And determining an interactive shared key value between any two associated data sets in the interactive shared addition list to obtain interactive shared key value distribution information.

And adjusting the interactive sharing key value smaller than the preset interactive sharing key value in the interactive sharing key value distribution information to be the preset interactive sharing key value to obtain the modified interactive sharing key value distribution information.

And extracting a sharing characteristic sequence corresponding to each shopping commodity sharing event according to the modified interactive sharing key value distribution information, the first event tracing information and the second event tracing information.

And determining a shared pushing space corresponding to the sharing strength from a plurality of preset databases according to the sharing strength in the sharing adding time sequence list of each shopping commodity sharing event. The shopping commodity sharing event, the sharing pushing space and the sharing characteristic sequence are in one-to-one correspondence with each other.

And determining shared addition index information between each group of shared characteristic sequences and the corresponding shared pushing space, and inquiring a shared matching information list corresponding to each group of shared characteristic sequences in the shared pushing space through the shared addition index information.

And comparing the relevance of each group of shared characteristic sequences with the corresponding shared matching information list to obtain a relevance value, and determining the shared addition result of each group of shared characteristic sequences according to the relevance value. And when the relevance value reaches the set relevance value, determining that the corresponding sharing addition result is successfully added.

In a possible implementation manner, the shared configuration module 340 is specifically configured to:

and extracting a first label attribute, a second label attribute and a third label attribute in the shopping commodity label information. The first tag attribute is an attribute corresponding to the sharing duration of the shopping commodity tag information, the second tag attribute is an attribute corresponding to the sharing applicable object set of the shopping commodity tag information, and the third tag attribute is an attribute corresponding to the sharing form of the shopping commodity tag information.

And determining first sentence vector coding information between a first sentence vector expression corresponding to the first tag attribute and a second sentence vector expression corresponding to the second tag attribute and second sentence vector coding information between a second sentence vector expression corresponding to the second tag attribute and a third sentence vector expression corresponding to the third tag attribute.

And aiming at the first tag attribute, updating the first tag attribute by taking the first sentence vector expression as reference according to the first sentence vector coding information to obtain a fourth tag attribute.

And aiming at the second tag attribute, updating the second tag attribute by taking the second sentence vector expression as reference according to the second sentence vector coding information to obtain a fifth tag attribute.

And respectively carrying out verification service operation on the first label attribute and the second label attribute, the first label attribute and the fourth label attribute, the second label attribute and the third label attribute, and the second label attribute and the fifth label attribute to obtain a first verification service operation result, a second verification service operation result, a third verification service operation result and a fourth verification service operation result.

And determining a first check service coverage between the first check service operation result and the second check service operation result and a second check service coverage between the third check service operation result and the fourth check service operation result.

And judging whether the first check service coverage and the second check service coverage both fall into the coverage interval.

If yes, determining intersection distribution logic information for performing intersection distribution of the shared queue aiming at the shopping commodity label information according to the first verification service operation result and the third verification service operation result, and performing attribute feature extraction on the first label attribute, the second label attribute and the third label attribute according to the intersection distribution logic information corresponding to the shopping commodity label information to obtain shared queue attribute features.

If not, respectively determining a first correlation difference and a second correlation difference between the coverage of the first check service and the coverage of the second check service and the coverage interval.

And comparing the difference value of the first relevance degree with the difference value of the second relevance degree, determining intersection distribution logic information for performing intersection distribution on the shopping commodity label information according to the first verification service operation result and the second verification service operation result when the difference value of the first relevance degree is smaller than the difference value of the second relevance degree, and performing attribute feature extraction on the first label attribute, the second label attribute and the third label attribute according to the intersection distribution logic information corresponding to the shopping commodity label information to obtain the attribute feature of the shared queue.

And when the first correlation difference is larger than the second correlation difference, determining intersection distribution logic information for performing intersection distribution of the shared queue on the shopping commodity label information according to a third verification service operation result and a fourth verification service operation result, and performing attribute feature extraction on the first label attribute, the second label attribute and the third label attribute according to the intersection distribution logic information corresponding to the shopping commodity label information to obtain shared queue attribute features.

And performing shared queue intersection distribution on the shopping commodity label information based on the shared queue attribute characteristics to obtain a shopping data shared queue based on the big data and the electronic mall platform, and performing shared configuration on the shopping data shared queue based on the big data and the electronic mall platform according to the queue execution priority.

It should be noted that the division of the modules of the above system is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the generating module 310 may be a processing element separately set up, or may be implemented by being integrated into a chip of the system, or may be stored in a memory of the system in the form of program code, and the function of the generating module 310 may be called and executed by a processing element of the system. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can call program code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).

Fig. 4 is a schematic diagram illustrating a hardware structure of a sharing server 100 for implementing the shopping data sharing method based on big data and an electronic mall platform according to an embodiment of the present invention, where as shown in fig. 4, the sharing server 100 may include a processor 110, a machine-readable storage medium 120, a bus 130, and a transceiver 140.

In a specific implementation process, the at least one processor 110 executes computer-executable instructions stored in the machine-readable storage medium 120 (for example, the shopping data sharing system 300 based on big data and electronic mall platform shown in fig. 3 includes a generating module 310, a dividing module 320, a sharing adding module 330, and a sharing configuration module 340), so that the processor 110 may execute the shopping data sharing method based on big data and electronic mall platform according to the above method embodiment, where the processor 110, the machine-readable storage medium 120, and the transceiver 140 are connected through the bus 130, and the processor 110 may be configured to control transceiving actions of the transceiver 140, so as to transceive data with the aforementioned user terminal 200.

For a specific implementation process of the processor 110, reference may be made to the above-mentioned method embodiments executed by the shared server 100, which implement principles and technical effects similar to each other, and this embodiment is not described herein again.

In the embodiment shown in fig. 4, it should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.

The machine-readable storage medium 120 may comprise high-speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory.

The bus 130 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus 130 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the buses in the figures of the present invention are not limited to only one bus or one type of bus.

In addition, the embodiment of the invention also provides a readable storage medium, wherein the readable storage medium stores computer execution instructions, and when a processor executes the computer execution instructions, the shopping data sharing method based on big data and the electronic mall platform is realized.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.

Also, the description uses specific words to describe embodiments of the description. Such as "one possible implementation," "one possible example," and/or "exemplary" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "one possible implementation," "one possible example," and/or "exemplary" in various places throughout this specification are not necessarily referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.

Claims

1. A shopping data sharing method based on big data and an electronic mall platform is applied to a sharing server communicating with a user terminal, and the method comprises the following steps:

2. The shopping data sharing method based on big data and the electronic mall platform according to claim 1, wherein the generating of the corresponding shopping commodity label information according to the shopping order information initiated by the user terminal comprises:

3. The shopping data sharing method based on big data and electronic mall platform according to claim 1, wherein the dividing of the shopping commodity sharing information in the shopping commodity label information into a plurality of shopping commodity sharing events based on sharing configuration service comprises:

4. The shopping data sharing method based on big data and an electronic mall platform according to claim 3, wherein the sharing feature extraction is performed on each shopping commodity sharing event to obtain a sharing feature sequence corresponding to each shopping commodity sharing event, the sharing push space corresponding to each shopping commodity sharing event obtained through division is determined, and the sharing push space corresponding to each group of sharing feature sequences is adopted to share and add the group of sharing feature sequences to obtain a sharing and adding result, comprising:

5. The shopping data sharing method based on big data and the electronic mall platform according to claim 1, wherein the step of generating a shopping data sharing queue based on big data and the electronic mall platform according to the sharing configuration object corresponding to all the sharing addition results, and sharing and configuring the shopping data sharing queue based on big data and the electronic mall platform comprises:

6. A shopping data sharing system based on big data and an electronic mall platform is applied to a sharing server communicating with a user terminal, and the system comprises:

7. The big data and electronic mall platform based shopping data sharing system according to claim 6, wherein the generating module is specifically configured to:

8. The big data and electronic mall platform based shopping data sharing system according to claim 6, wherein the dividing module is specifically configured to:

9. The big data and electronic mall platform based shopping data sharing system according to claim 7, wherein the sharing adding module is specifically configured to:

10. The big data and electronic mall platform based shopping data sharing system according to claim 6, wherein the sharing configuration module is specifically configured to: