CN110827049A - Data pushing method and device - Google Patents
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- CN110827049A CN110827049A CN201810901271.2A CN201810901271A CN110827049A CN 110827049 A CN110827049 A CN 110827049A CN 201810901271 A CN201810901271 A CN 201810901271A CN 110827049 A CN110827049 A CN 110827049A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
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Abstract
The application discloses a data pushing method and a device, wherein the method comprises the following steps: capturing commodity parameters of any commodity from an e-commerce platform; the commodity parameter is used for indicating attribute information of a commodity; extracting a brand field indicating the brand of the commodity and a comment keyword field evaluating the commodity from the commodity parameter; determining commodities with the same brand fields as similar commodities, and associating comment keyword fields of the similar commodities with the brand fields of the similar commodities; and pushing the associated comment keyword field and brand field to the user. The technical problems that the existing E-commerce platform provides the purchase opinions of the commodities, the reference opinions are not comprehensive enough, and the reference performance is not high are solved.
Description
Technical Field
The present application relates to the field of electronic technologies, and in particular, to a data pushing method and apparatus.
Background
With the continuous development of network and internet technologies, the internet data is explosively increased, the data amount stored by each internet platform is huge, and when a user screens commodities needing to be purchased on the e-commerce platform based on certain keywords, the data expression modes are different due to different types of data stored by each internet platform, and the commodity parameters of each e-commerce platform are not standardized enough; therefore, the current e-commerce platform can only search a plurality of discrete reference information for the user on the platform of the e-commerce platform based on the keywords input by the user.
The e-commerce platform provides the purchase opinions for the user only aiming at a certain commodity based on the implementation mode, and the purchase opinions are only provided discretely based on the analysis of discrete commodity evaluation information in the e-commerce platform, so that the technical problems that the reference opinions are not comprehensive enough and the reference performance is not high exist.
Disclosure of Invention
The application provides a data pushing method and device, which are used for solving the technical problems that reference opinions are not comprehensive enough and reference performance is not high when the conventional E-commerce platform provides purchase opinions of commodities.
In a first aspect, the present application provides a data pushing method, including:
capturing commodity parameters of any commodity from an e-commerce platform; the commodity parameter is used for indicating attribute information of a commodity;
extracting a brand field indicating the brand of the commodity and a comment keyword field evaluating the commodity from the commodity parameter;
determining commodities with the same brand fields as similar commodities, and associating comment keyword fields of the similar commodities with the brand fields of the similar commodities;
and pushing the associated comment keyword field and brand field to the user.
The method provided by the embodiment of the application analyzes and divides parameters of certain commodity category in detail, analyzes the comment keywords of each commodity, obtains the advantages and the disadvantages of each brand in the commodity category, and provides more reliable purchase suggestions from the brand of the commodity to specific commodities for users.
In one possible implementation, pushing the associated comment keyword field and brand field to the user includes:
determining the occurrence frequency of each comment keyword associated with the same brand field, and obtaining the sequencing result of the comment keywords associated with the same brand field according to the occurrence frequency;
forming a comment keyword word cloud picture according to the sequencing result;
and pushing the cloud image of the comment keywords to the user.
In one possible embodiment, the merchandise parameters include: at least one of function description parameters, price parameters, user comment keywords and user comment information of the commodity.
In a possible implementation, before extracting a brand field indicating the brand of the commodity and a comment keyword field evaluating the commodity from the commodity parameters, the method further includes:
preprocessing the commodity parameters:
and converting the commodity parameters after pretreatment into standard data meeting preset rules according to preset conversion standards.
In a possible embodiment, the pre-processing the commodity parameter includes:
judging whether the commodity parameters include price parameters or not, and if not, deleting the commodity parameters;
and classifying the commodity parameters according to the model parameters of each commodity in the commodity parameters.
According to the method provided by the embodiment of the application, data of the same field and different formats are converted into a uniform format by carrying out data standardization cleaning on commodity parameters, and a comment keyword word cloud picture is established for each brand, so that the advantages and the disadvantages of a certain brand in the commodity category are obtained, more comprehensive, accurate and visual guidance suggestions are provided for the purchasing behavior of a user, and the use experience of the user is improved.
In a second aspect, an apparatus for pushing data is provided, including:
the grabbing unit is used for grabbing commodity parameters of a commodity class of commodities from the E-commerce platform; the commodity parameter is used for indicating attribute information of a commodity;
an extracting unit configured to extract a brand field indicating a brand of the commodity and a comment keyword field evaluating the commodity from the commodity parameter;
the association unit is used for determining the commodities with the same brand fields as the same-class commodities and associating the comment keyword fields of the same-class commodities with the brand fields of the same-class commodities;
and the pushing unit is used for pushing the associated comment keyword field and the associated brand field to the user.
In a possible implementation manner, the pushing unit is specifically configured to determine the occurrence number of each comment keyword associated with a same brand field, and obtain a ranking result of the comment keywords associated with the same brand field according to the occurrence number; forming a comment keyword word cloud picture according to the sequencing result; and pushing the cloud image of the comment keywords to the user.
In one possible embodiment, the merchandise parameters include: at least one of function description parameters, price parameters, user comment keywords and user comment information of the commodity.
In a possible implementation manner, the extraction unit is specifically configured to pre-process the commodity parameters: and converting the commodity parameters after pretreatment into standard data meeting preset rules according to preset conversion standards.
In a possible embodiment, the extracting unit pre-processes the commodity parameters, including:
judging whether the commodity parameters include price parameters or not, and if not, deleting the commodity parameters;
and classifying the commodity parameters according to the model parameters of each commodity in the commodity parameters.
In a third aspect, the present application provides a computing device comprising:
at least one processor, and
a memory communicatively coupled to the at least one processor, a communication interface;
wherein the memory stores instructions executable by the at least one processor, and the at least one processor performs the method of any one of the possible embodiments of the first aspect using the communication interface by executing the instructions stored by the memory.
In a fourth aspect, the present application provides a computer-readable storage medium storing computer instructions that, when executed on a computer, cause the computer to perform the method of any one of the possible implementations of the first aspect.
The beneficial effect of this application is as follows:
according to the data pushing method and the data pushing device, the advantages and the disadvantages of each brand in a certain type of commodity (namely the same brand of commodity) are analyzed, all information of the same brand is gathered and then pushed to the user, the user can obtain detailed information of the commodity to be purchased from the overall evaluation of the brand and further specific commodity information, and therefore the user can obtain reasonable suggestions of the commodity to be purchased more clearly and simply.
Drawings
Fig. 1 is a schematic flowchart of a data pushing method according to an embodiment of the present application;
fig. 2 is a schematic flowchart of an implementation method for pushing a related comment keyword field and a brand field to a user according to an embodiment of the present application;
FIG. 3 is a schematic flow chart of a method used in conjunction with a specific example of a method provided by an embodiment of the present application;
fig. 4 is a schematic structural diagram of a device for pushing data according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a computing device according to an embodiment of the present application.
Detailed Description
When the e-commerce platform pushes the purchase opinion information of commodities to the user based on the prior art, the pushed information is in a discrete mode, so that the technical problems that reference opinions are not comprehensive enough and the reference performance is not high exist.
Based on the problems in the prior art, an embodiment of the present application provides a data pushing method, and an implementation idea of the method is:
capturing commodity parameters of any commodity from an e-commerce platform; the commodity parameter is used for indicating attribute information of a commodity; extracting a brand field indicating the brand of the commodity and a comment keyword field evaluating the commodity from the commodity parameter; determining commodities with the same brand fields as similar commodities, and associating comment keyword fields of the similar commodities with the brand fields of the similar commodities; and pushing the associated comment keyword field and brand field to the user.
Because the current e-commerce platform only analyzes a specific commodity and does not analyze the commonalities, namely the brand properties, held by the commodity, the collected and finally presented commodity information is too discrete to give correct instructive suggestions to the user for purchasing a certain brand of commodity.
The method provided by the embodiment of the application analyzes the advantages and the disadvantages of a certain type of commodity (namely the same brand of commodity), and then summarizes all information of the same brand of commodity and then pushes the summary to the user, so that the user can obtain detailed purchase suggestions of the commodity to be purchased from the overall evaluation of the brand, further specific certain type and information of a certain commodity.
In order to more clearly and specifically describe the solutions provided by the embodiments of the present application, the following describes the method and apparatus provided by the embodiments of the present application in further detail with reference to the accompanying drawings and specific application scenarios:
example one
A data pushing method provided in an embodiment of the present application is further described in detail below with reference to fig. 1 of the specification, and a specific implementation manner of the method may include the following steps:
step 101, capturing commodity parameters of any commodity from an e-commerce platform; the commodity parameter is used for indicating attribute information of a commodity;
because the data storage modes provided by the e-commerce platform are different, in order to obtain more comprehensive commodity parameter information, in the embodiment of the application, a crawler technology can be utilized to obtain commodity parameters on the e-commerce platform; the commodity parameter in the embodiment of the present application is commodity parameter information capable of providing instructive opinions for the purchasing activities of the user, and may include: at least one of function description parameters, price parameters, user comment keywords and user comment information of the commodity.
102, extracting a brand field indicating the brand of the commodity and a comment keyword field evaluating the commodity from the commodity parameters;
103, determining commodities with the same brand fields as similar commodities, and associating the comment keyword fields of the similar commodities with the brand fields of the similar commodities;
and 104, pushing the related comment keyword field and brand field to the user.
In this embodiment of the present application, in order to more intuitively push the obtained commodity information (the keyword field and the brand field) to the user, a specific implementation manner of pushing the associated comment keyword field and the brand field to the user in this embodiment may be (the method flow steps are shown in fig. 2):
since the number of occurrences of the comment keyword reflects the actual usage of the product and the usage experience of the user to a large extent, in this embodiment, the number of occurrences of the comment keyword among the comment keywords provided by the user is sorted, and then the comment keyword having the largest number of occurrences is presented to the user based on the sorting result.
and step 203, pushing the cloud image of the comment keyword words to a user.
Based on the characteristic of a large and complicated commodity information in the existing e-commerce platform, in order to provide a concise and accurate push information for a user, before extracting a brand field indicating a brand of the commodity and a comment keyword field evaluating the commodity from the commodity parameters in step 102, the method provided by this embodiment may further include:
a1, preprocessing the commodity parameters:
in this embodiment, the main purpose of preprocessing the commodity parameters is to remove parameter items that may cause deviation in commodity evaluation from the commodity parameters, and the specific method includes:
in the first mode, since the price parameter is an important criterion when the user decides whether to purchase a commodity, the parameter is filtered: judging whether the commodity parameters include price parameters or not, and if not, deleting the commodity parameters; in addition, if the number of the acquired commodity parameters is less than the set threshold (that is, the acquired commodity parameters are less), the price parameters may be acquired again after determining that the current commodity parameters do not include the price parameters, and if the current commodity parameters do not include the price parameters, the commodity parameters are deleted.
In the second mode, since prices, evaluations, and the like of commodities of different models may be greatly different, for convenience of user reference, when parameters are screened: classifying the commodity parameters according to the model parameters of each commodity in the commodity parameters; for example: although the price of the refrigerator and the price of the refrigerator accessories belong to the same brand, the price and the evaluation have great difference; therefore, in the embodiment, the commodity parameters of the refrigerator and the refrigerator accessories can be classified, and mutual interference is avoided.
And A2, converting the preprocessed commodity parameters into standard data meeting preset rules according to preset conversion standards.
According to the method provided by the embodiment, data of the same field and different formats are converted into a uniform format by carrying out data standardization cleaning on commodity parameters, and a comment keyword word cloud picture is established for each brand, so that the advantages and the disadvantages of a certain brand in the commodity category are obtained, a more comprehensive, accurate and visual guidance suggestion is provided for the purchasing behavior of a user, and the use experience of the user is improved.
Example two
As shown in fig. 3, the method provided by the embodiment of the present application is further described in detail with reference to specific examples, and the specific implementation may be:
the commodity parameters include: basic parameters of the commodity (such as basic parameters of an air purifier with a purification mode, a timing function and the like), price, user comment keywords, favorable comment of a user, bad comment of the user and the like;
step 302, preprocessing the captured commodity parameters for improving the efficiency of data cleaning:
in this embodiment, the pre-processing mainly comprises: removing repeated punctuation, deleting illegal data, modifying wrongly written words, integrating data of the same field into a uniform data format, and the like.
Wherein: the specific implementation manner for deleting the illegal data can be that if the price in the commodity parameters is null or zero, the illegal data is deleted; in addition, according to a certain commodity parameter, determining that the target commodity corresponding to the commodity parameter is not in the same type as the certain type of commodity mentioned in the step 301, namely the target commodity is a part of the certain type of commodity, and deleting the certain commodity parameter; by deleting the commodity parameters corresponding to the commodity parts, the misjudgment of the user on the normal price of the commodity caused by the price of the commodity parts can be prevented.
in this embodiment, converting data into normalized data requires analyzing the data to be processed, and defining different rules according to different fields, and the specific implementation may be:
and 1, judging whether the field is a numerical field, and entering a numerical rule to remove and correct if the field is the numerical field. Specifically, the numerical rule may be: analyzing the numerical value, and forming a numerical value interval according to a certain data interval, wherein the price interval is divided into 0-999 price intervals if the price is 500; for example, if a certain product capacity is shown as 1L and other product capacities are shown as 1-3L, then 1L is merged into the interval of 1-3L.
And 2, judging whether the field is a text field, and if the field is the text field, entering a text rule for correcting and cleaning. Specifically, the text rule may be:
a, judging whether a text field is a brand field, if so, pre-establishing a brand dictionary, and uniformly converting the brands with Chinese and English meanings into Chinese;
b, judging whether the text field is a comment keyword field, if so, processing the comment keyword field to establish a comment keyword word cloud picture, and the specific method comprises the following steps:
reading the obtained comment keywords of each commodity, wherein each commodity may not contain the comment keywords or may contain one or more comment keywords, and gathering the comment keywords of each commodity according to different brands; and recording the occurrence frequency of each comment keyword in a certain brand, sequencing the comment keywords, and forming a comment keyword word cloud picture so as to observe the advantages and the disadvantages of each brand under the product type, thereby providing suggestions for users to purchase. To reduce the impact of default comments on data analysis, system default comments may be deleted in this embodiment.
According to the method provided by the embodiment of the application, parameters of certain commodity are analyzed and divided in detail, and the comment keywords of each commodity are analyzed, so that the advantages and the disadvantages of each brand in the commodity are obtained, and a more reliable purchase suggestion from the brand of the commodity to a specific commodity is provided for a user.
EXAMPLE III
As shown in fig. 4, an embodiment of the present application further provides a data pushing device, where the data pushing device specifically includes:
the grabbing unit 401 is used for grabbing commodity parameters of a commodity class of commodities from an e-commerce platform; the commodity parameter is used for indicating attribute information of a commodity;
optionally, the commodity parameters may include: at least one of function description parameters, price parameters, user comment keywords and user comment information of the commodity.
An extracting unit 402, configured to extract a brand field indicating a brand of the commodity and a comment keyword field evaluating the commodity from the commodity parameter;
optionally, the extracting unit 402 is specifically configured to perform preprocessing on the commodity parameters: and converting the commodity parameters after pretreatment into standard data meeting preset rules according to preset conversion standards.
Further, in order to ensure that the data used for the analysis is data that can assist the user in purchasing the product, the extracting unit pre-processes the product parameters, including:
judging whether the commodity parameters include price parameters or not, and if not, deleting the commodity parameters;
and classifying the commodity parameters according to the model parameters of each commodity in the commodity parameters.
An associating unit 403, configured to determine commodities with the same brand field as similar commodities, and associate a comment keyword field of the similar commodity with the brand field of the similar commodity;
and a pushing unit 404, configured to push the associated comment keyword field and brand field to the user.
Optionally, the pushing unit 404 is specifically configured to determine the occurrence frequency of each comment keyword associated with the same brand field, and obtain a ranking result of the comment keywords associated with the same brand field according to the occurrence frequency; forming a comment keyword word cloud picture according to the sequencing result; and pushing the cloud image of the comment keywords to the user.
Example four
As shown in fig. 5, based on the same inventive concept, an embodiment of the present application further provides a computing device, and with reference to fig. 5, the computing device includes:
at least one processor 501, and
a memory 502, a communication interface 503 communicatively coupled to the at least one processor 501;
the memory 502 stores instructions executable by the at least one processor 501, and the at least one processor 501 executes the instructions stored in the memory 502 to perform a data pushing method according to a first embodiment of the present application by using the communication interface 503.
Based on the same inventive concept, embodiments of the present application further provide a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and when the computer instructions are run on a computer, the computer is caused to execute the data pushing method according to the embodiments of the present application.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (12)
1. A data pushing method, comprising:
capturing commodity parameters of any commodity from an e-commerce platform; the commodity parameter is used for indicating attribute information of a commodity;
extracting a brand field indicating the brand of the commodity and a comment keyword field evaluating the commodity from the commodity parameter;
determining commodities with the same brand fields as similar commodities, and associating comment keyword fields of the similar commodities with the brand fields of the similar commodities;
and pushing the associated comment keyword field and brand field to the user.
2. The method of claim 1, wherein pushing the associated review keyword fields and brand fields to the user comprises:
determining the occurrence frequency of each comment keyword associated with the same brand field, and obtaining the sequencing result of the comment keywords associated with the same brand field according to the occurrence frequency;
forming a comment keyword word cloud picture according to the sequencing result;
and pushing the cloud image of the comment keywords to the user.
3. The method of claim 1, wherein the merchandise parameters comprise: at least one of function description parameters, price parameters, user comment keywords and user comment information of the commodity.
4. The method of any of claims 1-3, wherein prior to extracting a brand field indicating the brand of the good and a review keyword field evaluating the good from the good parameters, further comprising:
preprocessing the commodity parameters:
and converting the commodity parameters after pretreatment into standard data meeting preset rules according to preset conversion standards.
5. The method of claim 4, wherein said pre-processing said commodity parameter comprises:
judging whether the commodity parameters include price parameters or not, and if not, deleting the commodity parameters;
and classifying the commodity parameters according to the model parameters of each commodity in the commodity parameters.
6. An apparatus for pushing data, comprising:
the grabbing unit is used for grabbing commodity parameters of a commodity class of commodities from the E-commerce platform; the commodity parameter is used for indicating attribute information of a commodity;
an extracting unit configured to extract a brand field indicating a brand of the commodity and a comment keyword field evaluating the commodity from the commodity parameter;
the association unit is used for determining the commodities with the same brand fields as the same-class commodities and associating the comment keyword fields of the same-class commodities with the brand fields of the same-class commodities;
and the pushing unit is used for pushing the associated comment keyword field and the associated brand field to the user.
7. The apparatus according to claim 6, wherein the pushing unit is specifically configured to determine the occurrence number of each comment keyword associated with the same brand field, and obtain a ranking result of the comment keywords associated with the same brand field according to the occurrence number; forming a comment keyword word cloud picture according to the sequencing result; and pushing the cloud image of the comment keywords to the user.
8. The apparatus of claim 6, wherein the merchandise parameters comprise: at least one of function description parameters, price parameters, user comment keywords and user comment information of the commodity.
9. The apparatus according to any of the claims 6 to 8, wherein the extraction unit is specifically configured to pre-process the merchandise parameters: and converting the commodity parameters after pretreatment into standard data meeting preset rules according to preset conversion standards.
10. The apparatus of claim 9, wherein the extraction unit pre-processing the merchandise parameters comprises:
judging whether the commodity parameters include price parameters or not, and if not, deleting the commodity parameters;
and classifying the commodity parameters according to the model parameters of each commodity in the commodity parameters.
11. A computing device, comprising:
at least one processor, and
a memory communicatively coupled to the at least one processor, a communication interface;
wherein the memory stores instructions executable by the at least one processor, the at least one processor performing the method of any of claims 1-5 with the communications interface by executing the instructions stored by the memory.
12. A computer-readable storage medium having stored thereon computer instructions which, when executed on a computer, cause the computer to perform the method of any one of claims 1-5.
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| CN117094752A (en) * | 2023-10-13 | 2023-11-21 | 广州市零脉信息科技有限公司 | Product sales intention group analysis system |
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