CN111507773A - Coupon management method, device and storage medium - Google Patents
Coupon management method, device and storage medium Download PDFInfo
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- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
- G06Q30/0217—Discounts or incentives, e.g. coupons or rebates involving input on products or services in exchange for incentives or rewards
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
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- G06F16/3344—Query execution using natural language analysis
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
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Abstract
The embodiment of the application discloses a coupon management method, a device and a storage medium, wherein the coupon management method receives an evaluation to be matched, which is sent by a terminal, through a server; then, the server determines a target label corresponding to the evaluation to be matched in a label set, wherein the label set comprises at least one label, each label in the label set corresponds to at least one coupon, each label in the label set corresponds to an evaluation set, all evaluations in the evaluation set are labeled with the labels corresponding to the evaluation set, and the evaluation set comprises at least one evaluation; and finally, the server sends the target coupon corresponding to the target label to the terminal. As can be known, the server determines the coupon corresponding to the evaluation according to the evaluation, so that the targeted distribution of the coupon is realized.
Description
Technical Field
The present application relates to the field of internet technologies, and in particular, to a coupon management method, an apparatus, and a storage medium.
Background
With the rise of online shopping, coupons have been playing a vital role in the purchase of goods as a way for merchants to attract customers. At present, coupons are generated primarily on an activity basis. The user receives the coupon at the activity and then places the order for use. However, the current issuing mode of the coupons autonomously picked up by the user is difficult to have pertinence for the user; it is also difficult for merchants to manage customers by using coupons because coupons are issued in a unified manner. Therefore, how to issue the coupon for the user is a problem to be solved urgently at present.
Disclosure of Invention
The embodiment of the application provides a coupon management method, a coupon management device and a coupon management storage medium, and can provide a mode of obtaining a coupon through evaluation content, and specifically issue the coupon to a user according to the evaluation content.
In a first aspect, an embodiment of the present application discloses a coupon management method, including:
receiving an evaluation to be matched sent by a terminal;
determining a target label corresponding to the evaluation to be matched in a label set, wherein the label set comprises at least one label, each label in the label set corresponds to at least one coupon, each label in the label set corresponds to an evaluation set, all evaluations in the evaluation set are labeled with the label corresponding to the evaluation set, and the evaluation set comprises at least one evaluation;
and sending the target coupon corresponding to the target label to the terminal.
As a possible implementation manner, the determining, in the tag set, the target tag corresponding to the evaluation to be matched includes:
splitting the evaluation to be matched into at least one word to obtain a word set to be matched;
summing the frequencies of each word in the word set to be matched in the evaluation set corresponding to the first label to obtain the total frequency corresponding to the first label, wherein the first label is any one label in the label set;
and determining the label corresponding to the maximum total frequency as the target label.
As a possible implementation manner, after performing word segmentation processing on the to-be-matched evaluation to obtain a to-be-matched word set, determining that the frequency of the to-be-matched evaluation in the evaluation set corresponding to the first tag is before the sum of the frequencies of all words in the to-be-matched word set in the evaluation set corresponding to the first tag, where the method further includes:
counting the occurrence times of each word in the word set to be matched in the evaluation set corresponding to the first label;
determining the frequency of a first word in the evaluation set corresponding to the first label as the product of the weight corresponding to the first word and the occurrence number of the first word in the evaluation set corresponding to the first label, wherein the first word is any word in the word set to be matched.
As a possible implementation manner, the determining, in the tag set, the target tag corresponding to the evaluation to be matched includes:
determining the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label, wherein the second label is any one label in the label set;
determining the matching degree of the evaluation to be matched and the second label according to the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label;
and taking the label corresponding to the maximum matching degree as the target label.
As a possible implementation manner, the determining the similarity of each evaluation in the evaluation set corresponding to the to-be-matched evaluation and the second label includes:
determining the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation according to at least one word included in the evaluation to be matched and at least one word included in the first evaluation, wherein the first evaluation is any one evaluation in an evaluation set corresponding to the second label;
and determining the similarity between the evaluation to be matched and the first comment as the cosine similarity between the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation.
As a possible implementation manner, before the target coupon corresponding to the target tag is sent to the terminal, the method further includes:
and determining the target coupon corresponding to the target label according to the corresponding relation between the label and the coupon.
As a possible implementation manner, the determining a target coupon corresponding to the target tag includes:
identifying the type of a target commodity to which the commodity to be matched, evaluated and evaluated belongs;
determining at least one coupon corresponding to the target commodity type according to the corresponding relation between the commodity type and the coupon, wherein each coupon in the at least one coupon corresponds to one label;
and determining the coupon corresponding to the target label from the at least one coupon as the target coupon.
In a second aspect, an embodiment of the present application discloses a coupon management apparatus, including:
the receiving unit is used for receiving the evaluation to be matched sent by the terminal;
a first determining unit, configured to determine a target tag corresponding to the evaluation to be matched in a tag set, where the tag set includes at least one tag, each tag in the tag set corresponds to at least one coupon, each tag in the tag set corresponds to an evaluation set, all evaluations in the evaluation set are labeled with tags corresponding to the evaluation set, and the evaluation set includes at least one evaluation;
and the sending unit is used for sending the target coupon corresponding to the target label to the terminal.
As a possible implementation manner, the determining, by the first determining unit, a target tag corresponding to the evaluation to be matched in a tag set includes:
splitting the evaluation to be matched into at least one word to obtain a word set to be matched;
summing the frequencies of each word in the word set to be matched in the evaluation set corresponding to the first label to obtain the total frequency corresponding to the first label, wherein the first label is any one label in the label set;
and determining the label corresponding to the maximum total frequency as the target label.
As a possible implementation manner, after performing word segmentation processing on the to-be-matched evaluation to obtain a to-be-matched word set, determining that the frequency of the to-be-matched evaluation in the evaluation set corresponding to the first tag is before the sum of the frequencies of all words in the to-be-matched word set in the evaluation set corresponding to the first tag, where the apparatus further includes:
the counting unit is used for counting the occurrence frequency of each word in the word set to be matched in the evaluation set corresponding to the first label;
a second determining unit, configured to determine that a frequency of a first word in the evaluation set corresponding to the first tag is a product of a weight corresponding to the first word and a number of occurrences of the first word in the evaluation set corresponding to the first tag, where the first word is any one of the words in the set of words to be matched.
As a possible implementation manner, the determining, by the first determining unit, a target tag corresponding to the evaluation to be matched in a tag set includes:
determining the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label, wherein the second label is any one label in the label set;
determining the matching degree of the evaluation to be matched and the second label according to the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label;
and taking the label corresponding to the maximum matching degree as the target label.
As a possible implementation manner, the determining the similarity of each evaluation in the evaluation set corresponding to the to-be-matched evaluation and the second label includes:
determining the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation according to at least one word included in the evaluation to be matched and at least one word included in the first evaluation, wherein the first evaluation is any one evaluation in an evaluation set corresponding to the second label;
and determining the similarity between the evaluation to be matched and the first comment as the cosine similarity between the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation.
As a possible implementation manner, before the sending unit sends the target coupon corresponding to the target tag to the terminal, the apparatus further includes:
and the third determining unit is used for determining the target coupon corresponding to the target label according to the corresponding relation between the label and the coupon.
As a possible implementation manner, the determining, by the third determining unit, the target coupon corresponding to the target tag includes:
identifying the type of a target commodity to which the commodity to be matched, evaluated and evaluated belongs;
determining at least one coupon corresponding to the target commodity type according to the corresponding relation between the commodity type and the coupon, wherein each coupon in the at least one coupon corresponds to one label;
and determining the coupon corresponding to the target label from the at least one coupon as the target coupon.
In a third aspect, an embodiment of the present application provides a coupon management apparatus, which includes a processor and a memory, where the processor is coupled to the memory, where the memory is used to store computer instructions, and the processor is used to execute the computer instructions and invoke the program code to implement the coupon management method disclosed in the embodiment of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a computer device, the coupon management method disclosed in the embodiments of the first aspect is implemented.
In a fifth aspect, the present application provides a computer program, which, when executed by a computer device, implements the coupon management method disclosed in the embodiments of the first aspect.
In the embodiment of the application, a server receives the evaluation to be matched, which is sent by a terminal; the method comprises the steps that a server determines a target label corresponding to an evaluation to be matched in a label set, wherein the label set comprises at least one label, each label in the label set corresponds to at least one coupon, each label in the label set corresponds to an evaluation set, all evaluations in the evaluation set are labeled with the label corresponding to the evaluation set, and the evaluation set comprises at least one evaluation; and the server sends the target coupon corresponding to the target label to the terminal. Therefore, the server determines the coupon corresponding to the evaluation according to the evaluation, and the targeted distribution of the coupon is realized.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a system architecture for coupon management provided by an embodiment of the present application;
FIG. 2 is a schematic flow chart of a coupon management method provided in the practice of the present application;
FIG. 3 is a schematic diagram of a tag collection exemplarily provided by an embodiment of the present application;
FIG. 4a is a schematic diagram illustrating a correspondence relationship between a tag and a coupon according to an embodiment of the present application;
FIG. 4b is a diagram illustrating an example of correspondence between a label, a product type, and a coupon according to an embodiment of the present application;
FIG. 5 is a coupon management apparatus according to an embodiment of the present application;
fig. 6 is another coupon management apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
First, concepts and terms related to the embodiments of the present application will be briefly described.
(1) Word frequency vector
The word frequency vector referred by the embodiment of the application is the word frequency vector of the evaluation, namely, an evaluation is converted into a vector form to be represented. A term comprised by a term set of multiple terms may constitute a term set, in which case a term in the term set may be represented as a vector in the multidimensional space comprised by the term set. For example, the evaluation set includes a first evaluation and a second evaluation, where:
the first evaluation was: this box is expensive and that price is suitable.
The second evaluation was: this box is not inexpensive and is more suitable.
Then the set of terms formed by the evaluation set is { this, box, price, expensive, that, appropriate, not, cheap, better }.
The word frequency of each word in the word set at the first evaluation is { this 1, box 1, price 2, 1, that 1, 1 proper, not 0, 0 cheap, 0 more }, respectively, then the word frequency vector of the first evaluation can be represented as (1, 1, 2, 1, 1, 0, 0, 0).
Each term in the term set has a term frequency of { this 1, box 1, price 1, expensive 0, that 1, suitable 1, not 1, cheap 1, more 1} in the second evaluation, respectively, then the term frequency vector of the second evaluation may be represented as (1, 1, 1, 0, 1, 1, 1).
(2) Cosine similarity
Cosine similarity measures the difference between two individuals by using the cosine value of the included angle between two vectors in the vector space. The closer the cosine value is to 1, the closer the angle is to 0 degrees, i.e. the more similar the two vectors are. According to the embodiment of the application, the similarity of the two evaluations can be calculated according to the cosine similarity of the word frequency vectors of the two evaluations, and the closer the calculation result is to 1, the higher the similarity between the two evaluations is.
Note that, the coupon referred to in the embodiments of the present application refers to a coupon in the form of an electronic resource.
For the convenience of understanding the embodiment of the present application, a system architecture of a coupon management method based on the embodiment of the present application is described below. Referring to fig. 1, fig. 1 is a schematic diagram of a system architecture for coupon management according to an embodiment of the present application, where the system architecture may include a terminal 101 and a server 102. In one implementation scenario, the terminal 101 may be configured to receive the evaluation to be matched and send the evaluation to be matched to the server 102. Alternatively, the terminal 101 may be a smart device such as a computer, a tablet, a mobile phone, and the like, which is not limited herein.
The server 102 stores a set of tags, the set of tags including at least one tag. After receiving the evaluation to be matched sent by the terminal 101, the server 102: firstly, determining a target label corresponding to the evaluation to be matched in a set label set; secondly, the server 102 determines the coupon corresponding to the target tag according to the corresponding relationship between the set tag and the coupon, namely the coupon corresponding to the to-be-matched evaluation; finally, the server 102 sends the coupon corresponding to the evaluation to be matched to the terminal 101. After the terminal 101 receives the coupon, when the product specified by the coupon is purchased in the account corresponding to the terminal 101, the terminal 101 automatically selects and uses the coupon.
Not limited to the system architecture diagram of the coupon management method shown in fig. 1, the system architecture diagram of the coupon management method provided in the embodiment of the present application may also include other devices, which are not limited herein.
Based on the above description, the present application embodiment proposes a coupon management method, which can be executed by the above-mentioned coupon management system in fig. 1. Wherein the terminal may be the terminal 101 and the server may be the server 102. Referring to fig. 2, fig. 2 is a flowchart illustrating a coupon management method according to an embodiment of the present disclosure, where the coupon management method may include some or all of the following steps.
S202, the server receives the evaluation to be matched sent by the terminal.
The evaluation to be matched mentioned in the embodiment of the application refers to text information for evaluating the commodity.
S204, the server determines a target label corresponding to the evaluation to be matched in a label set, wherein the label set comprises at least one label, each label in the label set corresponds to at least one coupon, each label in the label set corresponds to an evaluation set, all evaluations in the evaluation set are marked with the label corresponding to the evaluation set, and the evaluation set comprises at least one evaluation.
The server may store a labelset in advance, and the labelset includes labels and evaluation sets corresponding to the labels, which are divided in advance. For example, a total evaluation set may be obtained from a database of "panning", and then each evaluation in the total evaluation set may be labeled in an artificial intelligence classification manner, that is, each evaluation in the total evaluation set corresponds to one label, and each label corresponds to one evaluation set. Optionally, each evaluation in the total evaluation set may also be classified into a corresponding label by a manual classification manner, which is not limited herein. For example, referring to fig. 3, fig. 3 is a schematic diagram of a tag set exemplarily provided in an embodiment of the present application. As shown in fig. 3, different types of tags may be provided to identify the evaluations. For example, the tags in the tag set include "pull new tags", "activation tags", "product improvement tags", and "comment not real tags". The evaluation of the label of the 'renewing label' indicates that the evaluation can objectively and well display the characteristics of the product and approve the advantages of the product; the evaluation of the "activation tag" designation indicates that the evaluation may trigger a user-directed discussion of the attributes of the product; the evaluation of the product improvement label indicates that the evaluation indicates the defects of the product, improves the product quality, saves the production cost and other suggestions; the evaluation of the "comment not actually label" mark means the evaluation of the product of casual blacking, defatting. The total evaluation set includes the evaluations: evaluation a, evaluation b, evaluation c, evaluation d, evaluation e, evaluation f, evaluation g, evaluation h, evaluation i, evaluation j, evaluation k, and evaluation l. Labeling each evaluation in the total evaluation set to obtain an evaluation set corresponding to each label in the label set, as shown in fig. 3, the evaluation set corresponding to the updated label includes an evaluation a, an evaluation b, and an evaluation c.
Alternatively, the number of evaluations corresponding to each tag in the tag set is not limited to the above exemplary 3, each tag may correspond to other numbers of evaluations, and the number of evaluations corresponding to each tag may be different.
Optionally, the comments can be divided into more or less tag sets according to actual requirements without being limited to the four mentioned meaning tags.
And then, the server determines a target label corresponding to the evaluation to be matched from a pre-stored label set. The method for determining the target tag corresponding to the evaluation to be matched in the tag set can refer to the following steps S402-S406, S502-S504 and S602-S606 in detail.
S206, the server sends the target coupon corresponding to the target label to the terminal.
Before sending the target coupon corresponding to the target tag to the terminal, the server also needs to determine the target coupon corresponding to the target tag according to the corresponding relationship between the tag and the coupon. The setting of the correspondence between the tags in the tag set and the coupons can be referred to as the following two implementation manners.
Implementation (1):
in one implementation, the correspondence between the tags in the tag set and the coupons may be a one-to-one correspondence. For example, please refer to fig. 4a, fig. 4a is a schematic diagram illustrating a correspondence relationship between a tag and a coupon according to an embodiment of the present application. As shown in fig. 4a, the coupon corresponding to the "pull new tag" is a "9-fold coupon"; the coupon corresponding to the "activation promotion label" is a "9.5 discount coupon"; the coupon corresponding to the product improvement label is an 8-fold coupon; the coupon corresponding to the "comment false label" is a "120% price expansion coupon".
Optionally, the correspondence between the provided label and the coupon is not limited, and may be adjusted based on the actual situation, which is not limited herein.
Implementation (2):
in another implementation manner, the coupon corresponding to the tag may also correspond to different coupons according to different types of goods to be matched and evaluated, and this implementation manner may be referred to as the following partial or all steps.
S302, the server identifies the target commodity type of the commodity to be matched, evaluated and evaluated.
And according to the corresponding relation between the commodities and the commodity types, the server identifies the commodity type to which the commodity to be matched, evaluated and evaluated belongs, namely the target commodity type. Referring to fig. 4b, fig. 4b is a diagram illustrating an example of a correspondence relationship between a tag, a product type, and a coupon according to an embodiment of the present application. As shown in fig. 4b, the categories of goods may include clothing, appliances, and the like.
S304, the server determines at least one coupon corresponding to the target commodity type according to the corresponding relation between the commodity type and the coupon, wherein each coupon of the at least one coupon corresponds to one label.
As shown in fig. 4b, if the product category to which the target product to be matched with the evaluation belongs is "clothing", the coupons corresponding to the product category "clothing" include "3-fold coupon", "4-fold coupon", "2-fold coupon", and "120% expansion coupon". Wherein, the label corresponding to the 3-fold coupon is a ' pull-new label ', ' the label corresponding to the 4-fold coupon ' is a ' activation label ', ' the label corresponding to the 2-fold coupon is a ' product improvement label ', and ' the label corresponding to the 120% price-expansion coupon ' is a ' comment unreal label '.
S306, the server determines the coupon corresponding to the target label from the at least one coupon as the target coupon.
If the target label corresponding to the to-be-matched evaluation in the label set is a "pull new label", the target coupon corresponding to the target label "pull new label" is a "3-fold coupon".
The method is not limited to the implementation of the correspondence between the tag and the coupon mentioned in the implementation (1) and the implementation (2), and may also include other implementations capable of determining the correspondence between the tag and the coupon, which is not limited herein.
Next, three implementation manners in which the server determines the target tag corresponding to the evaluation to be matched in the tag set in step S202 are described.
Implementation mode (one):
s402, the server divides the evaluation to be matched into at least one word, and a word set to be matched is obtained.
The splitting of the evaluation to be matched into at least one word means that the evaluation to be matched is split into one or more independent words, and the word can be a noun, a verb, an adjective or any other word with any part of speech. For example, the matching is evaluated as "the piece of clothing is good in quality", and the resulting set of words to be matched may be { the piece of clothing, the quality, the good }.
S404, the server sums the frequencies of each word in the word set to be matched in the evaluation set corresponding to the first label to obtain the total frequency corresponding to the first label, wherein the first label is any one label in the label set.
For example, if the first tag is a "pull new tag", the evaluation set corresponding to the "pull new tag" includes: evaluation a, evaluation b and evaluation c. Firstly, dividing the evaluation a, the evaluation b and the evaluation c into an evaluation term set, then calculating the frequency of each term in the term set to be matched in the evaluation term set, and summing the frequencies of each term in the evaluation term set to obtain the total frequency of the term set to be evaluated corresponding to the 'update label'. And respectively calculating the total frequency corresponding to each label in the label set of the word set to be matched according to the above mode.
S406, the server determines that the label corresponding to the maximum total frequency is the target label.
Implementation mode (b):
on the basis of the implementation manner (one), namely after the word segmentation processing is performed on the to-be-matched evaluation to obtain the to-be-matched word set, before the frequency of the to-be-matched evaluation in the evaluation set corresponding to the first label is determined to be the sum of the frequencies of all words in the to-be-matched word set in the evaluation set corresponding to the first label, the weight can be added to each word in the to-be-matched word set, and the implementation manner of the method can further include the following partial or all steps.
S502, the server counts the occurrence frequency of each word in the word set to be matched in the evaluation set corresponding to the first label.
S504, the server determines that the frequency of the first word in the evaluation set corresponding to the first label is the product of the weight corresponding to the first word and the occurrence frequency of the first word in the evaluation set corresponding to the first label, and the first word is any word in the word set to be matched.
For example, a word weight table may be set in the server, and after the word set to be matched is obtained, the weight of each word in the word set to be matched may be searched in the word weight table. Firstly, the weight of each word in the word set to be matched is found in a word weight table to be 0.5, 0.5 of clothes, 1 of quality and 1 of fine quality; secondly, if the frequency of each word in the word set to be matched appearing in the evaluation set corresponding to the first label is { the piece 1, the piece 3, the quality 2, the good 2}, then, at this time, the frequency of each word in the word set to be matched in the first label can be obtained as { the piece 0.5, the piece 1.5, the quality 2, the good 2 }; finally, the sum of the frequencies of each word in the set of words to be matched in the first label is calculated to be 6 according to the implementation mode (one).
Implementation mode (c):
the server determines a target label corresponding to the evaluation to be matched in the label set, and can also determine the target label according to the similarity degree of the evaluation to be matched and the evaluation in the evaluation set corresponding to each label. The implementation may include some or all of the following steps.
S602, the server determines the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and a second label, wherein the second label is any one label in the label set.
One implementation of determining the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second tag may include some or all of the steps.
S6021, the server determines the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation according to at least one word included in the evaluation to be matched and at least one word included in the first evaluation, and the first evaluation is any one evaluation in the evaluation set corresponding to the second label.
Firstly, a term set composed of at least one term included by the evaluation to be matched and at least one term included by the first evaluation is obtained. For example, if the evaluation to be matched includes at least one word of { the piece of clothing, the quality, and the goodness }, and the first evaluation includes at least one word of { the piece of clothing, the quality, and the goodness }, then the resulting set of words is { the piece of clothing, the quality, the goodness, and the goodness }. Secondly, calculating the word frequency of each word in the word set of at least one word included in the evaluation to be matched as { the piece 1, the quality 1, the good 0, and the good 0}, wherein the word frequency vector to be matched and evaluated can be represented as (1, 1, 1, 1, 0, 0); the first evaluation includes at least one word with a frequency of { this piece of 0, clothing 1, quality 1, good 0, 1, good 1} in the set of words, and the word frequency vector of the first evaluation may be represented as (0, 1, 1, 0, 1, 1).
S6022, the server determines that the similarity between the to-be-matched evaluation and the first comment is the cosine similarity between the word frequency vector of the to-be-matched evaluation and the word frequency vector of the first evaluation.
Wherein the similarity represents the degree of similarity between the evaluation to be matched and the first evaluation. In the implementation manner of the embodiment of the application, the similarity between the evaluation to be matched and the first evaluation can be calculated through a cosine similarity formula, that is, the cosine similarity between the word frequency vector to be matched and evaluated and the word frequency vector of the first evaluation is calculated, so as to obtain the similarity between the evaluation to be matched and the first evaluation. Wherein, the cosine similarity formula is:
wherein xiRepresenting the ith component, y, in the word frequency vector to be matched and evaluatediAn ith partial vector in the word frequency vector representing the first evaluation. Wherein i is a positive integer, n is a positive integer, 1 < i < n, and n is the length of the word frequency vector of the evaluation to be matched and the first evaluation for calculating the degree of similarity.
Optionally, the similarity may also be obtained by other methods for calculating the similarity, for example, the Jaccard distance and the Dice coefficient, that is, the similarity between the evaluation to be matched and the first evaluation may be calculated according to the number of the same appearing words, which is not limited herein.
604. And the server determines the matching degree of the evaluation to be matched and the second label according to the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label.
In some implementation manners, the matching degree between the evaluation to be matched and the second label can be obtained by summing the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label.
And S606, the server takes the label corresponding to the maximum matching degree as a target label.
The implementation manner of determining the target tag corresponding to the evaluation to be matched is not limited to the implementation manners mentioned in the foregoing implementation manner (a), implementation manner (b), and implementation manner (c), and other implementation manners of determining the target tag corresponding to the evaluation to be matched may also be adopted, which is not limited herein.
According to the embodiment of the application, a server receives the evaluation to be matched sent by a terminal; then, the server determines a target label corresponding to the evaluation to be matched in a label set, wherein the label set comprises at least one label, each label in the label set corresponds to at least one coupon, each label in the label set corresponds to an evaluation set, all evaluations in the evaluation set are labeled with the labels corresponding to the evaluation set, and the evaluation set comprises at least one evaluation; and finally, the server sends the target coupon corresponding to the target label to the terminal. Thus, it can be seen that: firstly, the server determines the coupon corresponding to the evaluation according to the evaluation content, so that the targeted distribution of the coupon is realized, and for a merchant, the received real evaluation can reflect the actual public praise of the commodity and improve the commodity based on the evaluation. Secondly, the customer cannot blacken the goods at will due to the existence of the expansion coupon, and the coupon of the goods can be obtained by submitting real and objective evaluation, so that the coupon generated aiming at the evaluation content can ensure the authenticity and effectiveness of the evaluation content to a certain extent.
Based on the description of the above method embodiments, the present application provides a coupon management apparatus 500, where the coupon management apparatus 500 may operate a server as corresponding to fig. 2, and the coupon management apparatus 500 may be a computer program (including program code) that runs in the server. Referring to fig. 5, the coupon management apparatus may operate the following units:
a receiving unit 501, configured to receive an evaluation to be matched, which is sent by a terminal;
a first determining unit 502, configured to determine a target tag corresponding to the evaluation to be matched in a tag set, where the tag set includes at least one tag, each tag in the tag set corresponds to at least one coupon, each tag in the tag set corresponds to an evaluation set, all evaluations in the evaluation set are labeled with tags corresponding to the evaluation set, and the evaluation set includes at least one evaluation;
a sending unit 503, configured to send the target coupon corresponding to the target tag to the terminal.
In one embodiment, the determining, by the first determining unit 502, a target tag corresponding to the evaluation to be matched is determined in a tag set, and includes:
splitting the evaluation to be matched into at least one word to obtain a word set to be matched;
summing the frequencies of each word in the word set to be matched in the evaluation set corresponding to the first label to obtain the total frequency corresponding to the first label, wherein the first label is any one label in the label set;
and determining the label corresponding to the maximum total frequency as the target label.
In one embodiment, after performing word segmentation on the to-be-matched evaluation to obtain a to-be-matched term set, and determining that the frequency of the to-be-matched evaluation in the evaluation set corresponding to the first tag is before the sum of the frequencies of all terms in the to-be-matched term set in the evaluation set corresponding to the first tag, the apparatus 500 further includes:
a counting unit 504, configured to count the occurrence frequency of each term in the term set to be matched in the evaluation set corresponding to the first tag;
a second determining unit 505, configured to determine that a frequency of a first word in the evaluation set corresponding to the first tag is a product of a weight corresponding to the first word and a number of occurrences of the first word in the evaluation set corresponding to the first tag, where the first word is any one of the words in the set of words to be matched.
In one embodiment, the determining, by the first determining unit 502, a target tag corresponding to the evaluation to be matched is determined in a tag set, and includes:
determining the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label, wherein the second label is any one label in the label set;
determining the matching degree of the evaluation to be matched and the second label according to the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label;
and taking the label corresponding to the maximum matching degree as the target label.
In one embodiment, the determining the similarity of each evaluation in the evaluation set corresponding to the to-be-matched evaluation and the second label includes:
determining the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation according to at least one word included in the evaluation to be matched and at least one word included in the first evaluation, wherein the first evaluation is any one evaluation in an evaluation set corresponding to the second label;
and determining the similarity between the evaluation to be matched and the first comment as the cosine similarity between the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation.
In an embodiment, before the sending unit 503 sends the target coupon corresponding to the target tag to the terminal, the apparatus 500 further includes:
a third determining unit 506, configured to determine, according to the correspondence between the tag and the coupon, a target coupon corresponding to the target tag.
In one embodiment, the determining, by the third determining unit 506, the target coupon corresponding to the target tag includes:
identifying the type of a target commodity to which the commodity to be matched, evaluated and evaluated belongs;
determining at least one coupon corresponding to the target commodity type according to the corresponding relation between the commodity type and the coupon, wherein each coupon in the at least one coupon corresponds to one label;
and determining the coupon corresponding to the target label from the at least one coupon as the target coupon.
It should be understood that, for specific functional implementation manners of the above-mentioned functional units, reference may be made to the related description in the corresponding embodiment of fig. 2, and details are not described here again.
In the embodiment of the application, a server receives the evaluation to be matched, which is sent by a terminal; then, the server determines a target label corresponding to the evaluation to be matched in a label set, wherein the label set comprises at least one label, each label in the label set corresponds to at least one coupon, each label in the label set corresponds to an evaluation set, all evaluations in the evaluation set are labeled with the labels corresponding to the evaluation set, and the evaluation set comprises at least one evaluation; and finally, the server sends the target coupon corresponding to the target label to the terminal. Thus, it can be seen that: firstly, the server determines the coupon corresponding to the evaluation according to the evaluation content, so that the targeted distribution of the coupon is realized, and for a merchant, the received real evaluation can reflect the actual public praise of the commodity and improve the commodity based on the evaluation. Secondly, the customer cannot blacken the goods at will due to the existence of the expansion coupon, and the coupon of the goods can be obtained by submitting real and objective evaluation, so that the coupon generated aiming at the evaluation content can ensure the authenticity and effectiveness of the evaluation content to a certain extent.
Referring to fig. 6, fig. 6 is a schematic structural diagram of another coupon management apparatus 600 according to an embodiment of the present application. The coupon management apparatus 600 may specifically correspond to the server 102 in fig. 1, and the apparatus 600 may include: a processor 601, a bus 602, a network interface 603, and a memory 604. Wherein a communication bus 602 is used to enable the connection communication between these components. The network interface 603 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). As shown in fig. 6, the memory 604, which is a computer-readable storage medium, may include therein an operating system, a network communication module, a user interface module, and a device control application program, which may be executed when the apparatus 600 is operated.
In the coupon management apparatus 600 shown in fig. 6, the network interface 603 may provide a network communication function; and processor 601 may be used to invoke a device control application stored in memory 604 to implement:
receiving the evaluation to be matched sent by the terminal through a network interface 603;
determining a target label corresponding to the evaluation to be matched in a label set, wherein the label set comprises at least one label, each label in the label set corresponds to at least one coupon, each label in the label set corresponds to an evaluation set, all evaluations in the evaluation set are labeled with the label corresponding to the evaluation set, and the evaluation set comprises at least one evaluation;
and sending the target coupon corresponding to the target label to the terminal.
In an implementation of the embodiment of the present application, the processor 601 determines, in a tag set, a target tag corresponding to the evaluation to be matched:
splitting the evaluation to be matched into at least one word to obtain a word set to be matched;
summing the frequencies of each word in the word set to be matched in the evaluation set corresponding to the first label to obtain the total frequency corresponding to the first label, wherein the first label is any one label in the label set;
and determining the label corresponding to the maximum total frequency as the target label.
In an implementation of the embodiment of the present application, after performing word segmentation on the to-be-matched evaluation to obtain a to-be-matched word set, determining that a frequency of the to-be-matched evaluation in the evaluation set corresponding to the first tag is before a sum of frequencies of all words in the to-be-matched word set in the evaluation set corresponding to the first tag, where the method further includes:
counting the occurrence times of each word in the word set to be matched in the evaluation set corresponding to the first label;
determining the frequency of a first word in the evaluation set corresponding to the first label as the product of the weight corresponding to the first word and the occurrence number of the first word in the evaluation set corresponding to the first label, wherein the first word is any word in the word set to be matched.
In an implementation of the embodiment of the present application, the determining, by the processor 601, a target tag corresponding to the evaluation to be matched in a tag set includes:
determining the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label, wherein the second label is any one label in the label set;
determining the matching degree of the evaluation to be matched and the second label according to the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label;
and taking the label corresponding to the maximum matching degree as the target label.
In an implementation of the embodiment of the present application, the determining a similarity of each evaluation in the evaluation set corresponding to the to-be-matched evaluation and the second label includes:
determining the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation according to at least one word included in the evaluation to be matched and at least one word included in the first evaluation, wherein the first evaluation is any one evaluation in an evaluation set corresponding to the second label;
and determining the similarity between the evaluation to be matched and the first comment as the cosine similarity between the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation.
In an implementation of the embodiment of the present application, before sending the target coupon corresponding to the target tag to the terminal, the processor 601 is further configured to implement:
and determining the target coupon corresponding to the target label according to the corresponding relation between the label and the coupon.
In an implementation of the embodiment of the present application, the determining a target coupon corresponding to the target tag includes:
identifying the type of a target commodity to which the commodity to be matched, evaluated and evaluated belongs;
determining at least one coupon corresponding to the target commodity type according to the corresponding relation between the commodity type and the coupon, wherein each coupon in the at least one coupon corresponds to one label;
and determining the coupon corresponding to the target label from the at least one coupon as the target coupon.
It should be noted that the receiving unit 501 and the sending unit 503 in fig. 5 may be implemented by the network interface 601 in fig. 6, and the first determining unit 502, the counting unit 504, the second determining unit 505, and the third determining unit 506 in fig. 5 may be implemented by the processor 601 in fig. 6.
It should be understood that the coupon management apparatus 600 described in the embodiment of the present application can perform the foregoing description of the coupon management method in the embodiment corresponding to fig. 2, and will not be described herein again. In addition, the beneficial effects of the same method are not described in detail.
Further, here, it is to be noted that: an embodiment of the present application further provides a computer storage medium, and the computer storage medium stores the aforementioned computer programs executed by the coupon management apparatus 500 and the coupon management apparatus 600, and the computer programs include program instructions, and when the processor executes the program instructions, the method executed by the server in the embodiment corresponding to fig. 2 can be executed, which will not be described again here.
In addition, the beneficial effects of the same method are not described in detail. For technical details not disclosed in the embodiments of the computer storage medium referred to in the present application, reference is made to the description of the embodiments of the method of the present application.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present application and is not to be construed as limiting the scope of the present application, so that the present application is not limited thereto, and all equivalent variations and modifications can be made to the present application.
Claims (10)
1. A coupon management method, the method comprising:
receiving an evaluation to be matched sent by a terminal;
determining a target label corresponding to the evaluation to be matched in a label set, wherein the label set comprises at least one label, each label in the label set corresponds to at least one coupon, each label in the label set corresponds to an evaluation set, all evaluations in the evaluation set are labeled with the label corresponding to the evaluation set, and the evaluation set comprises at least one evaluation;
and sending the target coupon corresponding to the target label to the terminal.
2. The method according to claim 1, wherein the determining a target label corresponding to the evaluation to be matched in the label set comprises:
splitting the evaluation to be matched into at least one word to obtain a word set to be matched;
summing the frequencies of each word in the word set to be matched in the evaluation set corresponding to the first label to obtain the total frequency corresponding to the first label, wherein the first label is any one label in the label set;
and determining the label corresponding to the maximum total frequency as the target label.
3. The method according to claim 2, wherein after the to-be-matched evaluation is subjected to word segmentation processing to obtain a to-be-matched word set, it is determined that the frequency of the to-be-matched evaluation in the evaluation set corresponding to the first label is before the sum of the frequencies of all words in the to-be-matched word set in the evaluation set corresponding to the first label, and the method further comprises:
counting the occurrence times of each word in the word set to be matched in the evaluation set corresponding to the first label;
determining the frequency of a first word in the evaluation set corresponding to the first label as the product of the weight corresponding to the first word and the occurrence number of the first word in the evaluation set corresponding to the first label, wherein the first word is any word in the word set to be matched.
4. The method according to claim 1, wherein the determining a target label corresponding to the evaluation to be matched in the label set comprises:
determining the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label, wherein the second label is any one label in the label set;
determining the matching degree of the evaluation to be matched and the second label according to the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label;
and taking the label corresponding to the maximum matching degree as the target label.
5. The method according to claim 4, wherein the determining the similarity of each evaluation in the evaluation set corresponding to the evaluation to be matched and the second label comprises:
determining the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation according to at least one word included in the evaluation to be matched and at least one word included in the first evaluation, wherein the first evaluation is any one evaluation in an evaluation set corresponding to the second label;
and determining the similarity between the evaluation to be matched and the first comment as the cosine similarity between the word frequency vector of the evaluation to be matched and the word frequency vector of the first evaluation.
6. The method according to claim 1, wherein before sending the target coupon corresponding to the target tag to the terminal, the method further comprises:
and determining the target coupon corresponding to the target label according to the corresponding relation between the label and the coupon.
7. The method of claim 6, wherein the determining the target coupon corresponding to the target tag comprises:
identifying the type of a target commodity to which the commodity to be matched, evaluated and evaluated belongs;
determining at least one coupon corresponding to the target commodity type according to the corresponding relation between the commodity type and the coupon, wherein each coupon in the at least one coupon corresponds to one label;
and determining the coupon corresponding to the target label from the at least one coupon as the target coupon.
8. A coupon management apparatus, characterized in that the apparatus comprises:
the receiving unit is used for receiving the evaluation to be matched sent by the terminal;
a first determining unit, configured to determine a target tag corresponding to the evaluation to be matched in a tag set, where the tag set includes at least one tag, each tag in the tag set corresponds to at least one coupon, each tag in the tag set corresponds to an evaluation set, all evaluations in the evaluation set are labeled with tags corresponding to the evaluation set, and the evaluation set includes at least one evaluation;
and the sending unit is used for sending the target coupon corresponding to the target label to the terminal.
9. A coupon management apparatus comprising a processor and a memory, the processor and memory coupled, wherein the memory is configured to store computer instructions, the processor configured to execute the computer instructions to cause the coupon management apparatus to implement the method of any one of claims 1-7.
10. A computer-readable storage medium, in which a computer program is stored which, when executed by a computer device, causes the computer device to carry out the method according to any one of claims 1 to 7.
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