A method, device and storage medium for quantifying parking lot service quality

Abstract

The present application discloses a method, device and storage medium for quantifying the service quality of a parking lot, which is used to provide a decision basis for users to select parking lot services. The present application method includes: obtaining feedback information of target users, wherein the target users include users who have generated order information in a target parking lot, and the feedback information includes scoring information and comment information for the target parking lot; calculating the scoring information according to the scoring rules preset in the scoring model to obtain a final score; determining at least one recommended tag from a tag library according to the final score and the comment information; sending the recommended tag to the target user; receiving the target tag selected by the target user from the recommended tags; updating the click rate of the corresponding tag in the tag library according to the target tag; determining and displaying the displayed tag according to the updated click rate.

Description

Technical Field

[0001] The present application relates to the technical field of parking lot service evaluation, and in particular to a method, device and storage medium for quantifying parking lot service quality. Background Art

[0002] In recent years, with the rapid development of the Internet, it has brought great convenience to users and service providers. Service providers can extend the sales of services online and even complete transactions in advance. Users can search for services and products online without leaving home, and conduct screening and comparison. With the significant increase in the number of motor vehicles in cities, related applications have also appeared in the parking industry on the Internet, such as some services generated around parking lots, such as finding parking spaces, renting parking spaces, etc. Users browse the service information released by parking lot service providers through the Internet.

[0003] At present, in order to increase parking volume and improve the efficiency of transaction facilitation, most parking service providers are expanding their service portals online, allowing users to browse relevant information about parking services through the Internet and make reservations for services.

[0004] However, by merely displaying the provided services to users, it is difficult for users to understand the actual situation of parking services and to choose from a variety of parking services online. Summary of the invention

[0005] In order to solve the above technical problems, the present application provides a method, device and storage medium for quantifying the quality of parking lot services, which are used to provide a decision basis for users to select parking lot services.

[0006] The first aspect of the present application provides a method for quantifying parking lot service quality, comprising:

[0007] Acquire feedback information of target users, wherein the target users include users who have generated order information in the target parking lot, and the feedback information includes rating information and comment information on the target parking lot;

[0008] Calculating the scoring information according to the scoring rules preset in the scoring model to obtain a final score;

[0009] Determining at least one recommended tag from a tag library according to the final score and the comment information;

[0010] Sending the recommended tag to the target user;

[0011] Receiving a target tag selected by the target user from the recommended tags;

[0012] Update the click rate of the corresponding tag in the tag library according to the target tag;

[0013] Determine the label to be displayed based on the updated click-through rate and display it.

[0014] Optionally, determining at least one recommended tag from a tag library according to the final score and the comment information includes:

[0015] Filtering keywords in the review information;

[0016] Determining at least one recommended tag from the tag library according to the keyword, wherein the tag library includes positive tags and negative tags;

[0017] Determine the ratio of positive labels and negative labels recommended among the recommended labels according to the final score;

[0018] The sending the recommended tag to the target user comprises:

[0019] The positive label and the negative label are sent to the target user according to the ratio.

[0020] Optionally, determining and displaying a label according to the updated click rate includes:

[0021] Sorting all tags in the tag library according to the updated click rate to obtain a sorting result;

[0022] The labels to be displayed are determined according to the sorting results and displayed.

[0023] Optionally, before determining and displaying labels according to the sorting results, the method further includes:

[0024] Calculate an average score based on the score information;

[0025] Determine the ratio of the positive labels and the negative labels to be displayed according to the average score;

[0026] Determining the positive label and the negative label to be displayed according to the ratio;

[0027] Determining the display label according to the sorting result and displaying it includes:

[0028] The positive labels and negative labels to be displayed are determined according to the sorting results and displayed.

[0029] Optionally, after determining the label to be displayed according to the click rate and displaying it, the method further includes:

[0030] When the feedback information of the target user exceeds the preset time, the final score of the target user is recalculated according to the scoring rule of the feedback information exceeding the preset time in the scoring model;

[0031] Recalculate the average score based on the recalculated final score.

[0032] Optionally, after determining and displaying a label according to the updated click rate, the method further includes:

[0033] The average rating is displayed.

[0034] Optionally, after obtaining the feedback information of the target user, the method further includes:

[0035] The feedback information of the monthly card users is filtered out from the feedback information of the target users, and the monthly card users are included in the target users.

[0036] A second aspect of the present application provides a device for quantifying parking lot service quality, comprising:

[0037] an acquisition unit, configured to acquire feedback information of a target user, wherein the target user includes a user who has generated order information in a target parking lot, and the feedback information includes rating information and comment information on the target parking lot;

[0038] A first calculation unit, configured to calculate the scoring information according to a scoring rule preset in a scoring model to obtain a final score;

[0039] A first determining unit, configured to determine at least one recommended tag from a tag library according to the final score and the comment information;

[0040] A sending unit, configured to send the recommended tag to the target user;

[0041] A receiving unit, configured to receive a target tag selected by the target user from the recommended tags;

[0042] An updating unit, configured to update the click rate of the corresponding tag in the tag library according to the target tag;

[0043] The second determining unit is used to determine and display the label according to the updated click rate.

[0044] A third aspect of the present application provides a device for quantifying parking lot service quality, comprising:

[0045] CPU, memory, input and output interfaces, wired or wireless network interfaces, and power supply;

[0046] The memory is a short-term storage memory or a persistent storage memory;

[0047] The central processing unit is configured to communicate with the memory and execute instruction operations in the memory to perform the method described in the first aspect.

[0048] A fourth aspect of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a computer, enable the computer to execute the method described in the first aspect.

[0049] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0050] In this application, the scoring information of the target users who have placed orders in the target parking lot is obtained, and the scoring information is scored according to the scoring model rules to obtain the final score. According to the final score and the target user's comment information, the corresponding tag is selected from the tag library for the target user to choose. After the target user makes the selection, the click rate of each tag in the tag library is updated, and the tag to be displayed is determined according to the click rate. By converting user feedback into the form of tag display, that is, quantifying the quality of parking lot services, it can provide users with a decision-making basis when choosing parking lot services. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solution in the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 A schematic diagram of an embodiment of a method for quantifying parking lot service quality in this application;

[0053] Figure 2 This is a schematic diagram of another embodiment of the method for quantifying parking lot service quality in this application;

[0054] Figure 3 A schematic diagram of a device for quantifying parking lot service quality in this application;

[0055] Figure 4 Another schematic diagram of the device for quantifying the parking lot service quality in this application;

[0056] Figure 5 A schematic diagram of a physical device for quantifying parking lot service quality in this application. DETAILED DESCRIPTION

[0057] The present application provides a method, device and storage medium for quantifying the quality of parking lot services, which are used to provide a decision basis for users when selecting parking lot services.

[0058] The method of quantifying the service quality of a parking lot in this application can quantify the feedback on the service quality of a parking lot from users who have generated orders in the parking lot, and convert user ratings and user comments into labels for display, which can provide references for other users browsing this parking lot service. In addition, it can also provide relevant references for parking lot managers, such as improving services related to labels or expanding new businesses. When all parking lots can be calculated using scores, the platform can find parking lots with excellent service quality based on the scores. According to the labels selected by users, analyze the excellent conditions of each business in detail. Give specific improvement suggestions to other low-scoring parking lots. You can also use high-scoring parking lots as samples to make revenue forecasts and provide personalized business development suggestions for the parking lot. This method can be applied to a variety of different parking lot services, such as car rental services, parking services, etc., which are not specifically limited here.

[0059] The following is a brief description of the method for quantifying parking lot service quality in this application:

[0060] See also Figure 1 , Figure 1 This is an embodiment of the method for quantifying the parking lot service quality in the present application. The following is a specific description of the method applied to the system, including:

[0061] 101. The system obtains feedback information from target users, including users who have generated order information in the target parking lot, and the feedback information includes rating information and comment information on the target parking lot

[0062] In this embodiment, in order to ensure the accuracy and authenticity of the data, feedback information of target users who have only received services in the target parking lot will be obtained in a targeted manner, including users who have made online reservations for services and received services, as well as users who received services offline. Feedback information of services that have only been reserved but not received will not be obtained. The feedback information contains the target user's rating information and comment information on the service quality of the target parking lot. The rating information can be set to 1-5 points, and the target user will rate within this score range. The comment can be input by the user, or service-related comments can be pre-set, and the target user can select the comment. In order to allow the target user to complete the evaluation, an evaluation entry can be placed in a series of entries such as the target user completing payment, viewing orders, and message notifications.

[0063] 102. The system calculates the scoring information according to the scoring rules preset in the scoring model to obtain the final score.

[0064] In this embodiment, after obtaining the score of the target user, the target user is scored separately according to the different weights of each user. The scoring model is a scoring model established based on the user's personal aspects such as "user integrity", "parking behavior", "number of payments", "evaluation quality", and "user level", and the scoring rules are pre-set in the scoring model. Different users have different weights to reduce the occurrence of distortion in the scoring results. For example, user A has higher integrity, more payments, and a higher user level than user B, then the weight coefficients of these three aspects of user A are higher than user B. User B's parking behavior and evaluation quality are higher than user A, so the weight coefficients of these two aspects of user B are higher than user A. Since the final score is based on different weights of various aspects, the distortion of the score is reduced. For example, the scoring rule can be: User A's final score for a parking lot = User A's score * coefficient obtained by the integrity model * coefficient obtained by the current parking behavior model * coefficient obtained by the payment number model * coefficient obtained by the evaluation content model * coefficient of the user level system. It can be understood that the model can be set according to specific needs, and it is not limited here.

[0065] 103. The system determines at least one recommended tag from the tag library based on the final score and comment information

[0066] In this embodiment, after obtaining the final score and analyzing the comment information, the system determines at least one tag that needs to be recommended to the user from the tag library. The specific recommendation method can be to guess the tag behind the feedback information through the feedback information of the target user, and recommend it to the user, that is, when the score is high and the comment information center contains more positive words, the recommended tag is also a positive tag, and when the score is low and the comment information center contains more negative words, the recommended tag is also a negative tag. The recommendation of this tag can be one or more, and the specifics are not limited here. It should be explained that the tag library uses big data technology to run out high-frequency words in feedback and customer complaints, and then uses exhaustive enumeration method based on keywords to establish a tag library for parking service quality. Since basically every possible situation is exhausted, the tags in the tag library are relatively comprehensive.

[0067] 104. The system sends recommended tags to target users

[0068] In this embodiment, after determining the tags recommended to the target user, the system recommends tags to the target user, so that the target user can select the recommended tags when there are many recommended tags, so that the tag information is more accurate.

[0069] 105. The system receives the target tag selected by the target user from the recommended tags

[0070] In this embodiment, after the user has provided feedback, the system quickly generates recommended tags and recommends them to the target user for selection. The tags selected by the user in the recommendation are the target tags, and the target tags are returned to the system so that the system knows which tags the target user has selected.

[0071] 106. The system updates the click rate of the corresponding tag in the tag library according to the target tag

[0072] In this embodiment, after determining the target tag, the system updates the click rate of the corresponding tag in the tag library. For example, if the target user selects the tags "good attitude" and "quick solution", the click rate of "good attitude" in the tag library is 100, and the click rate of "quick solution" in the tag library is 100, then after the update, the click rate of the "good attitude" tag is 101, and the click rate of the "quick solution" tag is 101.

[0073] 107. The system determines the label to be displayed based on the updated click rate and displays it

[0074] After the click rate is updated, the tags to be displayed are determined based on the click rate. The tags with the highest click rate can be selected as the tags to be displayed, or the tags with the largest change in click rate within a period of time, such as a week, that is, the tags with the most clicks are selected as the tags to be displayed. After the selection is determined, the tags are displayed on the display interface of the parking service to provide a visual reference for people browsing the parking service.

[0075] Optionally, when displaying a tag, the click rate can also be displayed to let the browsing crowd know how many people have selected the tag.

[0076] In this embodiment, by obtaining the rating information of the target users who have placed orders in the target parking lot, the rating information is scored according to the rating model rules to obtain the final rating, and the corresponding tags are selected from the tag library based on the final rating and the target user's comment information for the target user to choose. After the selection, the click rate of each tag in the tag library is updated, and the tags are displayed according to the click rate. By converting user feedback into the form of tag display, that is, quantifying the quality of parking lot services, it can provide users with decision-making basis when choosing parking lot services.

[0077] In this embodiment, the tags in the tag library include positive tags and negative tags. The system determines the tags in the tag library by screening out the keywords in the comment information of the target user, and determines the ratio of the recommended positive tags and negative tags through the scoring information. This embodiment will be described in detail below with reference to the accompanying drawings.

[0078] See also Figure 2 , Figure 2This is another embodiment schematic diagram of the method for quantifying the parking lot service quality in this application. The following is a detailed description of the method applied to the system:

[0079] 201. The system obtains feedback information from target users, including users who have generated order information in the target parking lot, and the feedback information includes rating information and comment information on the target parking lot.

[0080] Step 201 in this embodiment is similar to the aforementioned Figure 1 Step 101 in the illustrated embodiment is similar and will not be described in detail here.

[0081] 202. The system filters out the feedback information of monthly card users from the feedback information of target users. The target users include monthly card users.

[0082] In this embodiment, in order to further ensure that the display of labels is as real and objective as possible, the feedback information of monthly card users needs to be screened out, because monthly card users may make multiple evaluations, and the evaluation content may be very similar, which will affect the labels that need to be displayed. Therefore, monthly card users need to be screened out. In addition, quarterly card users and annual card users can also be processed accordingly. Optionally, monthly card users may not be guided to evaluate the parking lot, that is, no evaluation entry is placed at the entrance where monthly card users complete payment, order viewing, and message notification.

[0083] 203. The system calculates the scoring information according to the scoring rules preset in the scoring model to obtain the final score.

[0084] Step 203 in this embodiment is similar to the aforementioned Figure 1 Step 102 in the illustrated embodiment is similar and will not be described in detail here.

[0085] 204. System screening of keywords in comment information

[0086] In this embodiment, the system filters the keywords in the target user's comment information. For example, if the target user's comment information is: "The staff is enthusiastic, the fees are cheap, and the experience is comfortable, but it is relatively remote and hard to find", specific filtering software can be used to filter out "enthusiastic attitude", "cheap fees", "comfortable" and "remote".

[0087] 205. The system determines at least one recommended tag from the tag library based on the keyword, and the tag library contains positive tags and negative tags

[0088] In this embodiment, the tags in the tag library are divided into two categories. The first category is positive tags, that is, tags generated by positive comments given by users, and the second category is negative tags, that is, tags generated by negative comments given by target users. Tags in the tag library will be associated with keywords. For example, "enthusiastic attitude" can be associated with the tag "enthusiastic attitude", "cheap charges" can be associated with the tag "cheap", and "remote" can be associated with the keywords "difficult to find the location" and "remote", so at least one recommended tag can be determined by keywords. It can be understood that a keyword can be associated with only one tag, a keyword can be associated with multiple tags, and multiple keywords can be associated with only one tag, which is not limited here.

[0089] 206. The system determines the ratio of positive and negative labels recommended based on the final score.

[0090] After determining the tags that need to be recommended to the target user, determine the proportion of positive tags and negative tags to be recommended based on the score. For example, the scoring range is 1 to 5 points. If the user scores 1 point, then it is obvious that the target user is generally dissatisfied with the parking lot service. The system will recommend to the target user 100% of the negative tags associated with this business based on the business handled by the target user. When the target user scores 5 points, it means that the target user is very satisfied with the parking lot service, and the proportion of positive tags recommended to the target user for this business is 100%. If the user scores between 2 and 4 points, we will recommend them in proportion. For example, if the target user scores 2 points, the negative tags account for 60% and the positive tags account for 40%.

[0091] 207. The system sends positive and negative labels to the target user in proportion

[0092] After determining the ratio, recommend tags to the target user according to the ratio. For example, if 10 recommended tags need to be recommended to the target user, determine that the negative tags recommended to the target user for this service account for 100%, that is, 10 negative tags, and determine that the positive tags recommended to the target user for this service account for 100%, that is, 10 positive tags. Determine that negative tags account for 60% and positive tags account for 40%, and recommend 6 negative tags and 4 positive tags to the target user. The tag can be randomly selected from the positive and negative tags that match this service. By determining the ratio of positive and negative tags by determining the target user's rating information, it is possible to guess the tags that the target user may choose as much as possible, and recommend the tags that the target user wants to choose as much as possible.

[0093] 208. The system receives the target tag selected by the target user from the recommended tags

[0094] 209. The system updates the click rate of the corresponding tag in the tag library according to the target tag

[0095] Steps 208 to 209 in this embodiment are similar to those in the previous embodiment. Figure 1 Steps 105 to 106 in the illustrated embodiment are similar and will not be described in detail here.

[0096] 210. The system sorts all tags in the tag library according to the updated click rate to obtain the sorting result

[0097] In this embodiment, in order to better recommend tags that the target user may want to select, before recommending tags to the target user, the server can sort the tags and give priority to recommending the tags with the highest ranking. The sorting can be sorted by click rate. The higher the click rate, the higher the ranking. For example, 101 people clicked on the "good attitude" tag and 100 people clicked on the "quick solution" tag. Therefore, the "good attitude" tag > the "quick solution" tag, and the tags are sorted according to this rule.

[0098] 211. The system calculates the average score based on the rating information

[0099] In this embodiment, after obtaining the rating information of the target user, the average rating is calculated based on the rating information. For example, if the target users' ratings for the parking lot service quality are "1", "2", "3", "4", and "5" respectively, then the average score of the parking lot is 3 points.

[0100] 212. The system determines the ratio of positive and negative labels to be displayed based on the average rating

[0101] After obtaining the average score after parking, the ratio of positive labels to negative labels to be displayed is determined according to the average score. The specific determination method is similar to step 106 and will not be repeated here.

[0102] 213. The system determines the positive and negative labels to display based on the ratio

[0103] Step 213 in this embodiment is similar to step 207 and will not be described again here.

[0104] 214. The system determines the positive and negative labels to be displayed based on the sorting results and displays them

[0105] In this embodiment, after obtaining the ranking results and determining the ratio, the positive tags and negative tags recommended according to the ratio are ranked higher. By determining to display positive tags and negative tags in different ratios, it is avoided that the user sees all positive or all negative tags when browsing, so that the browsing user can make a comprehensive consideration on whether to choose this parking service.

[0106] 215. System Display Average Rating

[0107] The comprehensive rating can also be displayed on the page of the parking lot service line, so that browsing users can make a quick comparison with other parking lot services based on the average rating, thereby improving the user experience.

[0108] 216. When the target user's feedback exceeds the preset time, the system recalculates the target user's final score according to the scoring rules for feedback exceeding the preset time in the scoring model.

[0109] In this embodiment, since the parking lot service will not remain unchanged, it will change due to many factors, such as personnel changes, service item upgrades, etc. Therefore, the user's previous score will affect the overall score of the current parking lot service, and the final score needs to be recalculated according to the calculation rules for feedback information exceeding the preset time. The rule will calculate the weight according to the order time, evaluation date, user's credit score, behavior, and the score will be updated regularly. The longer the order time, the gradually reduced weight, that is, the weight value of the target user's feedback information will be reduced to avoid affecting the overall evaluation of the current parking lot service quality.

[0110] 217. The system recalculates the average score based on the recalculated final score

[0111] In this embodiment, after the final score is recalculated according to the calculation rules for feedback information exceeding the preset time, the average score is calculated based on the re-obtained final score, and the proportion of positive labels and negative labels to be displayed is re-determined. By recalculating the final score and average score of the target user according to different weights, the timeliness of the information is guaranteed and the influence of past information is reduced.

[0112] In this embodiment, by obtaining the rating information of the target user who has placed an order in the target parking lot, the rating information is scored according to the rating model rules to obtain the final rating, and the corresponding positive and negative tags are selected from the tag library according to the final rating and the target user's comment information for the target user to choose. After the selection, the click rate of each tag in the tag library is updated, the tags are sorted according to the click rate, and the average rating is calculated, and the tags are displayed according to the click rate and the average rating. By converting user feedback into a form of tag display, that is, quantifying the quality of the parking lot service, it can provide a decision-making basis for users when choosing parking lot services. In addition, the positive tags and negative tags recommended according to the ratio are ranked higher, and the sorting can better recommend tags that the target user may want to choose. By determining to display different proportions of positive tags and negative tags, it is avoided that the user sees all positive or all negative tags when browsing, so that the browsing user can make a comprehensive consideration on whether to choose this parking lot service.

[0113] The above describes the method for quantifying the parking lot service quality. The following describes the device for quantifying the parking lot service quality:

[0114] See also Figure 3 , a device for quantifying parking lot service quality in this application includes:

[0115] The acquisition unit 301 is used to acquire feedback information of target users, where the target users include users who have generated order information in the target parking lot, and the feedback information includes rating information and comment information on the target parking lot;

[0116] The first calculation unit 302 is used to calculate the scoring information according to the scoring rules preset in the scoring model to obtain a final score;

[0117] A first determining unit 303 is used to determine at least one recommended tag from the tag library according to the final score and comment information;

[0118] A sending unit 304, configured to send a recommendation tag to a target user;

[0119] A receiving unit 305 is used to receive a target tag selected by a target user from the recommended tags;

[0120] An updating unit 306, configured to update the click rate of the corresponding tag in the tag library according to the target tag;

[0121] The second determining unit 307 is used to determine and display the label according to the updated click rate.

[0122] In this embodiment, the acquisition unit 301 acquires the rating information of the target user who has placed an order in the target parking lot. The first calculation unit 302 scores the rating information according to the rating model rules to obtain the final rating. The first determination unit 303 selects the corresponding tag from the tag library based on the final rating and the target user's comment information for the target user to select. The update unit 306 updates the click rate of each tag in the tag library after the target user selects. The second determination unit 307 determines the tag to be displayed based on the click rate. By converting user feedback into the form of tag display, that is, quantifying the quality of parking lot services, it can provide users with a decision-making basis when selecting parking lot services.

[0123] See also Figure 4 , another device for quantifying the parking lot service quality in this application includes:

[0124] The acquisition unit 401 is used to acquire feedback information of target users, where the target users include users who have generated order information in the target parking lot, and the feedback information includes rating information and comment information on the target parking lot;

[0125] A screening unit 402 is used to screen out the feedback information of monthly card users from the feedback information of target users, where the target users include monthly card users;

[0126] The first calculation unit 403 is used to calculate the scoring information according to the scoring rules preset in the scoring model to obtain a final score;

[0127] The first determining unit 404 includes:

[0128] A screening module 4041 is used to screen keywords in the review information;

[0129] A first determination module 4042 is used to determine at least one recommended tag from a tag library according to the keyword, where the tag library includes positive tags and negative tags;

[0130] The second determination module 4043 is used to determine the ratio of positive labels and negative labels recommended according to the final score;

[0131] The sending unit 405 includes:

[0132] A sending module 4051 is used to send positive labels and negative labels to target users in proportion;

[0133] A receiving unit 406 is used to receive a target tag selected by a target user from the recommended tags;

[0134] An updating unit 407, configured to update the click rate of the corresponding tag in the tag library according to the target tag;

[0135] The second determining unit 408 includes:

[0136] A sorting unit 4081 is used to sort all tags in the tag library according to the updated click rate to obtain a sorting result;

[0137] A calculation module 4082, used for calculating an average score according to the score information;

[0138] The third determination module 4083 is used to determine the ratio of positive labels and negative labels to be displayed according to the average score;

[0139] A fourth determination module 4084 determines the positive labels and negative labels to be displayed according to the ratio;

[0140] A fifth determination module 4085 determines and displays positive labels and negative labels according to the sorting result;

[0141] A display unit 409 is used to display the average rating;

[0142] The second calculation unit 410 is used to recalculate the final score of the target user according to the scoring rule of feedback information exceeding the preset time in the scoring model when the feedback information of the target user exceeds the preset time;

[0143] The third calculating unit 411 is used to recalculate the average score according to the recalculated final score.

[0144] In this embodiment, the acquisition unit 401 acquires the rating information of the target user who has placed an order in the target parking lot, the first calculation unit 403 scores the rating information according to the rating model rules to obtain the final rating, the first determination unit 404 selects the corresponding positive label and negative label from the label library according to the final rating and the target user's comment information for the target user to choose, the update unit 407 updates the click rate of each label in the label library after the target user selects, the sorting unit 4081 sorts the labels according to the click rate, the calculation module 4082 calculates the average rating, and the fifth determination module 4085 displays the label according to the click rate and the average rating. By converting user feedback into the form of label display, that is, quantifying the quality of the parking lot service, it can provide a decision-making basis for users when selecting parking lot services. In addition, the positive labels and negative labels recommended according to the ratio are the labels with the highest ranking, and the sorting can better recommend the labels that the target user may want to choose. By determining to display different proportions of positive labels and negative labels, it is avoided that the user sees all positive or all negative labels when browsing, so that the browsing user can make a comprehensive consideration on whether to choose this parking lot service.

[0145] See also Figure 5, a schematic diagram of a physical device for quantifying parking lot service quality in this application includes:

[0146] CPU 502, memory 501, input / output interface 503, wired or wireless network interface 504 and power supply 1005;

[0147] The memory 501 is a temporary storage memory or a permanent storage memory;

[0148] The CPU 502 is configured to communicate with the memory 501 and execute instructions in the memory 501 to perform Figure 1 to Figure 2 The steps in any of the embodiments shown in .

[0149] The present application provides a computer-readable storage medium, including instructions, which, when executed on a computer, enable the computer to execute Figure 1 to Figure 2 The method corresponding to any one of the embodiments.

[0150] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0151] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0152] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0153] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0154] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), disk or optical disk and other media that can store program code.

Claims

1. A method for quantifying parking lot service quality, characterized in that: include: Acquire feedback information of target users, wherein the target users include users who have generated order information in the target parking lot, and the feedback information includes rating information and comment information on the target parking lot; Calculating the scoring information according to the scoring rules preset in the scoring model to obtain a final score; Determining at least one recommended tag from a tag library according to the final score and the comment information; Sending the recommended tag to the target user; Receiving a target tag selected by the target user from the recommended tags; Update the click rate of the corresponding tag in the tag library according to the target tag; Determine the label to be displayed based on the updated click rate and display it; Determining at least one recommended tag from a tag library according to the final score and the comment information includes: Filtering keywords in the review information; Determining at least one recommended tag from the tag library according to the keyword, wherein the tag library includes positive tags and negative tags; Determine the ratio of positive labels and negative labels recommended among the recommended labels according to the final score; The sending the recommended tag to the target user comprises: Sending positive labels and negative labels to the target user according to the ratio; The step of determining the label to be displayed according to the updated click rate and displaying the label includes: Sorting all tags in the tag library according to the updated click rate to obtain a sorting result; The labels to be displayed are determined according to the sorting results and displayed.

2. The method according to claim 1, characterized in that Before determining the displayed labels according to the sorting results and displaying them, the method further includes: Calculate an average score based on the score information; Determine the ratio of the positive labels and the negative labels to be displayed according to the average score; Determining the positive label and the negative label to be displayed according to the ratio; Determining the display label according to the sorting result and displaying it includes: The positive labels and negative labels to be displayed are determined according to the sorting results and displayed.

3. The method according to claim 2, characterized in that After determining the label to be displayed according to the click rate and displaying it, the method further includes: When the feedback information of the target user exceeds the preset time, the final score of the target user is recalculated according to the scoring rule of the feedback information exceeding the preset time in the scoring model; Recalculate the average score based on the recalculated final score.

4. The method according to claim 2, characterized in that: After determining the label to be displayed according to the updated click rate and displaying it, the method further includes: The average rating is displayed.

5. The method according to any one of claims 1 to 4, characterized in that After obtaining the feedback information of the target user, the method further includes: The feedback information of the monthly card users is filtered out from the feedback information of the target users, and the monthly card users are included in the target users.

6. A device for quantifying the quality of parking lot service, characterized in that: include: an acquisition unit, configured to acquire feedback information of a target user, wherein the target user includes a user who has generated order information in a target parking lot, and the feedback information includes rating information and comment information on the target parking lot; A first calculation unit, configured to calculate the scoring information according to a scoring rule preset in a scoring model to obtain a final score; A first determining unit, configured to determine at least one recommended tag from a tag library according to the final score and the comment information; A sending unit, configured to send the recommended tag to the target user; A receiving unit, configured to receive a target tag selected by the target user from the recommended tags; An updating unit, configured to update the click rate of the corresponding tag in the tag library according to the target tag; A second determining unit, configured to determine and display a label to be displayed according to the updated click rate; The first determining unit includes: A screening module is used to screen keywords in the review information; A first determination module is used to determine at least one recommended tag from a tag library according to the keyword, where the tag library includes positive tags and negative tags; The second determination module is used to determine the ratio of positive labels and negative labels recommended according to the final score; The sending unit includes: A sending module, used to send positive labels and negative labels to target users in proportion; The second determining unit is specifically configured to: Used to sort all tags in the tag library according to the updated click rate to obtain the sorting result; The labels to be displayed are determined according to the sorting results and displayed.

7. A device for quantifying the quality of parking lot service, characterized in that: include: CPU, memory, input and output interfaces, wired or wireless network interfaces, and power supply; The memory is a transient storage memory or a persistent storage memory; The central processing unit is configured to communicate with the memory and execute instructions in the memory to perform the method according to any one of claims 1 to 5.

8. A computer-readable storage medium comprising instructions, which, when executed on a computer, enable the computer to execute the method according to any one of claims 1 to 5.

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