Optimization method and device of logistics order splitting system, electronic equipment and storage medium
By automatically matching and updating the keyword library in the logistics order allocation system, the problem of keyword data maintenance errors was solved, the accuracy and efficiency of order allocation were improved, and the error rate and labor costs were reduced.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING JINGDONG ZHENSHI INFORMATION TECH CO LTD
- Filing Date
- 2022-04-27
- Publication Date
- 2026-06-19
AI Technical Summary
Existing logistics companies have issues with keyword data maintenance errors and untimely updates in their keyword matching strategies, leading to incorrect site matching for logistics orders and affecting the accuracy and efficiency of order allocation.
By obtaining keywords from the keyword library of the logistics order allocation system and matching them with historical order address information in the address library, invalid keywords are set, and expanded keywords are determined based on the historical order addresses of invalid keywords. The keyword library is automatically updated to ensure the correctness of keywords.
It improved the order allocation accuracy of the logistics order allocation system, reduced the error rate, increased logistics speed, and reduced labor costs.
Smart Images
Figure CN117009555B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of computer technology, specifically to the field of logistics data processing, and particularly to an optimization method, apparatus, electronic device, and storage medium for a logistics order allocation system. Background Technology
[0002] In modern logistics technology, the degree of automation in order allocation is a key factor determining the efficiency of logistics companies. Currently, major logistics companies are using keyword matching strategies as a means of automating order allocation to improve efficiency.
[0003] However, the maintenance of keyword data is currently mainly done manually, which can lead to problems such as incorrect keyword data or untimely updates, resulting in incorrect matching of logistics order sites. Summary of the Invention
[0004] This application provides an optimization method, apparatus, electronic device, and storage medium for a logistics order splitting system.
[0005] According to a first aspect of this application, an optimization method for a logistics order splitting system is provided, comprising:
[0006] Retrieve keywords from the keyword library of the logistics order allocation system;
[0007] The keyword is matched with historical order address information in the address database to obtain N first historical order addresses that match the keyword; where N is a positive integer.
[0008] Since the N first historical order addresses belong to multiple sites, the keyword is set as an invalid keyword;
[0009] Based on the N first historical order addresses and the address database, determine the expanded keywords for the invalid keywords;
[0010] The expanded keywords are written into the keyword library.
[0011] In some embodiments of this application, determining the expanded keywords of the invalid keywords based on the N first historical order addresses and the address database includes:
[0012] The first historical order address of the i-th order is segmented to obtain M candidate keywords; where i is a positive integer less than or equal to N, and M is a positive integer;
[0013] The j-th candidate keyword is matched with the historical order address information in the address database to obtain the second historical order address that matches the j-th candidate keyword; where j is a positive integer less than or equal to M;
[0014] The site to which the second historical order address belongs is compared with the site to which the i-th first historical order address belongs;
[0015] Since the originating site of the second historical order address is consistent with the originating site of the i-th first historical order address, the j-th candidate keyword is used as the expanded keyword of the invalid keyword.
[0016] The step of performing word segmentation on the i-th first historical order address to obtain M candidate keywords includes:
[0017] The administrative region information and additional keywords in the i-th first historical order address are deleted;
[0018] The i-th first historical order address after deletion is segmented to obtain M candidate keywords.
[0019] In some embodiments of this application, writing the expanded keywords into the keyword library includes:
[0020] The coordinate information of the expanded keyword is determined based on the coordinate information of the address that matches the expanded keyword in the address database;
[0021] The expanded keyword and its coordinate information are written into the keyword database.
[0022] In some embodiments of this application, determining the coordinate information of the expanded keyword based on the coordinate information of the address matching the expanded keyword in the address database includes:
[0023] Obtain the first address information containing coordinate information from the address database;
[0024] The expanded keyword is matched with the first address information to obtain the third historical order address that matches the expanded keyword;
[0025] The coordinate information of the third historical order address is extracted, and the average of the extracted coordinate information is calculated to obtain the coordinate information of the expanded keyword.
[0026] According to a second aspect of this application, an optimization device for a logistics order splitting system is provided, comprising:
[0027] The first acquisition module is used to acquire keywords from the keyword library of the logistics order allocation system;
[0028] The second acquisition module is used to match the keyword with historical order address information in the address database to obtain N first historical order addresses that match the keyword; wherein, N is a positive integer;
[0029] The setting module is used to set the keyword as an invalid keyword in response to the fact that the N first historical order addresses belong to multiple sites;
[0030] The determination module is used to determine the expanded keywords of the invalid keywords based on the N first historical order addresses and the address database;
[0031] The writing module is used to write the expanded keywords into the keyword library.
[0032] In some embodiments of this application, the determining module includes:
[0033] The first acquisition unit is used to perform word segmentation on the i-th first historical order address to obtain M candidate keywords; wherein i is a positive integer less than or equal to N, and M is a positive integer;
[0034] The second acquisition unit is used to match the j-th candidate keyword with the historical order address information in the address database to obtain the second historical order address that matches the j-th candidate keyword; wherein, j is a positive integer less than or equal to M;
[0035] The comparison unit is used to compare the site to which the second historical order address belongs with the site to which the i-th first historical order address belongs.
[0036] The determining unit is configured to, in response to the fact that the attribution site of the second historical order address is consistent with the attribution site of the i-th first historical order address, use the j-th candidate keyword as the expanded keyword of the invalid keyword.
[0037] Specifically, the first acquisition unit is used for:
[0038] The administrative region information and additional keywords in the i-th first historical order address are deleted;
[0039] The i-th first historical order address after deletion is segmented to obtain M candidate keywords.
[0040] In some embodiments of this application, the writing module includes:
[0041] The determining unit is used to determine the coordinate information of the expanded keyword based on the coordinate information of the address that matches the expanded keyword in the address database;
[0042] The writing unit is used to write the expanded keyword and its coordinate information into the keyword library.
[0043] Furthermore, the determining unit is specifically used for:
[0044] Obtain the first address information containing coordinate information from the address database;
[0045] The expanded keyword is matched with the first address information to obtain the third historical order address that matches the expanded keyword;
[0046] The coordinate information of the third historical order address is extracted, and the average of the extracted coordinate information is calculated to obtain the coordinate information of the expanded keyword.
[0047] According to a third aspect of this application, an electronic device is provided, comprising:
[0048] At least one processor; and
[0049] A memory communicatively connected to the at least one processor; wherein,
[0050] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.
[0051] According to a fourth aspect of this application, a non-transitory computer-readable storage medium is provided that stores computer instructions for causing the computer to perform the method described in the first aspect above.
[0052] According to the technical solution of this application, by matching keywords in the keyword library of the logistics order allocation system with historical order address information in the address library, and setting keywords belonging to multiple sites for the matched historical order addresses as invalid keywords, the correctness of keywords can be automatically verified, thereby reducing the error rate of order allocation in the logistics order allocation system. Furthermore, this solution determines expanded keywords for invalid keywords by matching historical order addresses with the address library, and automatically writes the expanded keywords into the keyword library. This is equivalent to automatically updating the keyword library by expanding invalid keywords, thereby solving the problem of incorrect site allocation of logistics orders due to errors or delays in manual keyword maintenance. This not only improves the accuracy of order allocation in the logistics order allocation system but also increases logistics speed and reduces labor costs.
[0053] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description
[0054] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this application. Wherein:
[0055] Figure 1 A flowchart illustrating an optimization method for a logistics order splitting system provided in this application embodiment;
[0056] Figure 2 This is a flowchart illustrating a method for obtaining expanded keywords from invalid keywords in an embodiment of this application.
[0057] Figure 3 This is another flowchart for obtaining expanded keywords of invalid keywords in an embodiment of this application;
[0058] Figure 4 A flowchart illustrating an optimization method for a logistics order splitting system provided in the application embodiment;
[0059] Figure 5 This is a structural block diagram of an optimization device for a logistics order splitting system provided in an embodiment of this application;
[0060] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of this application is shown. Detailed Implementation
[0061] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.
[0062] First, it should be noted that the user data involved in the embodiments of this application has been authorized, acquired, processed, and transmitted in accordance with legal and regulatory requirements.
[0063] It should also be noted that in modern logistics technology, the degree of automation in order allocation is a key factor determining the efficiency of logistics companies. Currently, major logistics companies all use keyword matching strategies as a means of automating order allocation to improve efficiency.
[0064] However, currently, keyword data maintenance is mainly done manually, which can lead to problems such as incorrect keyword data maintenance or untimely updates, resulting in incorrect site matching for logistics orders. For example, there might be a residential community a1 within the service area of site A and a residential community b1 within the service area of site B. The keyword database contains the keyword k1, which can be successfully matched with the address of both community a1 and community b1. However, the coordinates of keyword k1 belong to site A, causing logistics orders with the address of community b1 to be mistakenly sent to site A.
[0065] To address the aforementioned issues, this application proposes an optimization method, apparatus, electronic device, and storage medium for a logistics order splitting system.
[0066] It should be noted that the logistics order allocation system mentioned in this application embodiment is a system for automatically allocating logistics orders. The order allocation process includes a process of assigning delivery stations to the nearest location based on the order's address information using a keyword matching strategy, and may also include a process of allocating logistics orders to their respective administrative regions based on administrative region information. In this application embodiment, the main focus is on optimizing the keyword library in the keyword matching strategy to improve the accuracy and efficiency of the logistics order allocation system's automatic order allocation.
[0067] Figure 1 This is a flowchart illustrating an optimization method for a logistics order allocation system proposed in an embodiment of this application. It should be noted that the optimization method for the logistics order allocation system in this embodiment can be used in the optimization device for the logistics order allocation system in this embodiment, and this device can be applied to electronic devices. Figure 1 As shown, the method may include the following steps:
[0068] Step 101: Obtain keywords from the keyword library of the logistics order splitting system.
[0069] In some embodiments of this application, the logistics order allocation system includes a maintained keyword database. The keyword information in this database can be maintained by data maintenance personnel at each site, or by other methods. The relevant information for each keyword in the keyword database may include the keyword itself, the fourth-level administrative region information (province, city, district, county) to which the keyword belongs, and the coordinate information of the keyword. When allocating orders, the logistics order allocation system can match the logistics order address with the keywords in the keyword database for that administrative region, and determine the destination site based on the coordinates of the keywords matching the logistics order address and the business scope of each site, thereby automatically distributing the logistics order to its destination site.
[0070] In some embodiments of this application, a site can refer to a location used to process logistics orders within its corresponding business scope, such as a courier delivery station. The business scope of a site refers to the coordinate range of logistics orders that can be processed, defined for the site based on the needs of the actual application scenario. As an example, site A is a courier delivery station, and its business scope refers to the coordinate range of logistics orders that can be delivered. For example, the business scope can be the range of four corner coordinates formed by four points: a(x1, y1), b(x2, y2), c(x3, y3), and d(x4, y4).
[0071] Step 102: Match the keyword with the historical order address information in the address database to obtain N first historical order addresses that match the keyword; where N is a positive integer.
[0072] In some embodiments of this application, the address database refers to a database used to store address information of historically successfully delivered logistics orders. The address database may include historical order address information, attribution station information, etc. The historical order address information refers to the address information in historically successfully delivered logistics orders, and there is a one-to-one relationship between the attribution station and the historical order address. For example, the attribution station of historical order address A refers to the station to which the logistics order for historical order address A was actually delivered.
[0073] In other words, for each keyword in the keyword database, the keyword is matched with the historical order address information under the administrative region of the site to which the keyword belongs in the address database to obtain N historical order addresses that match the keyword, which are used to determine whether the sites to which the N historical order addresses that match the keyword belong are the same site.
[0074] In some embodiments of this disclosure, in order to ensure the consistency of the matching process, the matching method used when matching keywords with historical order address information in the address database can be the same as the matching method used by the logistics order allocation system when allocating orders using the keyword database.
[0075] Step 103: In response to the fact that N first historical order addresses belong to multiple sites, the keywords are set as invalid keywords.
[0076] It's understandable that if N first-historical order addresses belong to multiple sites, it means that when the logistics order allocation system uses this keyword to match order addresses for order allocation, not only will the addresses of logistics orders from the site corresponding to that keyword match, but the addresses of logistics orders from other sites will also match that keyword. This could cause logistics orders from other sites to be mistakenly allocated to the site corresponding to that keyword, resulting in order allocation errors. To prevent this keyword from affecting subsequent order allocation operations, it can be set as an invalid keyword, preventing it from participating in order address matching.
[0077] As an example, the method to determine whether N first historical order addresses belong to multiple sites can be as follows: Based on the relevant information in the address database, determine the site to which each of the N first historical order addresses belongs, matching the keywords; compare the sites to which each first historical order address belongs to each other to determine whether the N first historical order addresses belong to the same site; if the sites to which the N first historical order addresses belong are not the same site, then the N first historical order addresses belong to multiple sites.
[0078] In this embodiment, for each keyword in the keyword library, if N first historical order addresses matching that keyword belong to multiple sites, then the keyword is set as an invalid keyword. This can be achieved by adding a status field to each keyword in the keyword library. If N first historical order addresses matching that keyword belong to multiple sites, then the status field of that keyword is set to invalid. When the logistics order allocation system calls keywords from the keyword library to allocate orders, it filters out keywords with invalid status fields and no longer uses invalid keywords for order address matching.
[0079] Step 104: Based on the N first historical order addresses and the address database, determine the expanded keywords for invalid keywords.
[0080] In other words, after a keyword is set as invalid, in order for the logistics order allocation system to accurately and automatically allocate subsequent logistics orders related to the N first historical order addresses that match that keyword, it is necessary to add keywords back to these addresses.
[0081] As an example, keywords can be extracted based on N first historical order addresses. The extracted keywords are then processed using step 102 above. The extracted keywords are then verified against the matched historical order addresses to ensure that the keywords do not cross-site with the address. Keywords that meet this condition are then used as expanded keywords for invalid keywords.
[0082] Step 105: Write the expanded keywords into the keyword library.
[0083] In other words, by adding expanded keywords to the keyword library, the logistics order allocation system can use the expanded keywords in the keyword library to match the order address when allocating logistics orders to sites, thereby improving the accuracy and efficiency of order allocation.
[0084] It should be noted that the optimization method of the logistics order allocation system in this application embodiment can be performed periodically according to the needs of actual application scenarios to regularly update the keyword library and improve the accuracy of automatic order allocation by the logistics order allocation system. Furthermore, the optimization process of the logistics order allocation system does not affect its normal use; the keyword library of the logistics order allocation system can be updated while the system is running.
[0085] According to the optimization method of the logistics order allocation system in this application, by matching keywords in the keyword library of the logistics order allocation system with historical order address information in the address library, and setting keywords belonging to multiple sites for the matched historical order addresses as invalid keywords, the correctness of keywords can be automatically verified, thereby reducing the error rate of order allocation in the logistics order allocation system. Furthermore, this solution determines expanded keywords for invalid keywords by matching historical order addresses with the address library, and automatically writes the expanded keywords into the keyword library. This is equivalent to automatically updating the keyword library by expanding invalid keywords, thereby solving the problem of incorrect site allocation of logistics orders due to errors or delays in manual keyword maintenance. This not only improves the accuracy of order allocation in the logistics order allocation system but also increases logistics speed and reduces labor costs.
[0086] Based on the above embodiments, the implementation method for obtaining expanded keywords of invalid keywords will be described in detail below.
[0087] Figure 2 This is a flowchart illustrating the process of obtaining expanded keywords for invalid keywords in an embodiment of this application. For example... Figure 2 As shown, based on the above embodiments, the method for obtaining expanded keywords may include the following steps:
[0088] Step 201: Perform word segmentation on the i-th first historical order address to obtain M candidate keywords; where i is a positive integer less than or equal to N, and M is a positive integer.
[0089] In other words, for each first historical order address, word segmentation is performed on that address to obtain multiple candidate keywords, and then expanded keywords are determined from these candidate keywords. This application's embodiment uses the implementation method of obtaining expanded keywords for the i-th first historical order address as an example for illustration.
[0090] In some embodiments of this application, the word segmentation of the first historical order address can be performed according to the address text rules in the actual scenario. As an example, semantic word segmentation can be used to segment the first historical order address into multiple words, and the resulting words are superimposed to obtain M candidate keywords. For example, if the i-th first historical order address is "Building 201, No. 12, D Community, District C, A Province", semantic word segmentation will result in "A Province / B City / District C / D Community / Building 201 / 12". After filtering out the administrative region information from the segmented words and superimposing them, three candidate keywords are obtained: "D Community", "Building 12, D Community", and "Building 201, No. 12, D Community".
[0091] It should be noted that, in the embodiments of this application, the word segmentation algorithm used can be an existing word segmentation algorithm or a word segmentation algorithm developed by computer experts in the art according to actual scenarios. This application does not limit it in this regard.
[0092] Step 202: Match the j-th candidate keyword with the historical order address information in the address database to obtain the second historical order address that matches the j-th candidate keyword; where j is a positive integer less than or equal to M.
[0093] It is understandable that for the i-th first historical order address, the resulting M candidate keywords need to be verified separately to determine whether the candidate keywords can be used as expanded keywords for invalid keywords.
[0094] In this embodiment of the application, the j-th candidate keyword is used as an example for illustration. The j-th candidate keyword is matched with the historical order address information under the administrative region in the address database to obtain the second historical order address that matches the j-th candidate keyword. The number of second historical order addresses is a positive integer.
[0095] Step 203: Compare the site to which the second historical order address belongs with the site to which the i-th first historical order address belongs.
[0096] In some embodiments of this application, the method for comparing the site of the second historical order address with the site of the i-th first historical order address can be as follows: determine the site of each second historical order address and the site of the i-th first historical order address in the address database; compare the site of each second historical order address with the site of the i-th first historical order address to determine whether the site of each second historical order address is consistent with the site of the i-th first historical order address.
[0097] Step 204: In response to the fact that the site of the second historical order address is consistent with the site of the first historical order address, the j-th candidate keyword is used as an expanded keyword of the invalid keyword.
[0098] It is understandable that since the j-th candidate keyword is obtained by segmenting the i-th first historical order address, if the site to which the second historical order address matched with the j-th candidate keyword belongs is the same as the site to which the i-th first historical order address belongs, it means that when the j-th candidate keyword is used to match the order address, the matched orders will not be across sites. In other words, the j-th candidate keyword is used as an expanded keyword for invalid keywords.
[0099] In other words, for a certain invalid keyword, for each of the N first historical order addresses that match it, the expanded keywords of the invalid keyword are obtained through steps 201-204, and all the obtained expanded keywords are written into the keyword library as supplements to the invalid keyword.
[0100] According to the optimization method of the logistics order allocation system in this application embodiment, multiple candidate keywords are obtained by segmenting the first historical order address that matches the invalid keyword. Each candidate keyword is then matched with the historical order address information in the address database. The matching second historical order address and the first historical order address are then compared with their respective sites to determine whether cross-site situations will occur when using candidate keywords to match addresses. This allows for the exclusion of cross-site candidate keywords and the generation of expanded keywords for invalid keywords. This ensures the accuracy of the automatic order allocation of logistics orders by the candidate logistics order allocation system and also improves the efficiency of logistics order allocation.
[0101] To reduce the computational load of word segmentation and improve the efficiency of obtaining expanded keywords, this application proposes yet another embodiment.
[0102] Figure 3 This is a flowchart illustrating another method for obtaining expanded keywords from invalid keywords in an embodiment of this application. For example... Figure 3 As shown, based on the above embodiments, the method for obtaining expanded keywords may include the following steps:
[0103] Step 301: Delete the administrative region information and additional keywords in the i-th first historical order address.
[0104] It's understandable that the process of automatically allocating orders using keyword matching strategies is the order allocation process after logistics orders have been processed by administrative region. Therefore, in the process of allocating sites based on keywords, there's no need to use administrative region information as keywords. Thus, before processing the first historical order address for word segmentation, the administrative region information can be removed from the first historical order address. Furthermore, additional keywords are usually information related to express delivery added by the ordering user based on their own needs. If additional keywords also participate in word segmentation, it will interfere with candidate keywords and increase the computational load during word segmentation. Therefore, before processing the first historical order address for word segmentation, additional keywords can also be removed from the first historical order address.
[0105] In this embodiment, the deletion of administrative region information in the i-th first historical order address can be implemented by: using semantic recognition to identify the administrative region information in the i-th first historical order address; and deleting the identified administrative region information in the i-th first historical order address. The semantic recognition method can be using an existing semantic recognition model to identify the administrative region information, or it can be using a semantic recognition model constructed by those skilled in the art according to the actual scenario. Furthermore, other methods can also be used to identify the administrative region information in the first historical order address, and this application does not limit this approach.
[0106] To remove additional words, an additional word recognition model can be used to identify additional words in the first historical order address, and then the identified additional words can be deleted. The additional word recognition model can be trained on a dataset based on historical order address information and labeled additional words. In practice, other methods can be used to identify additional words in the first historical order address as needed; this application does not limit this approach.
[0107] Furthermore, this application does not limit the order in which administrative region information and additional terms are deleted. It may identify and delete the administrative region information and additional terms in the first historical order address separately, or it may delete them separately.
[0108] Step 302: Perform word segmentation on the i-th first historical order address after deletion to obtain M candidate keywords.
[0109] In other words, in this embodiment of the application, word segmentation is performed only on the first historical order address after deletion, which can reduce the computational load of word segmentation, reduce the number of invalid candidate keywords, and improve the efficiency of obtaining expanded keywords.
[0110] Step 303: Match the j-th candidate keyword with the historical order address information in the address database to obtain the second historical order address that matches the j-th candidate keyword; where j is a positive integer less than or equal to M.
[0111] Step 304: Compare the site to which the second historical order address belongs with the site to which the i-th first historical order address belongs.
[0112] Step 305: In response to the fact that the site of the second historical order address is consistent with the site of the first historical order address, the j-th candidate keyword is used as an expanded keyword of the invalid keyword.
[0113] It should be noted that, Figure 3 Steps 303 to 305 in the middle Figure 2The implementation methods for steps 202 to 204 are the same, and will not be repeated here.
[0114] According to the optimization method of the logistics order splitting system in this application embodiment, the administrative region information and additional words in the first historical order address are first deleted, and then the word segmentation is performed. This not only avoids the computational consumption of administrative region information and additional words during the word segmentation process, but also avoids the interference of administrative region information and additional words on the obtained candidate keywords, reducing unnecessary calculations. This can improve the efficiency of obtaining expanded keywords and reduce the time and computational consumption of the optimization process of this solution.
[0115] Based on the above embodiments, this application proposes yet another embodiment for writing extended keywords.
[0116] Figure 4 This is a flowchart of another optimization method for a logistics order splitting system proposed in an embodiment of this application.
[0117] like Figure 4 As shown, based on the above embodiments, the method may include the following steps:
[0118] Step 401: Obtain keywords from the keyword library of the logistics order splitting system.
[0119] Step 402: Match the keyword with the historical order address information in the address database to obtain N first historical order addresses that match the keyword; where N is a positive integer.
[0120] Step 403: In response to the fact that N first historical order addresses belong to multiple sites, the keywords are set as invalid keywords;
[0121] Step 404: Based on the N first historical order addresses and the address database, determine the expanded keywords for invalid keywords.
[0122] Step 405: Determine the coordinate information of the expanded keyword based on the coordinate information of the address that matches the expanded keyword in the address database.
[0123] It should be noted that each keyword in the keyword library corresponds to its own coordinates. When the logistics order splitting system matches keywords with order addresses during order splitting, it can use the coordinates of the keywords that match the order as the order coordinates to confirm the site to which the order belongs.
[0124] As an example, determining the coordinate information of each expanded keyword can be achieved by: obtaining the first address information containing coordinate information in the address database; matching the expanded keyword with the first address information to obtain the third historical order address that matches the expanded keyword; extracting the coordinate information of the third historical order address and averaging the extracted coordinate information to obtain the coordinate information of the expanded keyword.
[0125] As another example, a map coordinate query tool can be used to query the coordinate information corresponding to the expanded keyword. The implementation method can include: matching the expanded keyword with the historical order address information in the address database, and retrieving a preset number of fourth historical order addresses that match the expanded keyword; using the map coordinate query tool to query the coordinate information corresponding to the expanded keyword and the retrieved fourth historical order addresses respectively, and taking the coordinate information with the highest repetition frequency in the query results as the coordinate information of the expanded keyword; if there are multiple coordinate information with the same repetition frequency, the average result of these coordinate information with the same repetition frequency can be taken as the coordinate information of the expanded keyword.
[0126] Step 406: Write the expanded keywords and their coordinate information into the keyword database.
[0127] In some embodiments of this application, the obtained expanded keywords and their coordinate information can be written into the keyword library together. In actual implementation, expanded keywords obtained based on the same invalid keyword can be written into the keyword library together as needed, or expanded keywords of multiple invalid keywords can be written into the keyword library together. This application does not limit this.
[0128] Furthermore, since each keyword in the keyword database stores its administrative region information, when writing extended keywords, the administrative region information of invalid keywords can be written into the keyword database as the administrative region information of their extended keywords.
[0129] According to the optimization method of the logistics order allocation system in the embodiments of this application, for the writing operation of expanded keywords, the coordinate information of the expanded keywords is determined by the coordinate information of the address matching the expanded keywords in the address database, and the expanded keywords and their coordinate information are written together into the keyword database. On the one hand, this can ensure the accuracy of the expanded keyword coordinate information, and on the other hand, it can improve the accuracy of the logistics order allocation system in allocating stations according to the keyword database, thereby improving the logistics speed.
[0130] The following section describes the application of the optimization method for the logistics order allocation system in the above embodiments. After optimization, the logistics order allocation system can perform the following process: obtaining the logistics order address of the station to be allocated; matching the order address with valid keywords in the keyword library to obtain target keywords matching the order address, where valid keywords refer to the keywords remaining after filtering out invalid keywords from those with the same administrative region information as the order address, and these valid keywords include expanded keywords; obtaining the coordinate information of the target keyword and associating this coordinate information with the order; determining the target station to which the associated coordinate information belongs based on the business scope of each station, and allocating the order to the target station; and determining the target road area to which the order belongs based on the preset road area distribution of the target station and the coordinates associated with the order, and allocating the order to the target road area. After the above order allocation process, the courier in the corresponding road area then delivers the items corresponding to the order to their address, thereby improving the accuracy of automatic order allocation, significantly increasing logistics speed, and reducing labor costs.
[0131] To achieve the above embodiments, this application proposes an optimization device for a logistics order splitting system.
[0132] Figure 5 This application provides an optimization device for a logistics order splitting system. For example... Figure 5 As shown, the device includes:
[0133] The first acquisition module 510 is used to acquire keywords from the keyword library of the logistics order allocation system;
[0134] The second acquisition module 520 is used to match the keyword with the historical order address information in the address database to obtain N first historical order addresses that match the keyword; where N is a positive integer;
[0135] Module 530 is configured to set keywords as invalid keywords in response to N first historical order addresses belonging to multiple sites.
[0136] The determination module 540 is used to determine the expanded keywords of invalid keywords based on N first historical order addresses and the address database;
[0137] The writing module 550 is used to write expanded keywords into the keyword library.
[0138] In some embodiments of this application, the determining module 540 includes:
[0139] The first acquisition unit 541 is used to perform word segmentation on the i-th first historical order address to obtain M candidate keywords; where i is a positive integer less than or equal to N, and M is a positive integer;
[0140] The second acquisition unit 542 is used to match the j-th candidate keyword with the historical order address information in the address database to obtain the second historical order address that matches the j-th candidate keyword; where j is a positive integer less than or equal to M;
[0141] The comparison unit 543 is used to compare the site to which the second historical order address belongs with the site to which the i-th first historical order address belongs.
[0142] The determining unit 544 is used to determine the j-th candidate keyword as an expanded keyword for invalid keywords in response to the fact that the home site of the second historical order address is consistent with the home site of the i-th first historical order address.
[0143] Specifically, the first acquisition unit 541 is used for:
[0144] The administrative region information and additional keywords in the i-th first historical order address are deleted;
[0145] The i-th historical order address after deletion is segmented to obtain M candidate keywords.
[0146] In some embodiments of this application, the writing module 550 includes:
[0147] The determining unit 551 is used to determine the coordinate information of the extended keyword based on the coordinate information of the address that matches the extended keyword in the address database;
[0148] The writing unit 552 is used to write the expanded keyword and its coordinate information into the keyword library.
[0149] Furthermore, the determining unit 551 is specifically used for:
[0150] Retrieve the first address information containing coordinate information from the address database;
[0151] The expanded keywords are matched with the first address information to obtain the third historical order address that matches the expanded keywords;
[0152] Extract the coordinate information of the third historical order address, and calculate the average of the extracted coordinate information to obtain the coordinate information of the expanded keyword.
[0153] The optimization device for the logistics order allocation system according to the embodiments of this application automatically verifies the correctness of keywords by matching keywords in the keyword library of the logistics order allocation system with historical order address information in the address library, and setting keywords belonging to multiple sites for the matched historical order addresses as invalid keywords. This reduces the error rate of order allocation in the logistics order allocation system. Furthermore, this solution determines expanded keywords for invalid keywords by matching historical order addresses with the address library, and automatically writes the expanded keywords into the keyword library. This is equivalent to automatically updating the keyword library by expanding invalid keywords, thereby solving the problem of incorrect site allocation of logistics orders caused by errors or delays in manual keyword maintenance. This not only improves the accuracy of order allocation in the logistics order allocation system but also increases logistics speed and reduces labor costs.
[0154] Based on embodiments of this application, this application also provides an electronic device, at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to execute any of the aforementioned optimization methods for a logistics order splitting system.
[0155] Based on embodiments of this application, this application also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute an optimization method for a logistics order splitting system according to any of the foregoing embodiments of this application.
[0156] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of this application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the application described and / or claimed herein.
[0157] like Figure 6As shown, device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 602 or a computer program loaded from storage unit 608 into random access memory (RAM) 603. RAM 603 may also store various programs and data required for the operation of device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.
[0158] Multiple components in device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of monitors, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.
[0159] The computing unit 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as the optimization method for a logistics order allocation system. For example, in some embodiments, the optimization method for a logistics order allocation system can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the optimization method for a logistics order allocation system described above can be performed. Alternatively, in other embodiments, the computing unit 601 can be configured to perform the optimization method for a logistics order allocation system by any other suitable means (e.g., by means of firmware).
[0160] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.
[0161] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.
[0162] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.
[0163] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).
[0164] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), the Internet, and blockchain networks.
[0165] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the management difficulties and weak business scalability inherent in traditional physical hosts and VPS (Virtual Private Server) services. Servers can also be servers for distributed systems or servers integrated with blockchain technology.
[0166] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application can be achieved, and this is not limited herein.
[0167] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.
Claims
1. An optimization method of a logistics order processing system, characterized by, include: Retrieve keywords from the keyword library of the logistics order allocation system; The keyword is matched with historical order address information in the address database to obtain N first historical order addresses that match the keyword; where N is a positive integer. Since the N first historical order addresses belong to multiple sites, the keyword is set as an invalid keyword; Based on the N first historical order addresses and the address database, determine the expanded keywords for the invalid keywords; Write the expanded keywords into the keyword library; The step of determining the expanded keywords for the invalid keywords based on the N first historical order addresses and the address database includes: The first historical order address of the i-th order is segmented to obtain M candidate keywords; where i is a positive integer less than or equal to N, and M is a positive integer; The j-th candidate keyword is matched with the historical order address information in the address database to obtain the second historical order address that matches the j-th candidate keyword; where j is a positive integer less than or equal to M; The site to which the second historical order address belongs is compared with the site to which the i-th first historical order address belongs; Since the originating site of the second historical order address is consistent with the originating site of the i-th first historical order address, the j-th candidate keyword is used as the expanded keyword of the invalid keyword.
2. The method of claim 1, wherein, The step of segmenting the i-th first historical order address to obtain M candidate keywords includes: The administrative region information and additional keywords in the i-th first historical order address are deleted; The i-th first historical order address after deletion is segmented to obtain M candidate keywords.
3. The method of claim 1, wherein, The step of writing the expanded keywords into the keyword library includes: The coordinate information of the expanded keyword is determined based on the coordinate information of the address that matches the expanded keyword in the address database; The expanded keyword and its coordinate information are written into the keyword database.
4. The method of claim 3, wherein, Determining the coordinate information of the expanded keyword based on the coordinate information of the addresses matching the expanded keyword in the address database includes: Obtain the first address information containing coordinate information from the address database; The expanded keyword is matched with the first address information to obtain the third historical order address that matches the expanded keyword; The coordinate information of the third historical order address is extracted, and the average of the extracted coordinate information is calculated to obtain the coordinate information of the expanded keyword.
5. An optimization device of a logistics order processing system, characterized by comprising: include: The first acquisition module is used to acquire keywords from the keyword library of the logistics order allocation system; The second acquisition module is used to match the keyword with historical order address information in the address database to obtain N first historical order addresses that match the keyword; wherein, N is a positive integer; The setting module is used to set the keyword as an invalid keyword in response to the fact that the N first historical order addresses belong to multiple sites; The determination module is used to determine the expanded keywords of the invalid keywords based on the N first historical order addresses and the address database; The writing module is used to write the expanded keywords into the keyword library; The determining module includes: The first acquisition unit is used to perform word segmentation on the i-th first historical order address to obtain M candidate keywords; wherein i is a positive integer less than or equal to N, and M is a positive integer; The second acquisition unit is used to match the j-th candidate keyword with the historical order address information in the address database to obtain the second historical order address that matches the j-th candidate keyword; wherein, j is a positive integer less than or equal to M; The comparison unit is used to compare the site to which the second historical order address belongs with the site to which the i-th first historical order address belongs. The determining unit is configured to, in response to the fact that the attribution site of the second historical order address is consistent with the attribution site of the i-th first historical order address, use the j-th candidate keyword as the expanded keyword of the invalid keyword.
6. The apparatus of claim 5, wherein, The first acquisition unit is specifically used for: The administrative region information and additional keywords in the i-th first historical order address are deleted; The i-th first historical order address after deletion is segmented to obtain M candidate keywords.
7. The apparatus of claim 5, wherein, The writing module includes: The determining unit is used to determine the coordinate information of the expanded keyword based on the coordinate information of the address that matches the expanded keyword in the address database; The writing unit is used to write the expanded keyword and its coordinate information into the keyword library.
8. The apparatus of claim 7, wherein, The determining unit is specifically used for: Obtain the first address information containing coordinate information from the address database; The expanded keyword is matched with the first address information to obtain the third historical order address that matches the expanded keyword; The coordinate information of the third historical order address is extracted, and the average of the extracted coordinate information is calculated to obtain the coordinate information of the expanded keyword.
9. An electronic device, comprising: include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 4.
10. A non-transitory computer-readable storage medium having stored thereon computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 4.