Cross-border logistics state query method and device based on multi-source data, computer equipment and storage medium

Abstract

The invention provides a cross-border logistics state query method based on multi-source data, and the method comprises the steps: obtaining a query identifier, a target shipman and a target harbor district, thereby precisely positioning a logistics service and a data source. And then respectively calling queries corresponding to the target shipman and the target harbor district to obtain the first logistics information and the second logistics information. And determining to-be-optimized logistics information according to the current transportation node, selecting a target data source by means of the first mapping relationship, and calling a querier of the target data source, so as to optimize to-be-optimized sub-logistics information. And finally, traversing a transportation node link, and fusing the first logistics information and the second logistics information according to a priority access relation to obtain third logistics information. According to the scheme, manual one-by-one query can be replaced by system automatic query, query time consumption is greatly reduced, data errors caused by manual operation are effectively avoided, all-day high-frequency data updating can be achieved, nodes can be intelligently judged, accurate source compensation data can be intelligently selected, and enterprise supply chain management optimization is assisted.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly to a cross-border logistics status query method, device, computer device, and storage medium based on multi-source data. Background Art

[0002] Currently, if an operator of a freight forwarder / cargo owner wants to know the status of the entire cross-border logistics link, they need to take the booking number / bill of lading number / container number to the public platforms of each data source and query one by one according to the website rules. After obtaining the results, classify and fill in the records of transportation nodes according to the industry experience according to the transportation segments where different data sources are located, and at the same time record other information such as the port of departure, port of destination, vessel name, voyage number, ETD, ETA, etc. Finally, complete data warehousing or data visualization. However, in current international trade, the sea freight link is long, the transportation time is highly uncertain, there are many involved links and nodes that need to be concerned about, the data sources are numerous and complex, it is difficult to track the location of goods, and many current system nodes are updated manually slowly and have a high error rate. Summary of the Invention

[0003] The purpose of this application aims to solve at least one of the above technical defects, and particularly provides a solution that can efficiently implement cross-border logistics status query based on multi-source data.

[0004] In a first aspect, a cross-border logistics status query method based on multi-source data includes:

[0005] Obtain a query identifier, a target shipping company, and a target port area;

[0006] Respectively call the queryers corresponding to the target shipping company and the target port area according to the query identifier to obtain first logistics information and second logistics information; the first logistics information and the second logistics information include various set types of sub-logistics information;

[0007] Respectively perform data optimization on the first logistics information and the second logistics information. The data optimization includes: determining the current transportation node according to the logistics information to be optimized, selecting the corresponding first mapping relationship according to the current transportation node, and using the first mapping relationship to determine the sub-logistics information to be optimized and its corresponding target data source from various set types of sub-logistics information, respectively calling the queryers corresponding to each target data source according to the query identifier, and replacing the obtained information with the corresponding sub-logistics information to be optimized; the target data source includes data sources other than the port area and the shipping company;

[0008] Fuse the first logistics information and the second logistics information to obtain the third logistics information. The data fusion includes: traversing each transportation node on the transportation node link. For the traversed transportation node, select one of the first logistics information and the second logistics information as the extraction source for each target field corresponding to the transportation node according to the priority access relationship to perform data extraction, so as to obtain the third logistics information including all transportation nodes.

[0009] In one embodiment, determining the current transportation node according to the logistics information to be optimized includes:

[0010] Retrieve the preset identification string existing in the logistics information to be optimized;

[0011] Determine the current transportation node according to the preset identification string and the second mapping relationship.

[0012] In one embodiment, before fusing the first logistics information and the second logistics information, it further includes:

[0013] Perform data cleaning on the first logistics information and the second logistics information respectively. The data cleaning includes: mapping the non-standard fields in the logistics information to be cleaned to standard fields according to the field mapping rules corresponding to the query tool for obtaining the logistics information to be cleaned.

[0014] In one embodiment, for the cross-border logistics status query method based on multi-source data, the data cleaning further includes:

[0015] After mapping the non-standard fields in the logistics information to be cleaned to standard fields, judge whether there are missing set types in the sub-logistics information included in the logistics information to be cleaned according to the set type list;

[0016] If so, determine the missing set type as the type to be compensated;

[0017] For the logistics information to be cleaned belonging to the first logistics information, select the third mapping relationship corresponding to the target shipping company to select the corresponding target type for the type to be compensated;

[0018] For the logistics information to be cleaned belonging to the second logistics information, select the third mapping relationship corresponding to the target port area to select the corresponding target type for the type to be compensated;

[0019] Generate the sub-logistics information corresponding to the target type, and fill it into the logistics information to be cleaned.

[0020] In one embodiment, before fusing the first logistics information and the second logistics information, it further includes:

[0021] If the first logistics information has completed data optimization and the second logistics information has not completed data optimization, then the data of the target field corresponding to each transport node on the transport node link is displayed according to the first logistics information;

[0022] If the second logistics information has completed data optimization and the first logistics information has not completed data optimization, the data of the target field corresponding to each transport node on the transport node link is displayed according to the second logistics information.

[0023] In one embodiment, the cross-border logistics status query method based on multi-source data further includes:

[0024] After the data fusion is completed, the data displayed in the corresponding target field of each transport node on the transport node link is updated according to the third logistics information.

[0025] In one embodiment, the cross-border logistics status query method based on multi-source data further includes:

[0026] Determine the quantity of the first box according to the first logistics information, and determine the quantity of the second box according to the second logistics information;

[0027] If the second box quantity is less than the first box quantity, extract the booking number from the first logistics information;

[0028] Update the second logistics information according to the query corresponding to the destination port area of ​​the booking number.

[0029] In a second aspect, the present application provides a form highlighting device based on a large model, comprising:

[0030] An acquisition module is used to acquire a query identifier, a target ship company and a target port area;

[0031] A query module, used to call the query devices corresponding to the target shipping company and the target port area respectively according to the query identifier to obtain the first logistics information and the second logistics information; the first logistics information and the second logistics information include sub-logistics information of multiple set types;

[0032] The optimization module is used to perform data optimization on the first logistics information and the second logistics information respectively, and the data optimization includes: determining the current transportation node according to the logistics information to be optimized, selecting the corresponding first mapping relationship according to the current transportation node, and using the first mapping relationship to determine the sub-logistics information to be optimized and its corresponding target data source from a plurality of set types of sub-logistics information, respectively calling the query device corresponding to each target data source according to the query identifier, and replacing the corresponding sub-logistics information to be optimized with the obtained information; the target data source includes a data source other than the port area and the shipping company;

[0033] A fusion module is used to perform data fusion on the first logistics information and the second logistics information to obtain the third logistics information. The data fusion includes: traversing each transportation node on the transportation node link, and for the traversed transportation node, selecting one of the first logistics information and the second logistics information as the extraction source for each target field corresponding to the transportation node according to the preferential access relationship to perform data extraction, so as to obtain the third logistics information including all transportation nodes.

[0034] In a third aspect, the present application provides a computer device, including one or more processors and a memory. Computer-readable instructions are stored in the memory. When the computer-readable instructions are executed by one or more processors, the steps of the cross-border logistics status query method based on multi-source data in any of the above embodiments are executed.

[0035] In a fourth aspect, the present application provides a storage medium in which computer-readable instructions are stored. When the computer-readable instructions are executed by one or more processors, one or more processors are caused to execute the steps of the cross-border logistics status query method based on multi-source data in any of the above embodiments.

[0036] From the above technical solutions, it can be seen that the embodiments of the present application have the following advantages:

[0037] In the cross-border logistics status query solution based on multi-source data, first, a query identifier, a target shipping company, and a target port area are obtained to accurately locate the logistics business and data sources. Then, the queryers corresponding to the target shipping company and the target port area are respectively called to obtain the first logistics information and the second logistics information. Next, the logistics information to be optimized is determined according to the current transportation node, and the target data source is selected with the help of the first mapping relationship and its queryer is called to optimize the sub-logistics information to be optimized. Finally, the transportation node link is traversed, and the first and second logistics information are fused according to the preferential access relationship to obtain the third logistics information. This solution can replace manual individual queries through system automation queries, greatly reducing the query time-consuming, improving the management efficiency of operators, and effectively avoiding data errors caused by human operations. This solution can also achieve high-frequency data updates throughout the day, and intelligently determine nodes and select accurate sources to compensate for data, providing a basis for subsequent data analysis and helping to optimize the enterprise supply chain management. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0039] Figure 1Schematic flowchart of a cross-border logistics status query method based on multi-source data provided by an embodiment of the present application;

[0040] Figure 2 Schematic flowchart of data cleaning in an embodiment of the present application;

[0041] Figure 3 Schematic flowchart of the box compensation query function in an embodiment of the present application;

[0042] Figure 4 Internal structure diagram of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0043] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0044] The entire cross-border logistics link mainly refers to the entire logistics process based on sea container transportation, which mainly includes three transportation segments, namely the origin transportation segment, the sea transportation segment, and the destination transportation segment. Each transportation segment includes more than one transportation node. For example, the origin transportation segment includes picking up empty containers at the container yard, loading goods, and entering the port area through transportation methods such as trucks / railways / barges, starting processes such as entering the port, customs release, and leaving the port to complete the shipment of goods. Querying the data of these nodes requires operators to manually query from data sources such as container yards, truck / railway / barge companies, origin port areas, and origin customs. This approach is time-consuming and laborious, and the definitions of data fields are different for different data source websites. Novice operators or those lacking industry experience are easily confused about the data, resulting in incorrect output results and affecting the business. After obtaining the results, it is necessary to classify and fill in the transportation nodes according to the transportation segments where different data sources are located based on industry experience, and only copy and paste. Querying a single transportation order takes several minutes, with low efficiency. Manual copying is also prone to incorrect pasting of data dimensions, especially when the time nodes are incorrect, which has a greater impact on the business. It is also difficult to obtain the latest status of transportation orders 7x24 hours continuously through manual querying, resulting in an inability to accurately control the time changes of each node, especially abnormal nodes (unable to load the ship, container deviation, customs interception), and it is impossible to give early warnings.

[0045] To solve the above problems, the present application provides a cross-border logistics status query method based on multi-source data. Please refer to Figure 1 , which includes steps S102 to S108.

[0046] S102. Obtain a query identifier, a target shipping company, and a target port area.

[0047] It can be understood that the query identifier is the key information used to determine cross-border logistics operations. Common ones include booking numbers, bill of lading numbers, or container numbers, etc. It is the indexing basis for the entire query process. The target shipping company is the shipping company designated by the user to be responsible for transporting goods. Different shipping companies have differences in data management, interface specifications, and business processes. The target port area is the port area involved in the import and export process of goods. The port area undertakes important functions such as cargo loading and unloading, storage, and transfer.

[0048] Specifically, a dedicated query input box can be set on the system interface, requiring the user to accurately enter query identifiers such as booking numbers / bill of lading numbers / container numbers in the specified format, and select the target shipping company and target port area by means of a drop-down menu or manual input. After the system background receives this information, it first performs data format verification to ensure the accuracy and integrity of the input information. For example, check whether the query identifier conforms to the corresponding coding rules, and whether the target shipping company and target port area are within the range of the pre-stored list in the system. After passing the verification, these information are temporarily stored and marked to prepare for the next step of calling the query tool. At the same time, the system will record metadata such as the initiation time of this query and user information for subsequent query record management and data analysis. It can also be that the user configures the query task in advance, sets the query identifier, target shipping company, and target port area in the query task, and the computer system automatically triggers according to the configured query task. Parameters such as the triggering frequency and interval can also be set in advance. In this way, round-the-clock uninterrupted query and data update can be achieved.

[0049] S104. Respectively call the query tools corresponding to the target shipping company and the target port area according to the query identifier to obtain the first logistics information and the second logistics information. The first logistics information and the second logistics information include various types of sub-logistics information.

[0050] It is understandable that a query tool is a software module or program interface specifically designed to interact with data sources such as specific shipping companies or port areas to obtain logistics data. A corresponding query tool is designed for each data source that may be a query object. The first logistics information is the relevant data at the shipping company level regarding this logistics operation obtained through the target shipping company query tool. The first logistics information includes various types of sub-logistics information, such as basic bill of lading information (including shipper, consignee, cargo description, etc.), voyage information (such as departure port, transit port, destination port, estimated departure time, estimated arrival time, etc.), basic container information (container number, container type, container quantity, etc.), and container dynamic information (status changes of the container at each transportation node, such as having entered the yard, having been loaded onto the ship, etc.). The second logistics information is the logistics data obtained by the target port area query tool, and the second logistics information also includes various types of sub-logistics information, such as basic bill of lading / booking information, basic container information, container dynamic information, customs information (cargo declaration status, whether inspected, etc.), truck information (truck license plate number, transportation track, etc. for the inland transportation link), and shipping schedule information (ship berthing plan and departure time within the port area, etc.). The types included in the first logistics information and the second logistics information can be the same or different, and can be specifically set according to user needs. Each type of sub-physical information contains multiple fields of data (such as the content exemplified in the parentheses above).

[0051] In this step, corresponding query tools are designed based on the respective data management systems and external interface specifications of the shipping company and the port area. Different query tools can communicate with the corresponding data sources according to a predetermined protocol and data request format. When calling a query tool, the system passes the query identifier as a key parameter to the query tool, and the query tool performs data retrieval and extraction in the database of the shipping company or the port area based on this parameter. The shipping company and the port area are two of the most important areas in cross-border logistics, and the cross-border logistics information they can provide is the most complete and perfect. Based on the first logistics information and the second logistics information queried from the port area and the shipping company, a complete cross-border logistics information portrait can be jointly constructed.

[0052] Specifically, according to the target shipping company and target port area information obtained in S102, the corresponding query program is matched in the internal query configurator library. For example, if the target shipping company is "Shipping Company A", the system will call the query interface developed specifically for Shipping Company A. After receiving the query identifier, the query program sends a data request to the database server of the shipping company in accordance with the data request format specified by the shipping company, such as through a specific EDI message format or API call method. The server retrieves data based on the query identifier in the request and returns the matched data to the query program in a predetermined response format. The query program then organizes this data into the first logistics information and transmits it back to the system. The process of calling the query program for the target port area is similar. For example, for "Port B", the query program for Port B is called. This query program obtains relevant data from the logistics information platform within the port area, including the customs system, port operation management system, and truck scheduling system, and organizes it into the second logistics information and feeds it back to the system. It is worth noting that the calls to the query programs for the target port area and the target shipping company are not necessarily synchronous, and the speeds at which the query programs return results may also vary. Finally, the first logistics information and the second logistics information are obtained.

[0053] S106, perform data optimization on the first logistics information and the second logistics information respectively. Data optimization includes: determining the current transportation node according to the logistics information to be optimized, selecting the corresponding first mapping relationship according to the current transportation node, and using the first mapping relationship to determine the sub-logistics information to be optimized and its corresponding target data source from various preset types of sub-logistics information, calling the query programs corresponding to each target data source according to the query identifier, and replacing the corresponding sub-logistics information to be optimized with the obtained information. The target data sources include data sources other than port areas and shipping companies.

[0054] It can be understood that both the first logistics information and the second logistics information need to be optimized. The first logistics information and the second logistics information for which data optimization begins are referred to as the logistics information to be optimized. Whether the data provided by the port area or the shipping company is comprehensive, in different stages of the cross-border logistics transportation link, some data of the port area and the shipping company are data obtained from other data sources and then processed, and there may be problems such as failure to update in a timely manner, or the data being insufficiently detailed and inaccurate, and the data quality needs to be improved. Here, data optimization refers to optimizing the inaccurate sub-logistics information in the first logistics information and the second logistics information to improve the data quality. The optimization measure is to directly query from the most accurate data source during the query and then supplement it to the logistics information to be supplemented.

[0055] Specifically, what is ultimately presented to the user in cross-border logistics information query is the specific situation at each transportation node in the cross-border logistics transportation link. The current transportation node refers to the actual location or stage where the goods are in the cross-border logistics transportation link, such as picking up an empty container, entering the port, sea release, loading the ship, etc. The current transportation node is determined by information related to the node status such as the timestamp and node status identifier in the data. For example, if the container movement information in the first logistics information shows "has entered the yard", then the current transportation node is determined to be "entering the port". Each transportation node is configured with a corresponding first mapping relationship. The first mapping relationship is a pre-established data association rule library, which defines, according to different transportation nodes, which set types of sub-logistics information need to be optimized at the corresponding transportation node and which data source should be used as the target data source to obtain data when optimizing. Additionally, the target data source here is a data source other than the shipping company for the first logistics information and a data source other than the port area for the second logistics information. Each target data source is also designed with a corresponding query tool. Taking the current transportation node as the stage of picking up an empty container as an example, the yard is the first-hand data source for the picking-up situation, and the corresponding query tool of the yard management system can be called according to the query statement to update the container movement information based on the information retrieved.

[0056] S108, perform data fusion on the first logistics information and the second logistics information to obtain the third logistics information. The data fusion includes: traversing each transportation node on the transportation node link, and for the traversed transportation node, selecting one of the first logistics information and the second logistics information as the extraction source for each target field corresponding to the transportation node according to the priority access relationship to perform data extraction, so as to obtain the third logistics information including all transportation nodes.

[0057] It can be understood that the transportation node link is an orderly arrangement of a series of key nodes in the cross-border logistics process, including picking up an empty container, entering the port, sea release, stacking, loading the ship, sailing, arriving at the port, unloading, picking up a loaded container, returning an empty container, etc. The priority access relationship is a pre-set data selection rule, which stipulates that for specific target fields (such as the time of entering the port, sea release status, etc.) at different transportation nodes, data should be preferentially obtained from which logistics information (the first logistics information or the second logistics information). When the field is missing in the preferentially accessed information, it is obtained from the other logistics information. The third logistics information is a complete and unified cross-border logistics information set obtained after data fusion, covering the key information of all transportation nodes and being able to comprehensively reflect the logistics status of the goods.

[0058] The purpose of data fusion is to integrate the advantages of the first logistics information and the second logistics information, and construct a complete, accurate and unified-standard logistics information view. Since shipping companies and port areas have different data advantages at different transportation nodes, for example, the data updates at port areas are more timely and accurate at nodes such as port entry and release at sea, while shipping companies may have more advantages in aspects such as voyage information and information related to picking up empty containers. By traversing the transportation node link and according to the priority access relationship, it is possible to ensure that the best data source is obtained at each node, so as to realize the optimized integration of logistics information and improve the availability and reliability of data.

[0059] The system starts data fusion sequentially from the empty container picking-up node according to the pre-set order of the transportation node link. For the empty container picking-up node, according to the priority access relationship, if it is stipulated to obtain the empty container picking-up time from the first logistics information (shipping company information) preferentially, but this field is missing in the shipping company information, then search for and extract it from the second logistics information (port area information). When traversing to the port entry node, first check the port entry time, port entry terminal and other information in the second logistics information. If these information are complete, directly extract them into the third logistics information; if the port entry time is missing in the second logistics information, search and supplement it from the first logistics information. For example, at the loading node, if the port area information shows that the ship has berthed but the loading start time is not recorded, and there is a loading plan time in the shipping company information and it is judged that this plan time is relatively accurate according to the on-site operation situation, then the loading plan time in the shipping company information is extracted as the loading time at the loading node into the third logistics information. And so on, after traversing all transportation nodes, the data extracted from each node are integrated together to form the third logistics information. For example, in the process of fusing the logistics information of a consignment of goods, at the arrival port node, preferentially use the actual arrival time of the ship and the terminal berth information in the second logistics information, and at the same time supplement relevant information such as the contact information of the destination port agent in the first logistics information, and finally form a complete third logistics information, which can comprehensively and accurately reflect the status of each link of the goods in the cross-border logistics process and provide a reliable decision-making basis for relevant parties such as freight forwarders and shippers.

[0060] The cross-border logistics status query solution based on multi-source data first obtains a query identifier, a target shipping company, and a target port area to accurately locate the logistics business and data sources. Then, it separately calls the queryers corresponding to the target shipping company and the target port area to obtain the first logistics information and the second logistics information. Next, it determines the logistics information to be optimized based on the current transportation node, selects the target data source according to the first mapping relationship, and calls its queryer to optimize the sub-logistics information to be optimized. Finally, it traverses the transportation node link, and fuses the first and second logistics information according to the priority access relationship to obtain the third logistics information. This solution can replace manual individual queries through system automation queries, greatly reducing the query time-consuming and improving the management efficiency of operators. It also effectively avoids data errors caused by human operations. This solution can also achieve high-frequency data updates throughout the day, and intelligently determine nodes and select accurate sources to compensate for data, providing a basis for subsequent data analysis and helping to optimize the enterprise's supply chain management.

[0061] In one embodiment, determining the current transportation node according to the logistics information to be optimized includes: retrieving a preset identification string existing in the logistics information to be optimized. Determining the current transportation node according to the preset identification string and the second mapping relationship.

[0062] It can be understood that the logistics information to be optimized is the data part determined to need further processing to improve data quality or integrity in the previously obtained first logistics information or second logistics information. The preset identification string is a specific character combination or code preset in the logistics data. These strings have specific meanings and uses and can serve as the key basis for judging transportation nodes. The second mapping relationship is a pre-constructed data association rule system that establishes the corresponding relationship between the preset identification string and the specific transportation node and is the core reference basis for determining the current transportation node.

[0063] In cross-border logistics data processing, due to the diverse data sources and formats of shipping companies and ports, determining the transportation nodes is crucial for subsequent data optimization and integration. With the change of the transportation stage, specific strings will appear in the first logistics information and the second logistics information. These strings are selected as preset identification strings and a second mapping relationship is established between them and the transportation nodes. By retrieving the preset identification strings in the logistics information to be optimized, the information characteristics carried by these strings are used to determine the transportation nodes according to the second mapping relationship. This is based on the standardized and structured design concept of logistics data, that is, to mark the key nodes in the logistics process with specific identification, so as to accurately identify the transportation stage of the goods in a complex data environment. For example, when recording and transmitting logistics data, shipping companies or ports embed these identification strings in the data field according to industry practices or internal specifications, and the system can parse and judge based on this. For example, in the dynamic information of the box, character combinations such as "Entered Port" with clear actions and location references are preset identification strings. When the string is found, it can be determined that the port entry node has been reached.

[0064] In one of the embodiments, before the first logistics information and the second logistics information are data-fused, it also includes: performing data cleansing on the first logistics information and the second logistics information respectively, and the data cleaning includes: mapping non-standard fields in the logistics information to be cleaned into standard fields according to the field mapping rules corresponding to the query device that obtains the logistics information to be cleaned.

[0065] It can be understood that the logistics information to be cleaned refers to the data content in the first logistics information and the second logistics information obtained from the target shipping company and the target port area that needs to be processed to conform to the unified standard specifications. The field mapping rules corresponding to the query tool are a set of pre-set rule systems. They are formulated based on the characteristics of the data provided by different shipping companies and port areas and the requirements of the entire cross-border logistics field for the standard data format, and clearly stipulate how to convert non-standard fields from various sources into standard fields to ensure the consistency and standardization of data. For example, for the information of the port of departure, some shipping companies may use the expression "departure port", while others may use "loading port", and the standard field is uniformly stipulated as "pol". The field mapping rules are the basis for handling the conversion of such different expressions into the standard expression. Due to different shipping companies and port areas having their own independent data management systems and data recording habits, when outputting logistics information, even if describing the same type of logistics attribute, there are often differences in the field names, formats, etc. In order to accurately and effectively perform data fusion on the first logistics information and the second logistics information in the subsequent process and construct a complete and standardized cross-border logistics status view, it is necessary to perform data cleaning operations and convert non-standard fields into standard fields according to the corresponding field mapping rules.

[0066] In one of the embodiments, for the cross-border logistics status query method based on multi-source data, please refer to Figure 2 , and the data cleaning further includes steps S202 to S210.

[0067] S202, after mapping the non-standard fields in the logistics information to be cleaned to standard fields, according to the set type list, determine whether there are missing set types in the sub-logistics information included in the logistics information to be cleaned.

[0068] It can be understood that the set type list is a list pre-formulated in the field of cross-border logistics data management that covers all the sub-logistics information types corresponding to all links of the complete cross-border logistics business. It clearly lists various sub-logistics information categories that should exist, such as basic bill of lading information, voyage information, basic container information, customs information, truck information, shipping schedule information, etc. It is an important reference basis for measuring and judging the integrity of the obtained logistics information. The sub-logistics information included in the logistics information to be cleaned is the specific category data actually existing in the logistics information obtained from the shipping company or port area after the mapping processing of non-standard fields to standard fields. After completing the mapping from non-standard fields to standard fields to ensure the standardization and unity of the data format, it is necessary to further consider the integrity of the data. By comparing with the standard framework of the set type list, the logistics information to be cleaned after cleaning is sorted out and analyzed to determine whether the sub-logistics information it covers includes all the key information types that should exist in the whole process of cross-border logistics.

[0069] S204. If so, determine the missing setting type as the type to be compensated.

[0070] It can be understood that the type to be compensated is the type of sub-logistics information that is determined to be missing in the logistics information to be cleaned after the previous steps and is specified in the setting type list. It clearly points out the deficiencies in the integrity of the current logistics information and is the specific object for subsequent data supplementation and improvement operations. For example, if the leg information is missing, then the information type of the leg information becomes the type to be compensated.

[0071] S206. For the logistics information to be cleaned that belongs to the first logistics information, select the third mapping relationship corresponding to the target shipping company and select the corresponding target type for the type to be compensated.

[0072] It can be understood that the third mapping relationship corresponding to the target shipping company is a data association rule system established specifically for a specific shipping company. It stipulates how, in the case of the type to be compensated (i.e., the missing type of logistics information), according to the data characteristics, business logic of the shipping company itself, and the association with other data sources, the type to be compensated is mapped to the target type that can obtain supplementary data. The target type is the type of sub-logistics information that is determined through the third mapping relationship and corresponds to the type to be compensated and can provide supplementary data. For example, if the type to be compensated is the transit port in the leg information, the target type is determined through the third mapping relationship as the information type where the transit port-related data obtained by the shipping company from interacting with a certain third-party logistics data platform is located.

[0073] The types of sub-logistics information that can be directly queried by each shipping company during query are not the same, and some types of sub-logistics information listed in the setting type list may be missing. However, the data provided by each shipping company is comprehensive enough. Although the sub-logistics information of the missing types cannot be directly queried, it can be extracted from other more detailed sub-logistics information. For example, in the first logistics information, there is no leg information, only the basic container information and container movement information. The dynamic text description in the container movement information can find information related to the leg, such as the estimated arrival time, actual arrival time, ship name and voyage number, etc. The leg information can be compensated based on the container movement information. Therefore, in the third mapping relationship, an association can be established between the leg information and the container movement information, and the container movement information can be used as the target type corresponding to the leg information.

[0074] S208. For the logistics information to be cleaned that belongs to the second logistics information, select the third mapping relationship corresponding to the target port area and select the corresponding target type for the type to be compensated.

[0075] It can be understood that the third mapping relationship corresponding to the target port area is similar to the third mapping relationship corresponding to the target shipping company. However, it is a rule system constructed based on factors such as the data composition of the port area itself, business processes, and cooperation relationships with surrounding relevant data sources. When the second logistics information appears in the type to be compensated, it is used to map it to the target type that can obtain supplementary data according to the characteristics of the port area. The target type here is also a specific sub-logistics information type that can provide missing data determined based on this mapping relationship, but it focuses on the data scope related to the port area. For example, if the type to be compensated is the cargo inspection result in the customs information, through the third mapping relationship corresponding to the target port area, the target type may be determined as the information type where the data related to the inspection result obtained by the port area's docking with the customs electronic port system is located.

[0076] The types of sub-logistics information that can be directly queried for each port area during query are not the same, and some types of sub-logistics information listed in the set type list may be missing. However, the data provided by each port area is comprehensive enough. Although the sub-logistics information of the missing types cannot be directly queried, it can be extracted from other more detailed sub-logistics information. For example, if there is no truck information in the second logistics information, the dynamic text description in the container movement information can find information related to truck information such as the empty pick-up time and truck license plate, and the truck information can be compensated based on the container movement information. Therefore, in the third mapping relationship, the truck information can be associated with the container movement information, and the container movement information can be used as the target type corresponding to the truck information.

[0077] S210. Generate the sub-logistics information of the corresponding type to be compensated according to the sub-logistics information of the target type, and fill it into the logistics information to be cleaned.

[0078] It can be understood that after determining the sub-logistics information of the target type, since its data format, content presentation, etc. may not fully meet the requirements of the logistics information to be cleaned where the type to be compensated is located, corresponding data processing and conversion are required to generate the sub-logistics information of the type to be compensated that meets the requirements, and then fill it in to ensure that the supplementary data can seamlessly integrate into the original logistics information system, so that the entire logistics information to be cleaned meets the standards in terms of integrity and standardization, accurately reflects the actual state of cargo transportation, and provides a complete and reliable data basis for subsequent logistics business operations and data analysis.

[0079] In one embodiment, before fusing the first logistics information and the second logistics information, it further includes: if the first logistics information has completed data optimization and the second logistics information has not completed data optimization, then display the data of the target fields corresponding to each transportation node on the transportation node link according to the first logistics information. If the second logistics information has completed data optimization and the first logistics information has not completed data optimization, then display the data of the target fields corresponding to each transportation node on the transportation node link according to the second logistics information.

[0080] It can be understood that the target field refers to the specific data item used to describe the key attributes of each transportation node. For example, at the inbound port node, the target field may include the inbound time, inbound terminal, etc. The data of all target fields can be extracted from various types of sub-logistics information included in the first logistics information or the second logistics information. Before preparing for data fusion, considering that the data optimization progress of the first logistics information and the second logistics information may be inconsistent, a mechanism is needed to ensure that relatively accurate and available logistics status display can be provided for users or relevant business systems before fusion. When the first logistics information has completed data optimization while the second logistics information has not, it means that the data at the shipping company level has relatively high reference value after being improved. At this time, displaying the data of the target fields corresponding to each transportation node on the transportation node link according to the first logistics information is based on the accuracy and reliability of the shipping company's data in describing the key attributes of each transportation node in the shipping process, and can reflect the general transportation status of the goods to a certain extent. Similarly, if the second logistics information has completed data optimization while the first logistics information has not, displaying the data of the target fields corresponding to each transportation node according to it can allow users to understand the general situation of each transportation node on the transportation node link from the perspectives of port area operations and relevant supervision. The principle of selective display based on the optimization situation is to make the best use of the optimized data before data fusion to avoid information blank periods due to waiting for all data optimization to be completed, and to ensure the timeliness and coherence of logistics status information.

[0081] In one embodiment, the cross-border logistics status query method based on multi-source data further includes: after the data fusion is completed, update the data displayed in the target fields corresponding to each transportation node on the transportation node link according to the third logistics information.

[0082] It can be understood that the data fusion operation integrates information from different data sources (shipping companies and port areas) to generate third-party logistics information, which presents the most comprehensive and accurate picture of the cargo transportation status. However, in the previous data display section, whether the data is displayed based on the first logistics information or the second logistics information (depending on the completion of their respective data optimizations), the presented data may only be stage-based or relatively incomplete and inaccurate. After the data fusion is completed, the data displayed in the corresponding target fields of each transportation node on the transportation node link is updated based on the third-party logistics information. The principle is to utilize the advantages of the fused data to ensure that the latest, most complete, and most realistic cargo transportation status information is provided to all logistics participants (freight forwarding enterprises, shippers, logistics operators, etc.). Through the update operation, the key data of each node can be replaced and improved according to the accurate content after fusion, avoiding information deviations caused by issues such as inconsistent data sources or untimely data updates, making the entire logistics status display highly consistent with the actual transportation progress, and providing a reliable basis for subsequent business decisions, transportation plan adjustments, etc.

[0083] In addition, more rich visualization functions can be developed during the display. For example, clicking on the ship name can call the ship AIS data to obtain the ship's location and historical track; clicking on the truck license plate can call the truck satellite data to obtain the truck's location and historical track; clicking on the destination port can call the operation data provided by the destination port to display the congestion level of the current destination port.

[0084] In one of the embodiments, for the cross-border logistics status query method based on multi-source data, please refer to Figure 3 , and it further includes steps S302 to S306.

[0085] S302, determine the first container quantity according to the first logistics information, and determine the second container quantity according to the second logistics information.

[0086] It can be understood that the first logistics information is a set of logistics data obtained through a query tool corresponding to the target shipping company, which contains many key information about cargo transportation, such as basic bill of lading information, voyage information, basic container information, and container dynamic information, etc. The first container quantity is the number of containers involved in this logistics business statistically calculated from this set of shipping company-level logistics information according to specific rules and data fields. The second logistics information is the logistics data obtained through a query tool corresponding to the target port area, covering multiple aspects such as basic bill of lading / booking information, basic container information, container dynamic information, customs information, truck information, and shipping schedule information. Correspondingly, the second container quantity is the number of containers under the same logistics business determined from these port area-related logistics data according to the established statistical logic.

[0087] S304. If the number of containers in the second shipment is less than that in the first shipment, extract the booking number from the first logistics information.

[0088] It can be understood that in cross-border logistics operations, due to different data sources and different focuses between shipping companies and port areas, the container quantities recorded for the same business may be inconsistent due to differences in data update timeliness, data statistics scope, or recording rules. Here, the inconsistency mainly lies in that the container quantity queried from the port area based on the bill of lading is less than that queried from the shipping company, resulting in incomplete information. The booking number, as a key identifier for associating goods on the shipping company side, can serve as an important clue for further querying and supplementing port area data. By extracting the booking number and querying the corresponding query tool in the port area again, it is possible to obtain container-related information that may not be reflected in the current second logistics information, thereby making the port area data more complete and accurate and keeping it consistent with the shipping company data in terms of container quantity.

[0089] Specifically, once the system determines that the number of containers in the second shipment is less than that in the first shipment, it will accurately locate the data field where the booking number is located in the first logistics information and extract it. For example, in the basic bill of lading information or booking business record module of the first logistics information, there will be a dedicated field for storing the booking number. The system accurately extracts the corresponding booking number string according to the preset field identifier and data format requirements.

[0090] S306. Use the query tool corresponding to the target port area based on the booking number to update the second logistics information.

[0091] It can be understood that this step is to initiate another query using the query tool corresponding to the target port area based on the booking number extracted in the previous step. The principle is to rely on this key identifier, the booking number, and according to the query logic of the port area data system, retrieve again from the port area data source the container information related to this booking business that may be missing or not yet updated. For example, if the number of containers in the first shipment is 100 and the number of containers in the second shipment is 95, after determining that the number of containers in the second shipment is less than that in the first shipment, the system extracts the booking number "ABC123456" from the first logistics information and is ready to use this booking number to further query the port area to improve the container quantity and detailed information about related containers in the second logistics information, ensuring that the port area data can more comprehensively reflect the actual containers involved in this shipment. This step can trigger the port area system to re-search, integrate, and return the missing container information by querying again based on the booking number, thereby realizing the update of the second logistics information, making the second logistics information more accurate and complete in terms of container quantity and the detailed status of related containers, better matching and coordinating with the first logistics information, and providing more reliable data support for the accurate presentation of the entire cross-border logistics status.

[0092] The present application provides a form highlighting device based on a large model, including an acquisition module, a query module, an optimization module, and a fusion module.

[0093] The acquisition module is used to acquire a query identifier, a target shipping company, and a target port area. The query module is used to respectively call the queryers corresponding to the target shipping company and the target port area according to the query identifier to obtain first logistics information and second logistics information. The first logistics information and the second logistics information include sub-logistics information of multiple set types. The optimization module is used to respectively perform data optimization on the first logistics information and the second logistics information. The data optimization includes: determining the current transportation node according to the logistics information to be optimized, selecting the corresponding first mapping relationship according to the current transportation node, and using the first mapping relationship to determine the sub-logistics information to be optimized and its corresponding target data source from the sub-logistics information of multiple set types, respectively calling the queryers corresponding to each target data source according to the query identifier, and replacing the corresponding sub-logistics information to be optimized with the obtained information. The target data source includes data sources other than port areas and shipping companies. The fusion module is used to perform data fusion on the first logistics information and the second logistics information to obtain third logistics information. The data fusion includes: traversing each transportation node on the transportation node link, and for the traversed transportation node, selecting one of the first logistics information and the second logistics information as the extraction source for each target field corresponding to the transportation node according to the priority access relationship to perform data extraction, so as to obtain the third logistics information including all transportation nodes.

[0094] In a third aspect, the present application provides a computer device, including one or more processors and a memory. Computer-readable instructions are stored in the memory. When the computer-readable instructions are executed by the one or more processors, the steps of the cross-border logistics status query method based on multi-source data in any of the above embodiments are executed.

[0095] In a fourth aspect, the present application provides a storage medium in which computer-readable instructions are stored. When the computer-readable instructions are executed by one or more processors, the one or more processors are caused to execute the steps of the cross-border logistics status query method based on multi-source data in any of the above embodiments.

[0096] For the specific limitations on the cross-border logistics status query device based on multi-source data, reference may be made to the limitations on the cross-border logistics status query method based on multi-source data in the foregoing text, which will not be elaborated here. Each module in the above view sorting device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor in the computer device in hardware form or independent of it, or stored in the memory in the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules. It should be noted that the division of modules in the embodiments of the present application is illustrative, only a logical function division, and there may be other division methods in actual implementation.

[0097] The present application provides a computer device, including one or more processors and a memory. Computer-readable instructions are stored in the memory. When the computer-readable instructions are executed by the one or more processors, the steps of the cross-border logistics status query method based on multi-source data in any of the above embodiments are executed.

[0098] Schematically, as Figure 4 shown, Figure 4 is a schematic internal structure diagram of a computer device provided by an embodiment of the present application. Referring to Figure 4 , the computer device 400 includes a processing component 402, which further includes one or more processors, and memory resources represented by a memory 401 for storing instructions executable by the processing component 402, such as application programs. The application programs stored in the memory 401 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 402 is configured to execute instructions to perform the steps of the cross-border logistics status query method based on multi-source data in any of the above embodiments.

[0099] The computer device 400 may further include a power supply component 403 configured to perform power management of the computer device 400, a wired or wireless model interface 404 configured to connect the computer device 400 to a model, and an input / output (I / O) interface 405.

[0100] The present application provides a storage medium. Computer-readable instructions are stored in the storage medium. When the computer-readable instructions are executed by one or more processors, the one or more processors are caused to execute the steps of the cross-border logistics status query method based on multi-source data in any of the above embodiments.

[0101] Finally, it should also be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0102] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0103] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A cross-border logistics status query method based on multi-source data, characterized in that: include: Obtain the query identifier, target ship company and target port area; According to the query identifier, the query devices corresponding to the target shipping company and the target port area are respectively called to obtain the first logistics information and the second logistics information; The first logistics information and the second logistics information include sub-logistics information of multiple set types; The first logistics information and the second logistics information are respectively optimized, and the data optimization includes: determining the current transportation node according to the logistics information to be optimized, selecting the corresponding first mapping relationship according to the current transportation node, and using the first mapping relationship to determine the sub-logistics information to be optimized and its corresponding target data source from the sub-logistics information of the set types, respectively calling the query device corresponding to each target data source according to the query identifier, and replacing the corresponding sub-logistics information to be optimized with the obtained information; the target data source includes a data source other than the port area and the shipping company; The first logistics information and the second logistics information are data-fused to obtain third logistics information, and the data fusion includes: traversing each transportation node on the transportation node link, and for the traversed transportation nodes, selecting one from the first logistics information and the second logistics information as an extraction source for each target field corresponding to the transportation node according to a priority relationship to perform data extraction, so as to obtain the third logistics information containing all the transportation nodes.

2. The cross-border logistics status query method based on multi-source data according to claim 1 is characterized in that: Determining the current transportation node according to the logistics information to be optimized includes: Retrieving a preset identification string existing in the logistics information to be optimized; The current transport node is determined according to the preset identification character string and the second mapping relationship.

3. The cross-border logistics status query method based on multi-source data according to claim 1 is characterized in that: Before fusing the first logistics information with the second logistics information, the method further includes: The first logistics information and the second logistics information are respectively cleaned, and the data cleaning includes: mapping non-standard fields in the logistics information to be cleaned to standard fields according to a field mapping rule corresponding to a query device that obtains the logistics information to be cleaned.

4. The cross-border logistics status query method based on multi-source data according to claim 3 is characterized in that: The data cleaning also includes: After mapping the non-standard fields in the logistics information to be cleaned to standard fields, judging whether the sub-logistics information included in the logistics information to be cleaned has the missing setting type according to the setting type list; If so, determining the missing setting type as the type to be compensated; For the logistics information to be cleaned belonging to the first logistics information, the third mapping relationship corresponding to the target ship company is selected to select a corresponding target type for the type to be compensated; For the logistics information to be cleaned belonging to the second logistics information, the third mapping relationship corresponding to the target port area is selected to select the corresponding target type for the type to be compensated; According to the sub-logistics information of the target type, the corresponding sub-logistics information of the type to be compensated is generated and filled into the logistics information to be cleaned.

5. The cross-border logistics status query method based on multi-source data according to claim 1 is characterized in that: Before fusing the first logistics information with the second logistics information, the method further includes: If the first logistics information has completed the data optimization and the second logistics information has not completed the data optimization, then displaying the data of the target field corresponding to each of the transportation nodes on the transportation node link according to the first logistics information; If the second logistics information has completed the data optimization and the first logistics information has not completed the data optimization, the data of the target field corresponding to each of the transport nodes on the transport node link is displayed according to the second logistics information.

6. The cross-border logistics status query method based on multi-source data according to claim 5 is characterized in that: Also includes: After the data fusion is completed, the data displayed by each of the transport nodes on the transport node link corresponding to the target field is updated according to the third logistics information.

7. The cross-border logistics status query method based on multi-source data according to claim 1 is characterized in that: Also includes: Determine the first box quantity according to the first logistics information, and determine the second box quantity according to the second logistics information; If the second box quantity is less than the first box quantity, extracting the booking number from the first logistics information; The second logistics information is updated according to the query device corresponding to the target port area according to the booking number.

8. A form highlighting device based on a large model, characterized in that: include: An acquisition module is used to acquire a query identifier, a target ship company and a target port area; A query module, used to call the query devices corresponding to the target shipping company and the target port area respectively according to the query identifier to obtain the first logistics information and the second logistics information; The first logistics information and the second logistics information include sub-logistics information of multiple set types; An optimization module is used to perform data optimization on the first logistics information and the second logistics information respectively, wherein the data optimization includes: determining the current transportation node according to the logistics information to be optimized, selecting the corresponding first mapping relationship according to the current transportation node, and using the first mapping relationship to determine the sub-logistics information to be optimized and its corresponding target data source from the sub-logistics information of the set types, respectively calling the query device corresponding to each target data source according to the query identifier, and replacing the corresponding sub-logistics information to be optimized with the obtained information; the target data source includes a data source other than the port area and the shipping company; A fusion module is used to fuse the first logistics information and the second logistics information to obtain third logistics information. The data fusion includes: traversing each transportation node on the transportation node link, and for the traversed transportation nodes, selecting one from the first logistics information and the second logistics information as an extraction source for each target field corresponding to the transportation node according to a priority relationship to perform data extraction, so as to obtain the third logistics information containing all the transportation nodes.

9. A computer device, characterized in that: It includes one or more processors and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the one or more processors, the steps of the cross-border logistics status query method based on multi-source data as described in any one of claims 1 to 7 are executed.

10. A storage medium, characterized in that: The storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the cross-border logistics status query method based on multi-source data as described in any one of claims 1 to 7.

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