Express order interception method and device, equipment and storage medium

Abstract

The invention relates to the field of logistics, and discloses a mailing order interception method, device and equipment and a storage medium, and the method is used for carrying out interception processing on a mailing order according to a risk level. The method comprises the following steps: acquiring historical intercepted data and a pre-intercepted address, performing clustering analysis on the historical intercepted data and the pre-intercepted address by using a clustering algorithm to obtain a potential new intercepted address, integrating the pre-intercepted address and the potential new intercepted address into an intercepted address set to receive a mailing order pre-submitted by a user, a sending address is extracted from the order information of the sending order; obtaining a preset interception matching rule, and judging whether the mailing address is matched with an interception address in an interception address set or not based on the interception matching rule; if the sending address is matched with the interception address in the interception address set, judging the interception level of the sending address, and generating an interception scheme according to the interception level; generating an interception operation instruction based on the interception scheme, and collecting feedback information based on the interception operation instruction.

Description

Technical Field

[0001] The present invention relates to the field of logistics technology, and in particular, to a method, device, equipment and storage medium for intercepting a sending order. Background Art

[0002] At present, with the booming development of the e-commerce industry, the volume of express delivery business has increased explosively, and the importance of the express order interception function has become increasingly prominent. However, there are many drawbacks in the interception link of traditional express order systems, which seriously affect the user experience and the economic benefits of the industry.

[0003] Firstly, the traditional interception process is cumbersome and inefficient. When a consumer needs to intercept an express delivery, they usually need to communicate with the merchant first, and then the merchant contacts the express company. This process involves multiple links, and information transmission is prone to delays, distortions or omissions, greatly increasing the communication cost and time cost. In addition, there is no unified standard for the interception processes of different express companies, and the interception systems of some small express companies are even imperfect, resulting in a low interception success rate and making it difficult to meet the user's need to intercept express deliveries in a timely and accurate manner.

[0004] Secondly, the existing systems lack intelligent prediction and active interception capabilities. In the face of natural disasters, national policy adjustments, large-scale national events, or situations where certain areas are inaccessible due to emergencies, the existing express order systems cannot predict in advance and take corresponding measures. Often, the interception process is only initiated after the customer places an order, which causes a large amount of human and material resources to be consumed in unnecessary transportation links.

[0005] Finally, the passive interception mode brings additional losses to customers. Since the system cannot identify and intercept inaccessible orders in a timely manner, customers may be forced to return goods due to the inability to deliver the express delivery, and bear the return freight and the time cost of waiting for a refund. This not only seriously affects the customer experience, but also reduces the economic benefits of the entire logistics industry.

[0006] In addition, the existing technologies also have the following defects: lack of effective utilization of historical interception data, unable to predict potential new interception addresses through data analysis; the interception address matching method is single, making it difficult to cope with complex and changeable actual situations; the interception level division is not fine enough, unable to formulate corresponding interception plans according to different risk levels; lack of an effective evaluation mechanism for interception operations, making it difficult to continuously optimize the interception strategy.

[0007] Therefore, the existing technologies still need to be improved and developed. Summary of the Invention

[0008] The present invention provides a method, device, equipment and storage medium for intercepting a sending order, which is used to intercept and process a sending order according to the risk level.

[0009] The first aspect of the present invention provides a method for intercepting a sender order. The method for intercepting a sender order includes: obtaining historical interception data and a pre-interception address, performing clustering analysis on the historical interception data and the pre-interception address by using a clustering algorithm to obtain potential new interception addresses, and integrating the pre-interception address and the potential new interception addresses into an interception address set; receiving a sender order pre-submitted by a user, and extracting a sender address from the order information of the sender order; obtaining a preset interception matching rule, and determining whether the sender address matches an interception address in the interception address set based on the interception matching rule; if the sender address matches an interception address in the interception address set, determining the interception level of the sender address, and generating an interception plan according to the interception level; generating an interception operation instruction based on the interception plan, and collecting feedback information based on the interception operation instruction.

[0010] Optionally, in the first implementation manner of the first aspect of the present invention, the obtaining historical interception data and a pre-interception address, performing clustering analysis on the historical interception data and the pre-interception address by using a clustering algorithm to obtain potential new interception addresses, and integrating the pre-interception address and the potential new interception addresses into an interception address set includes: obtaining historical interception data and a pre-interception address, performing clustering analysis on the historical interception data and the pre-interception address by using a clustering algorithm to obtain potential new interception addresses; converting the pre-interception address and the potential new interception addresses into geocodes and integrating them into an interception address set; saving the interception address set to a Mysql database.

[0011] Optionally, in the second implementation manner of the first aspect of the present invention, the obtaining historical interception data and a pre-interception address, performing clustering analysis on the historical interception data and the pre-interception address by using a clustering algorithm to obtain potential new interception addresses includes: obtaining the historical interception data and the pre-interception address, and extracting feature vectors of the historical interception data and the pre-interception address; performing clustering on the feature vectors of the historical interception data and the pre-interception address by using a DBSCAN clustering algorithm, and finding the boundary or center of each cluster according to the clustering result; expanding the boundary or center of each cluster based on a preset expansion range to obtain potential new interception addresses.

[0012] Optionally, in the third implementation manner of the first aspect of the present invention, the receiving a sender order pre-submitted by a user, and extracting a sender address from the order information of the sender order includes: constructing a Transformer model as a sender address conversion model; receiving a sender order pre-submitted by a user, and extracting a sender address text from the order information of the sender order; inputting the extracted sender address text into the sender address conversion model, and obtaining the sender address output by the sender address conversion model and the geocode corresponding to the sender address.

[0013] Optionally, in the fourth implementation manner of the first aspect of the present invention, the obtaining of the preset interception matching rule and determining whether the sender address matches the interception address in the interception address set based on the interception matching rule includes: obtaining the preset interception matching rule; if the interception matching rule is an exact matching rule, using a string comparison method to determine whether the sender address matches the interception address in the interception address set; if the interception matching rule is a fuzzy matching rule, using a similarity algorithm to calculate the similarity between the sender address and the interception address in the interception address set, comparing the calculated similarity with a preset similarity threshold, and determining whether the sender address matches the interception address in the interception address set according to the comparison result; if the interception matching rule is a range matching rule, comparing the geographical code of the sender address with the range of the interception address in the interception address set to determine whether the sender address matches the interception address in the interception address set.

[0014] Optionally, in the fifth implementation manner of the first aspect of the present invention, the determining the interception level of the sender address and generating an interception plan according to the interception level if the sender address matches the interception address in the interception address set includes: if the sender address matches the interception address in the interception address set, analyzing the risk level of the sender address; determining the interception level of the sender address according to the risk level of the sender address; obtaining an execution plan corresponding to the interception level, and generating an interception plan according to the interception level of the sender address and the execution plan corresponding to the interception level.

[0015] Optionally, in the sixth implementation manner of the first aspect of the present invention, the generating an interception operation instruction based on the interception plan and collecting feedback information based on the interception operation instruction includes: generating an interception operation instruction based on the interception plan; collecting feedback information based on the interception operation instruction and integrating the collected feedback information into structured data; evaluating the interception success rate and user satisfaction of the interception operation executed based on the interception operation instruction based on the integrated feedback information.

[0016] In a second aspect of the present invention, a device for intercepting a sender order is provided, including: a clustering module, configured to obtain historical interception data and a pre-interception address, perform clustering analysis on the historical interception data and the pre-interception address by using a clustering algorithm to obtain potential new interception addresses, and integrate the pre-interception address and the potential new interception addresses into an interception address set; an extraction module, configured to receive a sender order pre-submitted by a user, and extract a sender address from the order information of the sender order; a judgment module, configured to obtain a preset interception matching rule, and judge whether the sender address matches an interception address in the interception address set based on the interception matching rule; a generation module, configured to, if the sender address matches an interception address in the interception address set, judge an interception level of the sender address, and generate an interception plan according to the interception level; a collection module, configured to generate an interception operation instruction based on the interception plan, and collect feedback information based on the interception operation instruction.

[0017] Optionally, in a first implementation manner of the second aspect of the present invention, the clustering module includes: a clustering unit, configured to obtain historical interception data and a pre-interception address, perform clustering analysis on the historical interception data and the pre-interception address by using a clustering algorithm to obtain potential new interception addresses; an integration unit, configured to convert the pre-interception address and the potential new interception addresses into geocodes and then integrate them into an interception address set; a storage unit, configured to store the interception address set in a Mysql database.

[0018] Optionally, in a second implementation manner of the second aspect of the present invention, the extraction module includes: a construction unit, configured to construct a Transformer model as a sender address conversion model; an extraction unit, configured to receive a sender order pre-submitted by a user, and extract a sender address text from the order information of the sender order; a conversion unit, configured to input the extracted sender address text into the sender address conversion model, and obtain the sender address output by the sender address conversion model and the geocode corresponding to the sender address.

[0019] Optionally, in the third implementation manner of the second aspect of the present invention, the determination module includes: a first matching unit, configured to obtain a preset interception matching rule, and when the interception matching rule is an exact matching rule, use a string comparison method to determine whether the sender address matches the interception address in the interception address set; a second matching unit, configured to when the interception matching rule is a fuzzy matching rule, use a similarity algorithm to calculate the similarity between the sender address and the interception address in the interception address set, compare the calculated similarity with a preset similarity threshold, and determine whether the sender address matches the interception address in the interception address set according to the comparison result; a third matching unit, configured to when the interception matching rule is a range matching rule, compare the geocoding of the sender address with the range of the interception address in the interception address set to determine whether the sender address matches the interception address in the interception address set.

[0020] Optionally, in the fourth implementation manner of the second aspect of the present invention, the generation module includes: an analysis unit, configured to analyze the risk level of the sender address when the sender address matches the interception address in the interception address set; a level determination unit, configured to determine the interception level of the sender address according to the risk level of the sender address; a first generation unit, configured to obtain an execution plan corresponding to the interception level, and generate an interception plan according to the interception level of the sender address and the execution plan corresponding to the interception level.

[0021] Optionally, in the fifth implementation manner of the second aspect of the present invention, the collection module includes: a second generation unit, configured to generate an interception operation instruction based on the interception plan; a collection unit, configured to collect feedback information based on the interception operation instruction, and integrate the collected feedback information into structured data; an evaluation unit, configured to evaluate the interception success rate and user satisfaction of the interception operation executed based on the interception operation instruction based on the integrated feedback information.

[0022] The third aspect of the present invention provides a sender order interception device, including: a memory and at least one processor, where computer-readable instructions are stored in the memory, and the memory and the at least one processor are interconnected by a line; the at least one processor calls the computer-readable instructions in the memory to enable the sender order interception device to execute each step of the sender order interception method as described above.

[0023] The fourth aspect of the present invention provides a computer-readable storage medium, in which computer-readable instructions are stored, and when it runs on a computer, it enables the computer to execute each step of the sender order interception method as described above.

[0024] In the technical solution provided by the present invention, by obtaining and analyzing historical interception data and pre-interception addresses, using a clustering algorithm to identify potential new interception addresses and integrating them into the interception address set, after receiving a shipping order submitted by a user, extracting the shipping address from the order information, and judging whether the address is in the interception address set through a preset interception matching rule. If it matches, further judging the interception level of the shipping address and generating a corresponding interception plan. Finally, generating an operation instruction based on the interception plan and collecting feedback information can effectively solve the problem that the logistics order needs to be intercepted in a timely manner under specific circumstances. Moreover, the use of the clustering algorithm can dynamically identify new interception addresses, improving the accuracy and timeliness of interception. In addition, the preset interception matching rule ensures the matching requirements for different types of addresses, and the generated interception plan and operation instruction can quickly respond to user needs and be optimized through feedback information. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is the first flowchart of the shipping order interception method provided by an embodiment of the present invention;

[0026] Figure 2 It is the second flowchart of the shipping order interception method provided by an embodiment of the present invention;

[0027] Figure 3 It is the third flowchart of the shipping order interception method provided by an embodiment of the present invention;

[0028] Figure 4 It is the fourth flowchart of the shipping order interception method provided by an embodiment of the present invention;

[0029] Figure 5 It is the fifth flowchart of the shipping order interception method provided by an embodiment of the present invention;

[0030] Figure 6 It is the sixth flowchart of the shipping order interception method provided by an embodiment of the present invention;

[0031] Figure 7 It is the structural schematic diagram of the shipping order interception device provided by an embodiment of the present invention;

[0032] Figure 8 It is the structural schematic diagram of the shipping order interception device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] The embodiments of the present invention provide a method, device, equipment and storage medium for intercepting a sender order, and the method is used to intercept and process the sender order according to the risk level. The method includes: obtaining historical interception data and pre-intercept addresses, performing clustering analysis on the historical interception data and the pre-intercept addresses by using a clustering algorithm to obtain potential new interception addresses, and integrating the pre-intercept addresses and the potential new interception addresses into an interception address set; receiving a sender order pre-submitted by a user, and extracting a sender address from the order information of the sender order; obtaining a preset interception matching rule, and determining whether the sender address matches an interception address in the interception address set based on the interception matching rule; if the sender address matches an interception address in the interception address set, determining the interception level of the sender address, and generating an interception plan according to the interception level; generating an interception operation instruction based on the interception plan, and collecting feedback information based on the interception operation instruction.

[0034] The terms "first", "second", "third", "fourth", etc. (if any) in the specification, claims and drawings of the present invention are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such used data may be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order other than those illustrated or described herein. In addition, the term "comprising" or "having" and any variation thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0035] For ease of understanding, the specific process of the embodiments of the present invention will be described below. Please refer to Figure 1 , the first embodiment of a method for intercepting a sender order in the embodiments of the present invention includes:

[0036] S101. Obtain historical interception data and pre-intercept addresses, perform clustering analysis on the historical interception data and the pre-intercept addresses by using a clustering algorithm to obtain potential new interception addresses, and integrate the pre-intercept addresses and the potential new interception addresses into an interception address set.

[0037] In this embodiment, obtain historical interception data from the system storage, and these data are the address information of the orders that have undergone order interception operations in the past. At the same time, pre-intercept addresses also need to be obtained, and these addresses are the addresses that the customer service submits and are determined in advance to need to be intercepted, generally based on certain known risk factors or policy regulations.

[0038] In this embodiment, clustering algorithms (such as K-Means, DBSCAN, etc.) are used to perform clustering analysis on historical interception data and pre-interception addresses. The clustering algorithm groups addresses according to a certain similarity metric between addresses (such as geographical distance, similarity of address texts, etc.). For the clustering results, analyze the characteristics of each cluster to find potential new interception addresses. For example, if in a cluster, most addresses are concentrated in a specific area of a certain city, and the boundary addresses of this area have not been explicitly marked as interception addresses before, then the surrounding addresses of this area may be potential new interception addresses. These potential new interception addresses can be mined according to business requirements and the characteristics of the clustering algorithm. Heuristic rules can be used, such as considering the center and radius range of the cluster, and expanding the boundary of the cluster by a certain range as potential new interception addresses.

[0039] Understandably, the execution subject of the present invention can be a sender order interception device, or it can also be a terminal or a server, and specific limitations are not made here. In this embodiment of the present invention, the server is taken as the execution subject for illustration.

[0040] S102. Receive a sender order pre-submitted by a user, and extract the sender address from the order information of the sender order.

[0041] In this embodiment, the order information of the sender order includes various information provided by the user, including sender address information, sender contact person, recipient address, recipient contact person, and other information.

[0042] S103. Obtain a preset interception matching rule, and determine whether the sender address matches the interception addresses in the interception address set based on the interception matching rule.

[0043] In this embodiment, obtain the preset interception matching rule from the rule library. The interception matching rule is pre-established according to business requirements and risk assessment, and there are various types, such as exact matching, fuzzy matching, range matching, etc. The exact matching rule requires that the sender address be exactly the same as the address in the interception address set, which is usually used for precise interception of high-risk addresses; the fuzzy matching rule allows a certain degree of difference in address information, and judges by calculating the similarity (such as using algorithms such as edit distance, cosine similarity, etc.); the range matching rule involves a geographical range, and intercepts when the sender address is within a certain address range (such as the geographical coding range of a certain area).

[0044] S104. If the sender address matches the interception addresses in the interception address set, then determine the interception level of the sender address, and generate an interception plan according to the interception level.

[0045] In this embodiment, once it is determined that the mailing address matches an address in the interception address set, it is necessary to determine the interception level of the mailing address. The interception level can be determined based on a variety of factors, such as the interception frequency of the address in historical interception data, the risk type involved in the address (such as the severity of contraband involved, the behavior history of the offending user associated with the address, etc.). Different interception levels can represent different risk levels and urgency of processing, such as high, medium, and low interception levels.

[0046] In this embodiment, according to the interception level, a corresponding interception solution is selected from a preset interception solution library. A high interception level corresponds to a more stringent handling measure, such as immediate cancellation of the order; a medium interception level may be to suspend order processing and wait for further review; a low interception level may be to notify the user to modify the shipping address or provide more information.

[0047] S105: Generate an interception operation instruction based on the interception plan, and collect feedback information based on the interception operation instruction.

[0048] In this embodiment, specific interception operation instructions are generated according to the generated interception plan. These instructions will be sent to the corresponding logistics business system to instruct them how to process the order, such as calling the system's order cancellation function, suspending the order processing flow, notifying the user, etc.

[0049] In this embodiment, after executing the interception operation instruction, feedback information from different channels is collected, including user feedback (such as user complaints and inquiries about the interception operation, etc.) and system execution results (such as whether the order is successfully canceled, whether the suspension is effective, etc.). These feedback information are sorted and stored, and can be stored as structured data for subsequent analysis and evaluation, such as evaluating the effectiveness of the interception operation and user satisfaction, and adjusting and optimizing the interception rules and plans based on the feedback information.

[0050] The present embodiment provides a method for intercepting a mailing order, which obtains and analyzes historical interception data and pre-interception addresses, uses a clustering algorithm to identify potential new interception addresses, and integrates them into the interception address set. After receiving a mailing order submitted by a user, the mailing address is extracted from the order information, and a preset interception matching rule is used to determine whether the address is in the interception address set. If a match is found, the interception level of the mailing address is further determined, and a corresponding interception plan is generated. Finally, an operation instruction is generated based on the interception plan, and feedback information is collected. This method can effectively solve the problem that logistics orders need to be intercepted in a timely manner under specific circumstances. Moreover, the use of a clustering algorithm can dynamically identify new interception addresses, thereby improving the accuracy and timeliness of interception. In addition, the preset interception matching rules ensure that different types of address matching requirements are met. The generated interception plan and operation instruction can quickly respond to user needs and be optimized through feedback information.

[0051] Please refer to Figure 2 , the second embodiment of the sender order interception method in the embodiments of the present invention includes:

[0052] S201. Obtain historical interception data and pre-interception addresses, and use a clustering algorithm to perform clustering analysis on the historical interception data and pre-interception addresses to obtain potential new interception addresses.

[0053] In this embodiment, obtaining historical interception data and pre-interception addresses, and using a clustering algorithm to perform clustering analysis on the historical interception data and pre-interception addresses to obtain potential new interception addresses includes: obtaining historical interception data and pre-interception addresses, and extracting the feature vectors of the historical interception data and pre-interception addresses; using the DBSCAN clustering algorithm to cluster the feature vectors of the historical interception data and pre-interception addresses, and finding the boundaries or centers of each cluster according to the clustering results; based on a preset expansion range, expanding the boundaries or centers of each cluster to obtain potential new interception addresses.

[0054] In this embodiment, for an address, it can be considered to split it into different dimensions, such as longitude, latitude, area code, city code, etc. Natural language processing technology can also be used to convert the address text into a feature vector. For example, the bag-of-words model or word embedding technology can be used to convert the words in the address text into a vector representation.

[0055] S202. Convert the pre-interception addresses and potential new interception addresses into geocodes and integrate them into interception addresses.

[0056] In this embodiment, the pre-interception addresses and potential new interception addresses are sent to the geocoding service one by one to obtain their corresponding geocodes. The converted geocoded addresses are combined together to form an interception address set. The interception address set includes the geocoded forms of the pre-interception addresses and newly discovered potential interception addresses, ensuring the consistency and comparability of address information.

[0057] S203. Save the interception address set to the Mysql database.

[0058] In this embodiment, a table is designed in the MySQL database to store the interception address set. The table structure can include fields such as address_id (unique address identifier), longitude, latitude, address_type (address type, such as pre-interception address, potential new interception address), cluster_id (number of the clustering cluster, used to identify which clustering cluster the address belongs to), etc. Use SQL statements to insert the data of the interception address set into the database table.

[0059] In this embodiment, by analyzing historical interception data and pre-interception addresses through a clustering algorithm, potential new interception addresses can be effectively identified and integrated into the interception address set together with the pre-interception addresses. Compared with the prior art, this application improves the accuracy and efficiency of sender order interception and reduces the probability of misinterception. At the same time, the Mysql database is used to store the interception address set, which is convenient for subsequent query and management, and improves the maintainability and scalability of the system.

[0060] Please refer to Figure 3 , the third embodiment of a method for intercepting a sender order in the embodiment of the present invention includes:

[0061] S301. Construct a Transformer model as a sender address conversion model.

[0062] In this embodiment, the Transformer model is a neural network architecture based on the attention mechanism and performs well in processing sequence data. It abandons the traditional recurrent neural network (RNN) and convolutional neural network (CNN), and can better capture long-range dependencies in the sequence through the self-attention mechanism. When processing sender address information, the length and structure of the address text may vary, and the Transformer can effectively handle this variation.

[0063] In this embodiment, a sequence-to-sequence (Seq2Seq) Transformer model is constructed, including an encoder and a decoder part. The encoder encodes the input sender address text sequence into a series of hidden states, which contain the semantic and structural information of the address text. The decoder gradually generates a standardized sender address and the corresponding geocoding based on the output of the encoder and its own context information.

[0064] In the process of training the Transformer model to obtain the sender address conversion model, a supervised learning method is used. The original sender address text is used as the input, and the standardized sender address and geocoding are used as the target output. By minimizing the difference between the predicted output and the target output (for example, using the cross-entropy loss function), the parameters of the model are updated using the gradient descent algorithm. After multiple iterations of training, the model is capable of converting sender address texts in various formats into a standard form and obtaining geocoding.

[0065] S302. Receive a sender order pre-submitted by a user, and extract the sender address text from the order information of the sender order.

[0066] In this embodiment, for the received order, it is necessary to parse it and extract the part containing the sender's address. For example, in an order in JSON format, it may be necessary to find the sender's address field through key-value pair lookup, such as {"sender":{"address":"XX Street, No. XX, XX District, XX City, XX Province"}}, and extract "XX Street, No. XX, XX District, XX City, XX Province" as the sender's address text.

[0067] S303. Input the extracted sender's address text into the sender's address conversion model, and obtain the sender's address output by the sender's address conversion model and the corresponding geocoding of the sender's address.

[0068] In this embodiment, before inputting the sender's address text into the model, some preprocessing can be performed on it, such as splitting the address text into words or character sequences, converting it into an input format acceptable to the model, for example, encoding the text into a sequence of numbers (each word can be mapped to a unique integer using a vocabulary), and adding necessary start and end markers.

[0069] In this embodiment, the extracted sender's address text is input into the sender's address conversion model, and the model will output the standardized sender's address and the corresponding geocoding. For the output standardized sender's address, it needs to be converted back from the sequence of numbers to text form (through inverse mapping of the vocabulary). For the geocoding, it can be information represented by longitude and latitude coordinates or other geocoding systems (such as Geohash), and it needs to be parsed into usable geographical information.

[0070] In this embodiment, by constructing a sequence-to-sequence model based on the Transformer architecture, efficient processing and conversion of the sender's address text are realized. Especially when dealing with complex and diverse sender's addresses, it can significantly improve the accuracy of address extraction, reduce the need for manual intervention, and improve the automation level of logistics order processing.

[0071] Please refer to Figure 4 , the fourth embodiment of a method for intercepting sender orders in the embodiments of the present invention includes:

[0072] S401. Obtain a preset interception matching rule. If the interception matching rule is an exact matching rule, use a string comparison method to determine whether the sender's address matches the interception address in the interception address set.

[0073] In this embodiment, the implementation method of the exact matching rule may include: through a string comparison algorithm, such as the equals method in Java, directly compare the sender's address with each address in the interception address set to determine whether the two are exactly the same. If they are exactly the same, it means that the sender's address matches the interception address in the interception address set.

[0074] S402. If the interception matching rule is a fuzzy matching rule, use a similarity algorithm to calculate the similarity between the sender address and the interception addresses in the interception address set, compare the calculated similarity with a preset similarity threshold, and determine whether the sender address matches the interception addresses in the interception address set according to the comparison result.

[0075] In this embodiment, the implementation method of the fuzzy matching rule may include: using the Levenshtein distance algorithm or the Jaccard similarity coefficient algorithm to calculate the similarity between addresses, and then comparing it with a preset similarity threshold. If the similarity is higher than the threshold, it is considered that the addresses match.

[0076] S403. If the interception matching rule is a range matching rule, compare the geocoding of the sender address with the range of the interception addresses in the interception address set to determine whether the sender address matches the interception addresses in the interception address set.

[0077] In this embodiment, the implementation method of the range matching rule may include: using geocoding technology to convert the address into longitude and latitude coordinates, and then comparing whether the coordinates of the sender address are within the range of the interception addresses, for example, by implementing an algorithm for determining whether a point is within a polygon. If the coordinates of the sender address are within the range of the interception addresses, it means that the sender address matches the interception addresses in the interception address set.

[0078] In this embodiment, it can flexibly handle the address matching requirements in different scenarios, improve the accuracy and effectiveness of the interception of sender orders. Through the combination of precise matching, fuzzy matching, and range matching, it can accurately determine the matching situation between the sender address and the interception address in different situations, thereby improving the success rate of the interception operation and user satisfaction.

[0079] Please refer to Figure 5 , the fifth embodiment of a method for intercepting sender orders in an embodiment of the present invention includes:

[0080] S501. If the sender address matches the interception addresses in the interception address set, analyze the risk level of the sender address.

[0081] In this embodiment, when analyzing the risk level of the sender address, multiple factors are considered comprehensively, such as the frequency of occurrence of this address in historical interception data. If an address frequently appears in intercepted orders, it indicates a higher risk; the severity of the interception reasons caused by this address in the past will also be considered, such as situations involving the transportation of contraband, fraud, etc. If it is associated with serious violations multiple times, its risk level will surely be higher. In addition, the overall risk situation of the area where this address is located will also be taken into account. For example, in some areas, due to factors such as the security environment and policy supervision, the overall logistics risk is relatively high.

[0082] S502. Determine the interception level of the sender address according to the risk level of the sender address.

[0083] In this embodiment, according to the analysis result of the risk level, determine the interception level of the sender address. Generally speaking, the higher the risk level, the higher the corresponding interception level. For example, the interception level can be divided into three levels: high, medium, and low. If the risk level of the sender address is high, that is, it frequently involves serious violations, then its interception level may be determined to be high; if the risk level is low and only some minor abnormalities occur occasionally, the interception level may be low.

[0084] S503. Obtain the execution plan corresponding to the interception level, and generate an interception plan according to the interception level of the sender address and the execution plan corresponding to the interception level.

[0085] In this embodiment, different interception levels correspond to different processing methods. For the high interception level, the corresponding execution plan is to immediately stop order processing; the execution plan for the medium interception level may be to first suspend order transportation, contact the sender to verify information, and further process if no reasonable explanation can be provided; the low interception level may only mark the order and strengthen the monitoring during the subsequent transportation process. Then, combine the interception level of the sender address and the corresponding execution plan to generate a detailed interception plan, clarifying the specific operations and responsible persons for each step.

[0086] In this embodiment, first, by automatically generating interception operation instructions, the efficiency and accuracy of interception operations are improved; second, by collecting and integrating feedback information, the effect of interception operations can be monitored and evaluated in real time, so as to adjust and optimize the interception plan in a timely manner; finally, by evaluating the interception success rate and user satisfaction, the quality of interception operations can be continuously improved and the user experience can be enhanced.

[0087] Please refer to Figure 6 , the sixth embodiment of a method for intercepting a sender order in an embodiment of the present invention includes:

[0088] S601. Generate an interception operation instruction based on the interception plan.

[0089] In this embodiment, first, based on the interception plan, generate specific operation instructions, which may include but are not limited to operations such as express delivery interception, rerouting, and notifying users. Then, through the automated module of the system, these operation instructions are passed to the relevant execution units to ensure the efficient execution of interception operations.

[0090] S602. Collect feedback information based on the interception operation instruction, and integrate the collected feedback information into structured data.

[0091] In this embodiment, for the step of collecting feedback information, the system will automatically collect the user's feedback information after the interception operation is executed. This information can be obtained through various channels such as user evaluations and operation logs. The collected feedback information will be integrated into structured data and stored in the database for subsequent analysis and utilization.

[0092] S603. Based on the integrated feedback information, evaluate the interception success rate and user satisfaction of the interception operation executed based on the interception operation instruction.

[0093] In this embodiment, based on the integrated feedback information, data analysis tools can be used to evaluate the effect of the interception operation. Specifically, the effectiveness of the interception operation and the user experience can be evaluated by statistically analyzing indicators such as the interception success rate and user satisfaction. Through these evaluation results, the interception scheme and operation instructions can be further optimized to improve the overall performance of the system and user satisfaction.

[0094] In this embodiment, when evaluating the interception success rate, the ratio of the number of successful interception operations to the total number of operations within a certain period of time can be statistically analyzed. When evaluating user satisfaction, data such as user feedback scores and comments can be analyzed to form a satisfaction report.

[0095] In this embodiment, by generating interception operation instructions based on the interception scheme, collecting feedback information based on the interception operation instructions, integrating this feedback information into structured data, and finally evaluating the interception success rate and user satisfaction of the interception operation, an efficient and automated method for intercepting shipping orders is provided.

[0096] The method for intercepting shipping orders in the embodiments of the present invention has been described above. Next, the device in the embodiments of the present invention will be described. Please refer to Figure 7 , the implementation manner of the shipping order interception device in the embodiments of the present invention includes:

[0097] The clustering module 701 is used to obtain historical interception data and pre-interception addresses, perform clustering analysis on the historical interception data and the pre-interception addresses using a clustering algorithm to obtain potential new interception addresses, and integrate the pre-interception addresses and the potential new interception addresses into an interception address set;

[0098] The extraction module 702 is used to receive a shipping order pre-submitted by a user and extract the shipping address from the order information of the shipping order;

[0099] The judgment module 703 is used to obtain a preset interception matching rule and judge whether the shipping address matches the interception addresses in the interception address set based on the interception matching rule;

[0100] A generating module 704, configured to, if the sender address matches an intercepted address in the intercepted address set, determine the interception level of the sender address, and generate an interception plan according to the interception level;

[0101] A collecting module 705, configured to generate an interception operation instruction based on the interception plan, and collect feedback information based on the interception operation instruction.

[0102] In this embodiment, the clustering module 701 includes: a clustering unit 7011, configured to obtain historical intercepted data and a pre-intercepted address, and perform clustering analysis on the historical intercepted data and the pre-intercepted address by using a clustering algorithm to obtain potential new intercepted addresses; an integration unit 7012, configured to convert the pre-intercepted address and the potential new intercepted addresses into geocodes and integrate them into an intercepted address set; and a saving unit 7013, configured to save the intercepted address set into a Mysql database.

[0103] In this embodiment, the extraction module 702 includes: a construction unit 7021, configured to construct a Transformer model as a sender address conversion model; an extraction unit 7022, configured to receive a sender order pre-submitted by a user, and extract a sender address text from the order information of the sender order; and a conversion unit 7023, configured to input the extracted sender address text into the sender address conversion model, and obtain the sender address output by the sender address conversion model and the geocode corresponding to the sender address.

[0104] In this embodiment, the judgment module 703 includes: a first matching unit 7031, configured to obtain a preset interception matching rule, and when the interception matching rule is an exact matching rule, use a string comparison method to determine whether the sender address matches an intercepted address in the intercepted address set; a second matching unit 7032, configured to, when the interception matching rule is a fuzzy matching rule, use a similarity algorithm to calculate the similarity between the sender address and an intercepted address in the intercepted address set, compare the calculated similarity with a preset similarity threshold, and determine whether the sender address matches an intercepted address in the intercepted address set according to the comparison result; and a third matching unit 7033, configured to, when the interception matching rule is a range matching rule, compare the geocode of the sender address with the range of an intercepted address in the intercepted address set to determine whether the sender address matches an intercepted address in the intercepted address set.

[0105] In this embodiment, the generation module 704 includes: an analysis unit 7041, configured to analyze the risk level of the sender address when the sender address matches an interception address in the interception address set; a level determination unit 7042, configured to determine the interception level of the sender address according to the risk level of the sender address; and a first generation unit 7043, configured to obtain an execution plan corresponding to the interception level, and generate an interception plan according to the interception level of the sender address and the execution plan corresponding to the interception level.

[0106] In this embodiment, the collection module 705 includes: a second generation unit 7051, configured to generate an interception operation instruction based on the interception plan; a collection unit 7052, configured to collect feedback information based on the interception operation instruction, and integrate the collected feedback information into structured data; and an evaluation unit 7053, configured to evaluate the interception success rate and user satisfaction of the interception operation executed based on the interception operation instruction based on the integrated feedback information.

[0107] In this embodiment, by obtaining and analyzing historical interception data and pre-interception addresses, using a clustering algorithm to identify potential new interception addresses and integrating them into the interception address set, after receiving a sender order submitted by a user, extracting the sender address from the order information, and determining whether the address is in the interception address set through a preset interception matching rule. If it matches, further determining the interception level of the sender address and generating a corresponding interception plan. Finally, generating an operation instruction based on the interception plan and collecting feedback information can effectively solve the problem that a logistics order needs to be intercepted in a specific situation. Moreover, the use of the clustering algorithm can dynamically identify new interception addresses, improving the accuracy and timeliness of interception. In addition, the preset interception matching rule ensures different types of address matching requirements, and the generated interception plan and operation instruction can quickly respond to user needs and be optimized through feedback information.

[0108] Figure 7 The structure of the shown sender order interception device does not limit the sender order interception device, and can implement the steps of the sender order interception method provided in the above method embodiments.

[0109] Above Figure 7 The sender order interception device in the embodiments of the present invention is described in detail from the perspective of modular functional entities. Next, the sender order interception device in the embodiments of the present invention is described in detail from the perspective of hardware processing.

[0110] Figure 8FIG. 0 is a schematic structural diagram of a device for intercepting a shipping order provided by an embodiment of the present invention. The device 800 may vary greatly due to different configurations or performances, and may include one or more processors (central processing units, CPUs) 810 (for example, one or more processors) and a memory 820, and one or more storage media 830 (for example, one or more mass storage devices) for storing application programs 833 or data 832. Among them, the memory 820 and the storage media 830 may be transient storage or persistent storage. The program stored in the storage media 830 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the device 800. Further, the processor 810 may be configured to communicate with the storage media 830 and execute a series of instruction operations in the storage media on the device 800.

[0111] The device 800 may further include one or more power supplies 840, one or more wired or wireless network interfaces 850, one or more input / output interfaces 860, and / or one or more operating systems 831, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, and so on.

[0112] The embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are run on a computer, the computer is caused to execute the steps of the method for intercepting a shipping order.

[0113] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described system, device, or unit can refer to the corresponding processes in the foregoing method embodiments and will not be described herein again.

[0114] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0115] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of various embodiments of the present invention.

Claims

1. A method for intercepting a mailing order, characterized in that: The shipping order interception method comprises: Acquire historical interception data and pre-interception addresses, perform cluster analysis on the historical interception data and the pre-interception addresses using a clustering algorithm to obtain potential new interception addresses, and integrate the pre-interception addresses and the potential new interception addresses into an interception address set; Receive the shipping order pre-submitted by the user, and extract the shipping address from the order information of the shipping order; Obtaining a preset interception matching rule, and judging whether the mailing address matches an interception address in the interception address set based on the interception matching rule; If the mailing address matches an interception address in the interception address set, determining the interception level of the mailing address, and generating an interception plan according to the interception level; An interception operation instruction is generated based on the interception scheme, and feedback information is collected based on the interception operation instruction.

2. The method for intercepting a mailing order according to claim 1, characterized in that: The acquiring of historical interception data and pre-interception addresses, performing cluster analysis on the historical interception data and the pre-interception addresses using a clustering algorithm to obtain potential new interception addresses, and integrating the pre-interception addresses and the potential new interception addresses into an interception address set, includes: Acquire historical interception data and pre-interception addresses, and perform cluster analysis on the historical interception data and the pre-interception addresses using a clustering algorithm to obtain potential new interception addresses; The pre-interception addresses and the potential new interception addresses are converted into geocodes and then integrated into an interception address set; The interception address set is saved in the MySQL database.

3. The method for intercepting a mailing order according to claim 2, characterized in that: The acquiring of historical interception data and pre-interception addresses, and performing cluster analysis on the historical interception data and the pre-interception addresses using a clustering algorithm to obtain potential new interception addresses includes: Acquiring the historical interception data and the pre-interception address, and extracting feature vectors of the historical interception data and the pre-interception address; Clustering the feature vectors of the historical interception data and the pre-interception addresses using a DBSCAN clustering algorithm, and finding the boundary or center of each cluster based on the clustering results; Based on the preset expansion range, the boundary or center of each cluster is expanded to obtain potential new interception addresses.

4. The method for intercepting a mailing order according to claim 1, characterized in that: The receiving of the shipping order pre-submitted by the user and extracting the shipping address from the order information of the shipping order includes: Build a Transformer model as a mailing address conversion model; Receive the shipping order pre-submitted by the user, and extract the shipping address text from the order information of the shipping order; The extracted mailing address text is input into a mailing address conversion model, and the mailing address output by the mailing address conversion model and the geocode corresponding to the mailing address are obtained.

5. The method for intercepting a mailing order according to claim 1, characterized in that: The obtaining of a preset interception matching rule, and judging whether the mailing address matches an interception address in the interception address set based on the interception matching rule, includes: Obtaining a preset interception matching rule, and if the interception matching rule is an exact matching rule, using a string comparison method to determine whether the mailing address matches an interception address in the interception address set; If the interception matching rule is a fuzzy matching rule, a similarity algorithm is used to calculate the similarity between the mailing address and the interception addresses in the interception address set, the calculated similarity is compared with a preset similarity threshold, and it is determined whether the mailing address matches the interception addresses in the interception address set according to the comparison result; If the interception matching rule is a range matching rule, the geographic code of the mailing address is compared with the range of interception addresses in the interception address set to determine whether the mailing address matches the interception addresses in the interception address set.

6. The method for intercepting a mailing order according to claim 1, characterized in that: If the mailing address matches an interception address in the interception address set, determining the interception level of the mailing address, and generating an interception plan according to the interception level, including: If the mailing address matches an interception address in the interception address set, analyzing the risk level of the mailing address; Determining an interception level of the sending address according to the risk level of the sending address; An execution plan corresponding to the interception level is obtained, and an interception plan is generated according to the interception level of the mailing address and the execution plan corresponding to the interception level.

7. The method for intercepting a mailing order according to claim 1, characterized in that: The generating an interception operation instruction based on the interception scheme, and collecting feedback information based on the interception operation instruction, includes: Generate interception operation instructions based on the interception plan; Collect feedback information based on interception operation instructions, and integrate the collected feedback information into structured data; Based on the integrated feedback information, the interception success rate and user satisfaction of the interception operation performed based on the interception operation instruction are evaluated.

8. A device for intercepting mailing orders, characterized in that: include: A clustering module, used to obtain historical interception data and pre-interception addresses, perform cluster analysis on the historical interception data and the pre-interception addresses using a clustering algorithm to obtain potential new interception addresses, and integrate the pre-interception addresses and the potential new interception addresses into an interception address set; The extraction module is used to receive the shipping order pre-submitted by the user and extract the shipping address from the order information of the shipping order; A judgment module, used for obtaining a preset interception matching rule, and judging whether the mailing address matches an interception address in the interception address set based on the interception matching rule; a generating module, configured to determine the interception level of the sending address if the sending address matches an interception address in the interception address set, and generate an interception plan according to the interception level; The collection module is used to generate an interception operation instruction based on the interception scheme, and collect feedback information based on the interception operation instruction.

9. A mailing order interception device, characterized in that: comprising a memory and at least one processor, wherein the memory has computer-readable instructions stored therein; The at least one processor calls the computer-readable instructions in the memory to execute the various steps of the shipping order interception method as described in any one of claims 1-7.

10. A computer-readable storage medium having computer-readable instructions stored thereon, characterized in that: When the computer-readable instructions are executed by a processor, the various steps of the method for intercepting a shipping order as described in any one of claims 1-7 are implemented.

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