Signing log report query management method and device, equipment and storage medium

Abstract

The invention relates to the technical field of logistics management, in particular to a sign-in log report query management method and device, equipment and a storage medium. The sign-in log report query management method comprises the following steps: obtaining logistics sign-in log data, and establishing a multi-dimensional data model according to the logistics sign-in log data; according to the user query request, querying data in the multi-dimensional data model by adopting a pre-constructed user query preference model or a semantic understanding-based query analysis technology to obtain original data; establishing a depth analysis rule, and performing depth analysis on the original data according to the depth analysis rule to obtain depth analysis data; and performing visualization processing on the original data and the depth analysis data to obtain a visual chart, and outputting the original data, the depth analysis data and the visual chart to a user. According to the method, the query response time under the condition of big data can be shortened, the user can deeply understand details of signed data, and powerful support is provided for logistics operation decision making.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics management, and particularly to a method, device, equipment and storage medium for querying and managing a signature log report. Background Art

[0002] In the logistics industry, the signature log report is an important basis for recording the goods receipt situation. At present, the query of the signature log report in the system mainly adopts the traditional method, that is, traversing the entire database for query. With the continuous growth of logistics business, the amount of data related to the signature log report has become extremely large. When facing a large amount of data, the traditional query method often has the problem of long query response time, seriously affecting work efficiency. Especially during the peak logistics period, a large number of query requests may cause the system to freeze or even crash. Moreover, the existing query method lacks intelligent analysis capabilities and cannot actively provide users with valuable query suggestions and data insights based on the user's historical query behavior and business characteristics.

[0003] It can be seen that the existing technology still needs to be improved. Summary of the Invention

[0004] In view of the deficiencies of the above-mentioned prior art, the purpose of the present invention is to provide a method, device, equipment and storage medium for querying and managing a signature log report, aiming to solve the problems that the traditional query method in the existing technology often has a long query response time and lacks intelligent analysis capabilities.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions:

[0006] The first aspect of the present invention provides a method for querying and managing a signature log report, including the following steps: obtaining logistics signature log data, performing multi-dimensional data modeling based on the logistics signature log data to obtain a multi-dimensional data model; obtaining a user query request, and according to the user query request, querying the data in the multi-dimensional data model by using a pre-constructed user query preference model or a query parsing technology based on semantic understanding to obtain original data; establishing a deep analysis rule, and performing deep analysis on the original data according to the deep analysis rule to obtain deep analysis data; performing visualization processing on the original data and the deep analysis data to obtain a visualization chart, and outputting the original data, the deep analysis data and the visualization chart to the user.

[0007] Optionally, in the first implementation manner of the first aspect of the present invention, the obtaining of the logistics signature log data and the multi-dimensional data modeling based on the logistics signature log data to obtain a multi-dimensional data model specifically include: obtaining the logistics signature log data, preprocessing the logistics signature log data to obtain preprocessed data; establishing dimension design rules, and establishing multiple dimension tables according to the preprocessed data; associating the multiple dimension tables, and establishing a multi-dimensional data model according to the associated multiple dimension tables; performing distributed storage and index construction on the multiple dimension tables in the multi-dimensional data model.

[0008] Optionally, in the second implementation manner of the first aspect of the present invention, the obtaining of the user query request and the querying of the data in the multi-dimensional data model according to the user query request by using a pre-constructed user query preference model or a query parsing technique based on semantic understanding to obtain the original data specifically include: obtaining the user query request and judging the content of the user query request; if the content of the user query request is a keyword or a conditional word, using the pre-constructed user query preference model to query the data in the multi-dimensional data model according to the keyword or the conditional word to obtain the original data; if the content of the user query request is a natural language query statement, using the query parsing technique based on semantic understanding to query the data in the multi-dimensional data model according to the natural language query statement to obtain the original data.

[0009] Optionally, in the third implementation manner of the first aspect of the present invention, the if the content of the user query request is a keyword or a conditional word, using the pre-constructed user query preference model to query the data in the multi-dimensional data model according to the keyword or the conditional word to obtain the original data specifically include: obtaining the historical query records and behavior patterns of the user to construct a training set; using the training set to train a machine learning algorithm to obtain a user query preference model; using the user query preference model to query the data in the multi-dimensional data model according to the keyword or the conditional word to obtain the original data.

[0010] Optionally, in the fourth implementation manner of the first aspect of the present invention, the establishing of the in-depth analysis rules and the in-depth analysis of the original data according to the in-depth analysis rules to obtain the in-depth analysis data specifically include: establishing the in-depth analysis rules, and setting analysis schemes for different types of users respectively; obtaining user information and judging the user type, and performing in-depth analysis on the original data according to the user type and the in-depth analysis rules; for courier users, calculating the individual signature efficiency, individual signature success rate and the comparison with other couriers according to the original data, and generating improvement suggestions according to the original data; for management users, calculating the regional signature efficiency, regional signature success rate, all courier signature information and the comparison with other regions according to the original data, and generating improvement suggestions according to the original data.

[0011] Optionally, in the fifth implementation manner of the first aspect of the present invention, for the courier user, the personal signing efficiency, personal signing success rate, and comparison with other couriers are calculated based on the original data, and improvement suggestions are generated based on the original data. Specifically, it includes: for the courier user, calculating the personal signing efficiency, personal signing success rate, and comparison with other couriers based on the original data; constructing an efficiency analysis model, and calculating the key factors affecting the courier's signing efficiency based on the original data; generating improvement suggestions based on the key factors and the original data, and the improvement suggestions include time planning suggestions and delivery route suggestions.

[0012] Optionally, in the sixth implementation manner of the first aspect of the present invention, the original data and the in-depth analysis data are visually processed to obtain a visual chart, and the original data, the in-depth analysis data, and the visual chart are output to the user. Specifically, it includes: visually processing the original data and the in-depth analysis data by using a map visualization library or a chart library to obtain a visual chart; respectively marking the content in the visual chart, and binding the marked content to the original data or the in-depth analysis data; setting paged loading for the original data, the in-depth analysis data, and the visual chart, and outputting the original data, the in-depth analysis data, and the visual chart to the user.

[0013] The second aspect of the present invention provides a signing log report query and management device, including: a construction module, configured to obtain logistics signing log data, perform multi-dimensional data modeling based on the logistics signing log data to obtain a multi-dimensional data model; a query module, configured to obtain a user query request, and query the data in the multi-dimensional data model according to the user query request by using a pre-constructed user query preference model or a query parsing technology based on semantic understanding to obtain the original data; an analysis module, configured to establish in-depth analysis rules, and perform in-depth analysis on the original data according to the in-depth analysis rules to obtain in-depth analysis data; a visualization module, configured to visually process the original data and the in-depth analysis data to obtain a visual chart, and output the original data, the in-depth analysis data, and the visual chart to the user.

[0014] Optionally, in the first implementation manner of the second aspect of the present invention, the construction module includes: a preprocessing sub-module, configured to obtain logistics signing log data, and preprocess the logistics signing log data to obtain preprocessed data; an establishment sub-module, configured to establish dimension design rules, and establish multiple dimension tables according to the preprocessed data; an association sub-module, configured to associate the multiple dimension tables, and establish a multi-dimensional data model according to the associated multiple dimension tables; a storage sub-module, configured to perform distributed storage and index construction on the multiple dimension tables in the multi-dimensional data model.

[0015] Optionally, in the second implementation manner of the second aspect of the present invention, the query module includes: a judgment sub-module, configured to obtain a user query request and judge the content of the user query request; a first query sub-module, configured to, if the content of the user query request is a keyword or a conditional word, use a pre-constructed user query preference model to query data in a multi-dimensional data model according to the keyword or the conditional word to obtain raw data; a second query sub-module, configured to, if the content of the user query request is a natural language query statement, use a query parsing technique based on semantic understanding to query data in the multi-dimensional data model according to the natural language query statement to obtain raw data.

[0016] Optionally, in the third implementation manner of the second aspect of the present invention, the first query sub-module includes: a construction unit, configured to obtain a user's historical query records and behavior patterns to construct a training set; a training unit, configured to use the training set to train a machine learning algorithm to obtain a user query preference model; a query unit, configured to use the user query preference model to query data in the multi-dimensional data model according to the keyword or the conditional word to obtain raw data.

[0017] Optionally, in the fourth implementation manner of the second aspect of the present invention, the analysis module includes: a setting sub-module, configured to establish in-depth analysis rules and set analysis schemes for different types of users respectively; an in-depth analysis sub-module, configured to obtain user information and judge the user type, and perform in-depth analysis on the raw data according to the user type and the in-depth analysis rules; a first generation sub-module, configured to, for a courier user, calculate the individual signing efficiency, individual signing success rate, and comparison with other couriers according to the raw data, and generate improvement suggestions according to the raw data; a second generation sub-module, configured to, for a management user, calculate the regional signing efficiency, regional signing success rate, signing information of all couriers, and comparison with other regions according to the raw data, and generate improvement suggestions according to the raw data.

[0018] Optionally, in the fifth implementation manner of the second aspect of the present invention, the first generation sub-module includes: a first calculation unit, configured to, for a courier user, calculate the individual signing efficiency, individual signing success rate, and comparison with other couriers according to the raw data; a second calculation unit, configured to construct an efficiency analysis model and calculate key factors affecting the courier's signing efficiency according to the raw data; a generation unit, configured to generate improvement suggestions according to the key factors and the raw data, and the improvement suggestions include time planning suggestions and delivery route suggestions.

[0019] Optionally, in the sixth implementation manner of the second aspect of the present invention, the visualization module includes: a visualization unit for visualizing the original data and the in-depth analysis data using a map visualization library or a chart library to obtain a visualization chart; a marking unit for marking the content in the visualization chart respectively and binding the marked content to the original data or the in-depth analysis data; and an output unit for performing paging loading settings on the original data, the in-depth analysis data, and the visualization chart, and outputting the original data, the in-depth analysis data, and the visualization chart to the user.

[0020] The third aspect of the present invention provides a receipt log report query and management device, including a memory and at least one processor, wherein computer-readable instructions are stored in the memory; the at least one processor calls the computer-readable instructions in the memory to execute each step of the receipt log report query and management method as described above.

[0021] The fourth aspect of the present invention provides a computer-readable storage medium, on which computer-readable instructions are stored, and when the computer-readable instructions are executed by a processor, each step of the receipt log report query and management method as described above is implemented.

[0022] Beneficial effects: The present invention provides a receipt log report query and management method. The receipt log report query and management method first obtains logistics receipt log data, performs multi-dimensional data modeling based on the logistics receipt log data to obtain a multi-dimensional data model, so that when querying, it matches the corresponding dimension data according to the key information, without traversing the database, improving the query speed; then obtains a user query request, and according to the user query request, queries the data in the multi-dimensional data model using a pre-constructed user query preference model or a query parsing technology based on semantic understanding to obtain the original data, improving the intelligence and accuracy of the query; then establishes in-depth analysis rules, performs in-depth analysis on the original data according to the in-depth analysis rules to obtain in-depth analysis data, enabling the user to comprehensively understand the business status based on the in-depth analysis data and optimize the work; finally, visualizes the original data and the in-depth analysis data to obtain a visualization chart, and outputs the original data, the in-depth analysis data, and the visualization chart to the user, enabling the customer to intuitively understand the data, thereby better insight into the data. Description of the Drawings

[0023] Figure 1 It is the first flow chart of the receipt log report query and management method provided by the embodiment of the present invention;

[0024] Figure 2 It is the second flow chart of the receipt log report query and management method provided by the embodiment of the present invention;

[0025] Figure 3 The third flowchart of the receipt log report query management method provided by the embodiment of the present invention;

[0026] Figure 4 The fourth flowchart of the receipt log report query management method provided by the embodiment of the present invention;

[0027] Figure 5 The fifth flowchart of the receipt log report query management method provided by the embodiment of the present invention;

[0028] Figure 6 The sixth flowchart of the receipt log report query management method provided by the embodiment of the present invention;

[0029] Figure 7 The seventh flowchart of the receipt log report query management method provided by the embodiment of the present invention;

[0030] Figure 8 A schematic structural diagram of the receipt log report query management device provided by the embodiment of the present invention;

[0031] Figure 9 Another schematic structural diagram of the receipt log report query management device provided by the embodiment of the present invention;

[0032] Figure 10 A schematic structural diagram of the receipt log report query management device provided by the embodiment of the present invention. Detailed implementation manners

[0033] The present invention provides a receipt log report query management method, device, equipment and storage medium. The present invention first obtains logistics receipt log data and performs multi-dimensional data modeling on it to form a multi-dimensional data model, so as to quickly match the corresponding dimension data through key information during query, avoiding traversing the database, thereby improving the query speed. Then, obtain the user's query request, and use the pre-constructed user query preference model or query parsing technology based on semantic understanding to query data in the multi-dimensional data model to obtain the original data, enhancing the intelligence and accuracy of the query. Subsequently, analyze the original data according to the preset in-depth analysis rules to obtain in-depth analysis data, which helps users comprehensively understand the business status and optimize their work. Finally, perform visualization processing on the original data and the in-depth analysis data to generate visualization charts, and output the original data, in-depth analysis data and visualization charts to the user together, enabling the user to intuitively understand the data and better perform data insight.

[0034] In the description of the present invention, the claims and the above-mentioned drawings, the terms "first", "second", "third", "fourth", etc. (if any) are used to distinguish similar objects and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the term "comprising" or "having" and any variations 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 the method for querying and managing the receipt log report in the embodiments of the present invention includes:

[0036] S101. Obtain logistics receipt log data, perform multi-dimensional data modeling based on the logistics receipt log data to obtain a multi-dimensional data model;

[0037] S102. Obtain a user query request, and according to the user query request, query the data in the multi-dimensional data model by using a pre-constructed user query preference model or query parsing technology based on semantic understanding to obtain raw data;

[0038] S103. Establish in-depth analysis rules, and perform in-depth analysis on the raw data according to the in-depth analysis rules to obtain in-depth analysis data;

[0039] S104. Perform visualization processing on the raw data and the in-depth analysis data to obtain a visualization chart, and output the raw data, the in-depth analysis data, and the visualization chart to the user.

[0040] In this embodiment, by first performing comprehensive multi-dimensional modeling on the logistics receipt log data, the obtained multi-dimensional data model not only covers basic information such as traditional order numbers, receipt dates, and recipients, but also incorporates data from multiple dimensions such as logistics outlets, couriers, transportation routes, and cargo types. By establishing such a multi-dimensional data model, a rich data foundation can be provided for subsequent intelligent queries. For example, logistics outlets are divided by region, couriers are classified according to their affiliated teams and business capabilities, transportation routes are marked according to distance and transportation duration, and cargo types are distinguished according to weight, volume, and value, etc. In this way, when querying, combined queries can be performed from multiple dimensions according to different business requirements.

[0041] Based on the established multi-dimensional data model, the system can make the query results more in line with user needs and improve query efficiency by adopting a user query preference model and query parsing technology based on semantic understanding for different query contents. The improvement of query efficiency can reduce the query instructions issued by users, thereby reducing the overall response time of the system.

[0042] After obtaining the original data, the present invention conducts further in-depth analysis on the original data with the goal of providing users with valuable insights and suggestions. According to business needs, it can also provide an intelligent early warning function for users by combining real-time data and historical data based on the characteristics and laws of the logistics business. For example, if the abnormal signature rate in a certain area continues to rise, the system can issue an early warning in a timely manner to remind logistics enterprise managers to take corresponding measures, such as increasing delivery personnel, optimizing the delivery process, etc.

[0043] Finally, data visualization technology is adopted to present the query results to users in an intuitive and easy-to-understand chart form. Specifically, it can support various chart types, such as bar charts, line charts, pie charts, maps, etc. When users query the signature volume in different regions, the system can intuitively display the distribution of signature volumes in each region in the form of a map, and different regions are distinguished by different colors or annotation sizes to represent the amount of signature volume; when querying the change in signature success rate within a certain period of time, a line chart is used to clearly show the fluctuation trend of the success rate.

[0044] Please refer to Figure 2 , the second embodiment of the signature log report query management method in the embodiment of the present invention includes:

[0045] S201. Obtain logistics signature log data, and preprocess the logistics signature log data to obtain preprocessed data;

[0046] S202. Establish dimension design rules, and establish multiple dimension tables according to the preprocessed data;

[0047] S203. Associate multiple dimension tables, and establish a multi-dimensional data model according to the associated multiple dimension tables;

[0048] S204. Perform distributed storage and index construction on multiple dimension tables in the multi-dimensional data model.

[0049] By preprocessing the logistics signature log data, such as removing duplicate and incorrect records, formatting date fields, handling missing values, unifying data formats, etc., it can avoid errors in subsequent data utilization and improve accuracy.

[0050] In dimensional design, tables can be designed to be established according to different dimensions to classify and store the preprocessed data. For example, data in the order dimension, data in the recipient dimension, data in the courier dimension, data in the goods type dimension, data in the network point dimension, etc. After the table design for the corresponding dimension is completed, the ETL tool can be used to load the preprocessed data into the dimension table. By classifying and storing the data, it is possible to reduce the traversal of all data during querying and improve the query efficiency.

[0051] In this embodiment, by associating multiple dimension tables, the scattered data can be integrated to form a comprehensive and structured multi-dimensional data model. When querying multiple types of data, it can be provided through the multi-dimensional data model at once, improving the query response speed.

[0052] Preferably, this embodiment also performs distributed storage (such as Redis) and index construction on multiple dimension tables in the multi-dimensional data model. Distributed storage can cache frequently used data, reduce the database query pressure, and improve the system response speed. During querying, it can quickly locate the relevant data storage nodes according to the query conditions and quickly retrieve the data that meets the conditions through the index, thus significantly shortening the query time. For example, for the case of querying by date, a date index is established, and for the case of querying by region, a region index is established, etc., so that the query can directly obtain data from the index without traversing the entire database.

[0053] Please refer to Figure 3 , the third embodiment of the query management method for the signature log report in the embodiment of the present invention includes:

[0054] S301. Obtain the user query request and judge the content of the user query request;

[0055] S302. If the content of the user query request is a keyword or a conditional word, use the pre-constructed user query preference model to query the data in the multi-dimensional data model according to the keyword or the conditional word to obtain the original data;

[0056] S303. If the content of the user query request is a natural language query statement, use the query parsing technology based on semantic understanding to query the data in the multi-dimensional data model according to the natural language query statement to obtain the original data.

[0057] In this embodiment, when judging the content of the user query request, the type can be judged based on conditions such as the number of words in the query content and whether it is a complete sentence;

[0058] When the content of the user's query request is a keyword or conditional term, the system can automatically perform intelligent association and recommendation according to the user query preference model. For example, if a user often queries the signing status in a specific time period in a certain region, when the user enters the region name again, the system will automatically pop up relevant time range options for the user to select, greatly improving the query efficiency.

[0059] When the user inputs a natural language query statement, the system can accurately understand the user's query intention based on the query parsing technology of semantic understanding and convert it into a corresponding database query statement. For example, when the user inputs "the signing success rate in East China last month", the system can identify the time range corresponding to "last month", the region range corresponding to "East China", and the query metric corresponding to "signing success rate", and perform an accurate query in the database.

[0060] Please refer to Figure 4 , the fourth embodiment of the signing log report query management method in the embodiments of the present invention includes:

[0061] S401. Obtain the user's historical query records and behavior patterns to construct a training set;

[0062] S402. Use the training set to train a machine learning algorithm to obtain a user query preference model;

[0063] S403. Use the user query preference model to query the data in the multi-dimensional data model according to keywords or conditional terms to obtain the original data.

[0064] Specifically, the user's past query content can be obtained from the database or log file, including query keywords, phrases or sentences, as well as information such as the time and frequency of the query; and the operation behavior of the user after the query can be obtained, such as which search results are clicked, the stay time on the result page, whether filtering or sorting operations are performed, etc., to understand the user's preferences and needs. Then, after preprocessing the data, it is organized into an input format suitable for the machine learning algorithm, usually including feature vectors and corresponding labels. For example, the user's query keywords and behavior features can be used as input features, and the user's preference category or query intention can be used as the label.

[0065] During training, machine learning algorithms such as decision trees, support vector machines, and neural networks in supervised learning algorithms can be used for training. The obtained user query preference model is then evaluated by methods such as cross-validation and holdout validation, and evaluation metrics such as accuracy, recall, and F1 value are used to measure the performance of the model. The model is optimized according to the evaluation results, such as adjusting the hyperparameters of the algorithm, increasing the amount of training data, etc., to improve the accuracy and generalization ability of the model.

[0066] Query the multi-dimensional data model using the user query preference model. The model maps keywords or conditional terms to corresponding dimensions and data ranges according to the user's preferences and query intentions, so as to quickly locate the data related to the query in the multi-dimensional data model. This embodiment of the personalized query method based on user behavior not only reduces the time for users to retrieve in complex data, but also provides query results that better meet the user's needs, enhancing the user experience.

[0067] Please refer to Figure 5 , the fifth embodiment of the signed receipt log report query management method in the embodiments of the present invention includes:

[0068] S501. Establish in-depth analysis rules and set analysis schemes for different types of users respectively;

[0069] S502. Obtain user information and judge the user type, and conduct in-depth analysis on the original data according to the user type and in-depth analysis rules;

[0070] S503. For courier users, calculate the individual signing efficiency, individual signing success rate and comparison with other couriers according to the original data, and generate improvement suggestions according to the original data;

[0071] S504. For management users, calculate the regional signing efficiency, regional signing success rate, signing information of all couriers and comparison with other regions according to the original data, and generate improvement suggestions according to the original data.

[0072] In this embodiment, for each user type, it is necessary to clarify the analysis objectives and key points. For example, for courier users, the analysis objective may be to evaluate the individual signing efficiency and success rate; for management users, the analysis objective may be to evaluate the regional signing efficiency and success rate, and compare the performance of different regions.

[0073] After setting the analysis scheme, the system obtains the basic information of the user, such as user ID, user name, user role, etc., judges the user type from the basic information, and then analyzes and calculates the extracted original data according to the definitions and index systems in the in-depth analysis rules.

[0074] For courier users, count the number of packages signed by the courier within a certain period of time, divide it by the working hours or working days to get the average number of packages signed per day, and thus the individual signing efficiency can be further obtained; count the number of packages successfully signed by the courier, divide it by the total number of packages delivered, and the signing success rate can be obtained. According to the calculation results and comparison, the system will combine business knowledge and experience to generate targeted improvement suggestions. For example, if a courier has a low signing efficiency, it is recommended to optimize the delivery route; if the signing success rate is low, it is recommended to strengthen communication and appointment with the recipient.

[0075] For management users, the system calculates the regional signing efficiency, regional signing success rate, signing information of all couriers, and compares the signing efficiency and success rate of this region with those of other regions to analyze the differences, advantages, and disadvantages between regions. Finally, based on the calculation results and comparison, combined with business knowledge and experience, targeted improvement suggestions are generated. For example, if the signing efficiency of a certain region is low, it is recommended to optimize the distribution route planning within the region; if the signing success rate is low, it is recommended to strengthen the training of couriers and the monitoring of service quality.

[0076] Please refer to Figure 6 , the sixth embodiment of the signing log report query management method in the embodiments of the present invention includes:

[0077] S601. For courier users, calculate the individual signing efficiency, individual signing success rate, and comparison with other couriers based on the original data;

[0078] S602. Construct an efficiency analysis model and calculate the key factors affecting the signing efficiency of couriers based on the original data;

[0079] S603. Generate improvement suggestions based on the key factors and the original data, and the improvement suggestions include time planning suggestions and distribution route suggestions.

[0080] In this embodiment, an efficiency analysis model is constructed by selecting appropriate statistical or machine learning methods, such as regression analysis, decision tree, random forest, etc., to quantify the influence degree of each factor (such as the size and complexity of the distribution area, package weight and volume, transportation distance, customer signing habits, distribution volume, etc.) on the signing efficiency, so as to obtain the key factors affecting the signing efficiency of couriers.

[0081] After obtaining the key factors, the system can further analyze the results and provide reasonable time planning suggestions for couriers. For example, if the signing rate of customers in a certain region is usually high in the morning, it is recommended that couriers give priority to the morning distribution in this region; if the package volume is large during certain time periods, it is recommended to arrange working hours reasonably to avoid over-fatigue.

[0082] In addition, it can also combine the geographical information of the distribution area and the package distribution situation to plan the optimal distribution route for couriers. For example, using the shortest path algorithm or considering traffic congestion, generate a distribution route that can reduce transportation time and distance and improve distribution efficiency.

[0083] Please refer to Figure 7 , the seventh embodiment of the signing log report query management method in the embodiments of the present invention includes:

[0084] S701. Visualize the original data and the in-depth analysis data using a map visualization library or a chart library to obtain a visualization chart;

[0085] S702. Mark the content in the visualization chart respectively, and bind the marked content to the original data or the in-depth analysis data;

[0086] S703. Set paging loading for the original data, the in-depth analysis data, and the visualization chart, and output the original data, the in-depth analysis data, and the visualization chart to the user.

[0087] In this embodiment, the system can also provide an interactive data visualization interface, and the user can perform operations such as zooming, filtering, and sorting on the chart according to their own needs. For example, the user can click on a certain area on the map to view more detailed signing data in that area; select a specific bar in the bar chart to view the specific details of the data represented by that bar, etc.

[0088] Furthermore, when querying data, use a paging query algorithm to accurately obtain corresponding data from the database according to the amount of data per page and the current page number set by the user, so as to avoid system lag caused by loading a large amount of data at one time.

[0089] The signing log report query management method in the embodiment of the present invention has been described above. Next, the signing log report query management device in the embodiment of the present invention will be described. Please refer to Figure 8 , an embodiment of the signing log report query management device in the embodiment of the present invention includes:

[0090] A construction module 10, configured to obtain logistics signing log data, and perform multi-dimensional data modeling according to the logistics signing log data to obtain a multi-dimensional data model;

[0091] A query module 20, configured to obtain a user query request, and query the data in the multi-dimensional data model according to the user query request by using a pre-constructed user query preference model or a query parsing technology based on semantic understanding to obtain the original data;

[0092] An analysis module 30, configured to establish in-depth analysis rules, and perform in-depth analysis on the original data according to the in-depth analysis rules to obtain in-depth analysis data;

[0093] A visualization module 40, configured to perform visualization processing on the original data and the in-depth analysis data to obtain a visualization chart, and output the original data, the in-depth analysis data, and the visualization chart to the user.

[0094] Please refer to Figure 9 , an embodiment of the signing log report query management device in the embodiment of the present invention includes:

[0095] The building block 10 is used to obtain the logistics receipt log data, perform multi-dimensional data modeling based on the logistics receipt log data to obtain a multi-dimensional data model;

[0096] The query module 20 is used to obtain a user query request, and according to the user query request, query the data in the multi-dimensional data model by using a pre-constructed user query preference model or query parsing technology based on semantic understanding to obtain the original data;

[0097] The analysis module 30 is used to establish in-depth analysis rules, and perform in-depth analysis on the original data according to the in-depth analysis rules to obtain in-depth analysis data;

[0098] The visualization module 40 is used to perform visualization processing on the original data and the in-depth analysis data, obtain a visualization chart, and output the original data, the in-depth analysis data, and the visualization chart to the user;

[0099] In this embodiment, the building block 10 includes:

[0100] The preprocessing sub-module 11 is used to obtain the logistics receipt log data and preprocess the logistics receipt log data to obtain preprocessed data;

[0101] The establishment sub-module 12 is used to establish dimension design rules and establish multiple dimension tables according to the preprocessed data;

[0102] The association sub-module 13 is used to associate multiple dimension tables and establish a multi-dimensional data model according to the associated multiple dimension tables;

[0103] The storage sub-module 14 is used to perform distributed storage and index construction on the multiple dimension tables in the multi-dimensional data model;

[0104] In this embodiment, the query module 20 includes:

[0105] The judgment sub-module 21 is used to obtain a user query request and judge the content of the user query request;

[0106] The first query sub-module 22 is used to, if the content of the user query request is a keyword or a conditional word, query the data in the multi-dimensional data model by using a pre-constructed user query preference model to obtain the original data;

[0107] The second query sub-module 23 is used to, if the content of the user query request is a natural language query statement, query the data in the multi-dimensional data model by using query parsing technology based on semantic understanding to obtain the original data;

[0108] In this embodiment, the first query sub-module 22 includes:

[0109] A building unit 221, configured to obtain the user's historical query records and behavior patterns to build a training set;

[0110] A training unit 222, configured to train a machine learning algorithm using the training set to obtain a user query preference model;

[0111] A query unit 223, configured to query data in a multi-dimensional data model according to keywords or conditional words using the user query preference model to obtain raw data;

[0112] In this embodiment, the analysis module 30 includes:

[0113] A setting sub-module 31, configured to establish in-depth analysis rules and set analysis schemes for different types of users respectively;

[0114] An in-depth analysis sub-module 32, configured to obtain user information and determine the user type, and perform in-depth analysis on the raw data according to the user type and in-depth analysis rules;

[0115] A first generation sub-module 33, configured to, for a courier user, calculate the individual signing efficiency, individual signing success rate, and comparison with other couriers according to the raw data, and generate improvement suggestions according to the raw data;

[0116] A second generation sub-module 34, configured to, for a management user, calculate the regional signing efficiency, regional signing success rate, signing information of all couriers, and comparison with other regions according to the raw data, and generate improvement suggestions according to the raw data;

[0117] In this embodiment, the first generation sub-module 33 includes:

[0118] A first calculation unit 331, configured to, for a courier user, calculate the individual signing efficiency, individual signing success rate, and comparison with other couriers according to the raw data;

[0119] A second calculation unit 332, configured to build an efficiency analysis model and calculate key factors affecting the courier's signing efficiency according to the raw data;

[0120] A generation unit 333, configured to generate improvement suggestions according to the key factors and the raw data, where the improvement suggestions include time planning suggestions and delivery route suggestions;

[0121] In this embodiment, the visualization module 40 includes:

[0122] A visualization unit 41, configured to perform visualization processing on the raw data and in-depth analysis data using a map visualization library or a chart library to obtain a visualization chart;

[0123] A marking unit 42 is used to mark the content in the visualization chart respectively and bind the marked content to the original data or in-depth analysis data;

[0124] An output unit 43 is used to perform paging loading settings on the original data, in-depth analysis data, and visualization chart, and output the original data, in-depth analysis data, and visualization chart to the user.

[0125] The signed receipt log report query and management device of the present invention first collects logistics signed receipt log data and constructs a multi-dimensional data model, and through pre-computation and distributed storage optimization, replaces the traditional full-library traversal, significantly improving the query efficiency; then based on the user's query request, using intelligent semantic parsing technology or a user preference model trained by historical behavior, it accurately matches the associated data in the multi-dimensional model to ensure that the query results have both accuracy and scenario adaptability; subsequently, it analyzes the original data through preset in-depth analysis rules to generate valuable analysis results and puts forward optimization suggestions or risk warnings; finally, the structured data and in-depth analysis conclusions are presented through visualization charts (such as heat maps, trend curves) to support users in optimizing business strategies.

[0126] The above is a detailed description of the signed receipt log report query and management device in the embodiments of the present invention from the perspective of modular functional entities. The following is a detailed description of the signed receipt log report query and management device in the embodiments of the present invention from the perspective of hardware processing.

[0127] Figure 10 FIG. is a schematic structural diagram of a signed receipt log report query and management device provided in an embodiment of the present invention. The signed receipt log report query and management device 900 may vary greatly due to configuration or performance, and may include one or more processors (central processing units, CPU) 910 (for example, one or more processors) and a memory 920, and one or more storage media 930 (for example, one or more mass storage devices) for storing application programs 933 or data 932. Among them, the memory 920 and the storage media 930 may be transient storage or persistent storage. The program stored in the storage media 930 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the signed receipt log report query and management device 900. Further, the processor 910 may be configured to communicate with the storage media 930 and execute a series of instruction operations in the storage media 930 on the signed receipt log report query and management device 900 to implement the steps of the signed receipt log report query and management method provided in the above method embodiments.

[0128] The signing log report query management device 900 may further include one or more power supplies 940, one or more wired or wireless network interfaces 950, one or more input / output interfaces 960, and / or, one or more operating systems 931, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art can understand that Figure 10 The structure of the signing log report query management device shown does not constitute a limitation on the signing log report query management device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0129] The present invention also provides a computer-readable storage medium, which 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 signing log report query management method.

[0130] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described devices or apparatuses can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0131] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present 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 the various embodiments of the present invention. The foregoing storage medium includes: USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs, etc., which can store program codes.

[0132] It can be understood that for those of ordinary skill in the art, equivalent substitutions or changes can be made according to the technical solution of the present invention and its inventive concept, and all such changes or substitutions should fall within the protection scope of the claims appended to the present invention.

Claims

1. A method for querying and managing a receipt log report, characterized in that, It includes the following steps: Obtain logistics receipt log data, perform multi-dimensional data modeling based on the logistics receipt log data to obtain a multi-dimensional data model; Obtain a user query request, and according to the user query request, query the data in the multi-dimensional data model by using a pre-constructed user query preference model or a query parsing technique based on semantic understanding to obtain the original data; Establish in-depth analysis rules, and perform in-depth analysis on the original data according to the in-depth analysis rules to obtain in-depth analysis data; Perform visualization processing on the original data and the in-depth analysis data to obtain a visualization chart, and output the original data, the in-depth analysis data, and the visualization chart to the user.

2. The query management method for the signed receipt log report according to claim 1, wherein The obtaining of the logistics receipt log data, performing multi-dimensional data modeling based on the logistics receipt log data to obtain a multi-dimensional data model specifically includes: Obtain logistics receipt log data, and perform preprocessing on the logistics receipt log data to obtain preprocessed data; Establish dimension design rules, and establish multiple dimension tables according to the preprocessed data; Associate the multiple dimension tables, and establish a multi-dimensional data model according to the associated multiple dimension tables; Perform distributed storage and index construction on the multiple dimension tables in the multi-dimensional data model.

3. The method for querying and managing the signed receipt log report according to claim 1, wherein, The obtaining of the user query request, and according to the user query request, querying the data in the multi-dimensional data model by using a pre-constructed user query preference model or a query parsing technique based on semantic understanding to obtain the original data specifically includes: Obtain a user query request, and judge the content of the user query request; If the content of the user query request is a keyword or a conditional word, use the pre-constructed user query preference model to query the data in the multi-dimensional data model according to the keyword or the conditional word to obtain the original data; If the content of the user query request is a natural language query statement, use a query parsing technique based on semantic understanding to query the data in the multi-dimensional data model according to the natural language query statement to obtain the original data.

4. The query management method for the signed receipt log report according to claim 3, characterized in that, The if the content of the user query request is a keyword or a conditional word, using the pre-constructed user query preference model to query the data in the multi-dimensional data model according to the keyword or the conditional word to obtain the original data specifically includes: Obtain the historical query records and behavior patterns of the user to construct a training set; Use the training set to train a machine learning algorithm to obtain a user query preference model; Use the user query preference model to query the data in the multi-dimensional data model according to the keyword or the conditional word to obtain the original data.

5. The method for querying and managing the signature log report according to claim 1, wherein The establishing of the in-depth analysis rules, and performing in-depth analysis on the original data according to the in-depth analysis rules to obtain the in-depth analysis data specifically includes: Establish in-depth analysis rules, and set analysis schemes for different types of users respectively; Obtain user information and judge the user type, and perform in-depth analysis on the original data according to the user type and the in-depth analysis rules; For courier users, calculate the individual receipt efficiency, individual receipt success rate, and comparison with other couriers according to the original data, and generate improvement suggestions according to the original data; For management users, calculate the regional signing efficiency, regional signing success rate, signing information of all couriers, and comparison with other regions based on the original data, and generate improvement suggestions according to the original data.

6. The management method for querying the receipt log report according to claim 5, characterized in that, For courier users, calculate the individual signing efficiency, individual signing success rate, and comparison with other couriers based on the original data, and generate improvement suggestions according to the original data. Specifically, it includes: For courier users, calculate the individual signing efficiency, individual signing success rate, and comparison with other couriers based on the original data; Construct an efficiency analysis model and calculate the key factors affecting the signing efficiency of couriers based on the original data; Generate improvement suggestions according to the key factors and the original data. The improvement suggestions include time planning suggestions and delivery route suggestions.

7. The inquiry management method for the signed receipt log report according to claim 1, wherein, Visualize the original data and in-depth analysis data to obtain visual charts, and output the original data, in-depth analysis data, and visual charts to the user. Specifically, it includes: Use a map visualization library or a chart library to visualize the original data and in-depth analysis data to obtain visual charts; Mark the content in the visual charts respectively and bind the marked content to the original data or in-depth analysis data; Set paging loading for the original data, in-depth analysis data, and visual charts, and output the original data, in-depth analysis data, and visual charts to the user.

8. A receipt log report query and management device, characterized in that, It includes: A construction module for obtaining logistics signing log data and performing multi-dimensional data modeling based on the logistics signing log data to obtain a multi-dimensional data model; A query module for obtaining a user query request and querying the data in the multi-dimensional data model according to the user query request using a pre-constructed user query preference model or query parsing technology based on semantic understanding to obtain the original data; An analysis module for establishing in-depth analysis rules and performing in-depth analysis on the original data according to the in-depth analysis rules to obtain in-depth analysis data; A visualization module for visualizing the original data and in-depth analysis data to obtain visual charts, and outputting the original data, in-depth analysis data, and visual charts to the user.

9. A receipt log report query and management device, characterized in that, It includes a memory and at least one processor, and computer-readable instructions are stored in the memory; The at least one processor calls the computer-readable instructions in the memory to execute each step of the signing log report query management method described in any one of claims 1-7.

10. A computer-readable storage medium, on which computer-readable instructions are stored, characterized in that, When the computer-readable instructions are executed by the processor, each step of the signing log report query management method described in any one of claims 1-7 is implemented.

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