Intelligent logistics report generation method and system based on business data

Abstract

The invention discloses a logistics report intelligent generation method and system based on business data, and relates to the technical field of data processing, and the method comprises the steps: obtaining logistics system data, obtaining a logistics data topological structure network based on topological structure analysis according to the logistics system data, and obtaining a logistics data topological structure network based on logistics report data item information and the logistics report data. And filling the logistics report to generate the logistics report. According to the method, the data attributes of different logistics data are analyzed, the data processing efficiency is improved, the basic data in the logistics report is arranged through the data attribute evaluation index, important data of the logistics report is highlighted, the logistics data expansion item information is screened, various logistics data expansion items are avoided, and the data processing efficiency is improved. Through the report expansion item period difference coefficient, the abnormal expansion item in the logistics report is marked, the reading efficiency is improved, the time cost is reduced, and the overall operation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method and system for intelligently generating logistics reports based on business data. Background Art

[0002] Reports are an important part of information management systems. As enterprise-level applications, reports mainly exist in the form of browser and server architecture (i.e., B / S architecture). Deploying an application can be accessed by multiple people. When people in different roles access reports, there will be permission control, so that different people see different report results. For the logistics industry, logistics reports integrate data such as transportation, warehousing, loading and unloading, handling, packaging, circulation processing, distribution and information platforms, and generally have obvious regional attributes. Therefore, there are many types of reports, frequent changes, and high timeliness. Reports need to be generated in a timely and accurate manner. In the development process of data application systems, report engines came into being. Based on the original data, they can define the format and algorithm of the report, automatically perform calculations according to the defined algorithms, output the calculated results, and then display the content of the report according to the defined report format.

[0003] At present, there are still problems in the generation of logistics reports, such as the inability to accurately analyze logistics system data, the inability to arrange different logistics system data according to report requirements, the inability to select appropriate data extension items according to the demand type of logistics report, the inability to avoid reading difficulties caused by complex logistics report data, and the inability to accurately identify abnormal items in logistics reports based on logistics system data. Summary of the invention

[0004] In order to solve the above technical problems, a method and system for intelligently generating logistics reports based on business data are provided. This technical solution solves the problems raised in the above background technology, namely, the inability to accurately analyze logistics system data, the inability to arrange different logistics system data according to report requirements, the inability to select appropriate data extension items according to the demand type of logistics report, the inability to avoid reading difficulties caused by complex logistics report data, and the inability to accurately identify abnormal items in logistics reports based on logistics system data.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A method for intelligently generating logistics reports based on business data, comprising:

[0007] Acquire logistics system data, wherein the logistics system includes a warehouse management system, a transportation management system, and an order management system;

[0008] According to the logistics system data, based on the topological structure analysis, the logistics data topological structure network is obtained;

[0009] Acquire user interaction information, the user interaction information including user identity information and report requirement information, the report requirement is divided into daily report requirement, weekly report requirement and monthly report requirement;

[0010] According to the user interaction information, the basic information of the logistics report is arranged and generated, and the basic item information of the logistics report is obtained, and each type of logistics system data in the basic item information of the logistics report is arranged according to the data attribute sorting information;

[0011] According to the logistics system data and based on the logistics report analysis requirements, obtain the logistics report extension item information;

[0012] Obtain logistics report data item information based on logistics report extension item information and logistics report basic item information;

[0013] Based on the report requirement information, filter the logistics system data and obtain the logistics report data;

[0014] Fill in the logistics report based on the logistics report data item information and logistics report data to generate the logistics report.

[0015] Preferably, the obtaining of the logistics data topology network based on the logistics system data and the topology structure analysis specifically includes:

[0016] According to the logistics system data, based on named entity recognition, the logistics system data attribute information is obtained, wherein the logistics system data attributes include logistics transportation time, logistics transportation mode, logistics order time and logistics warehousing information;

[0017] Analyze the logical relationship between data attributes of different logistics systems to obtain logistics data topology information;

[0018] According to the logistics data topology structure information, based on the topology network construction, a logistics data topology structure network is obtained, wherein the logistics data topology structure network includes a plurality of logistics data attribute nodes;

[0019] Among them, for any logistics data attribute node in the logistics data topology structure network, the logistics data attribute node that points to the node in logical order is the upper node of the node, and the logistics data attribute node that the node points to in logical order is the lower node.

[0020] Preferably, the generating of arranging the basic information of the logistics report according to the user interaction information and obtaining the basic item information of the logistics report specifically includes:

[0021] Based on system function analysis, the logistics system data is classified to obtain warehouse management system data, transportation management system data and order management system data;

[0022] According to user interaction information, weights are set for different categories of logistics system data;

[0023] Based on the weight of logistics system data and the logistics data topological structure network, obtain the data attribute evaluation index;

[0024] Sort the logistics data attributes in descending order according to the data attribute evaluation index to obtain data attribute sorting information;

[0025] Based on the data attribute sorting information, the basic information of the logistics report is arranged and generated to obtain the basic item information of the logistics report;

[0026] The calculation formula of the data attribute evaluation index is:

[0027]

[0028] In the formula, Q(x, τ) represents the data attribute evaluation index of the logistics data attribute represented by the x-th logistics data attribute node, τ is the user identity recognition coefficient, if τ = 1, the weight ratio of the warehouse management system data, transportation management system data and order management system data is 1:2:1, if τ = 2, the weight ratio of the warehouse management system data, transportation management system data and order management system data is 2:1:1, if τ = 3, the weight ratio of the warehouse management system data, transportation management system data and order management system data is 1:1:2, α x is the logistics data weight of the x-th logistics data attribute node, α i is the logistics data weight of the ith upper node of the xth logistics data attribute node, w i is the number of intermediate nodes between the ith upper node of the xth logistics data attribute node and the xth logistics data attribute node, k i is the total number of adjacent logistics data attribute nodes pointed to by the ith upper node of the xth logistics data attribute node in logical order, α j is the logistics data weight of the jth subordinate node of the xth logistics data attribute node, w j is the number of intermediate nodes between the jth subordinate node of the xth logistics data attribute node and the xth logistics data attribute node, k j is the total number of logistics data attribute nodes that point to the jth subordinate node of the xth logistics data attribute node in logical order among the adjacent nodes of the jth subordinate node of the xth logistics data attribute node, n is the total number of upper nodes of the xth logistics data attribute node, and m is the total number of subordinate nodes of the xth logistics data attribute node.

[0029] Preferably, the obtaining of logistics report extension item information based on logistics system data and logistics report analysis requirements specifically includes:

[0030] According to the logistics system data, based on the logistics report analysis requirements, the logistics data extension item information is obtained, and the logistics data extension item information includes inventory turnover rate, order completion rate, return rate, on-time delivery rate, transportation rate and profit rate;

[0031] Based on the logistics data extension item information, obtain data extension related information corresponding to each logistics data extension item, wherein the data extension related information represents the logistics data attributes required for the logistics data extension item calculation;

[0032] According to the logistics data extension item information, data extension related information and data attribute evaluation index, obtain the data extension related index;

[0033] According to the data expansion related index, the logistics data expansion item information is filtered to obtain the logistics report expansion item information;

[0034] Among them, if the data expansion related index E(y, τ) ≤ 0.08, the logistics data expansion item does not meet the logistics report requirements. If the data expansion related index E(y, τ)> 0.08, the logistics data expansion item is available. The calculation formula of the data expansion related index is:

[0035]

[0036] Where E(y, τ) is the data extension related index of the y-th logistics data extension item, Q(b) is the data attribute evaluation index of the b-th logistics data required by the y-th logistics data extension item, τ is the user identity recognition coefficient, if τ = 1, then Q(c) is the data attribute evaluation index of the c-th logistics data in the transportation management system data, s is the total number of logistics data attribute types in the transportation management system data, if τ = 2, then Q(c) is the data attribute evaluation index of the c-th logistics data in the warehouse management system data, s is the total number of logistics data attribute types in the warehouse management system data, if τ = 3, then Q(c) is the data attribute evaluation index of the c-th logistics data in the order management system data, s is the total number of logistics data attribute types in the order management system data, H is the total number of logistics data attribute types required by the y-th logistics data extension item, and δ is the number of occurrences of the b-th logistics data in the calculation process of the y-th logistics data extension item.

[0037] Preferably, the step of screening the logistics system data based on the report requirement information to obtain the logistics report data specifically includes:

[0038] According to the report requirement information, obtain the report generation cycle information;

[0039] According to the logistics system data, based on data feature recognition, obtain data time tag information;

[0040] According to the user interaction information, obtain the user report requirement instruction time information;

[0041] Taking the user report demand instruction time information as the starting point, and the report generation cycle information as the benchmark, the logistics system data is classified according to the data time tag information to obtain the logistics system data group;

[0042] The logistics system data group represents the logistics system data within a report generation cycle;

[0043] Based on the data time tag information, the logistics system data groups are numbered, and the logistics system data group within a report generation cycle from the user report demand instruction time is taken as the first logistics system data group;

[0044] The first logistics system data set is used as logistics report data.

[0045] Preferably, the step of filling the logistics report according to the logistics report data item information and the logistics report data to generate the logistics report specifically includes:

[0046] According to the logistics report data item information, obtain the logistics report extension item information and logistics report basic item information;

[0047] Based on the logistics report data, fill in the basic items of the logistics report;

[0048] Based on the logistics report data and logistics report extension information, obtain the logistics report extension item calculation data;

[0049] Based on the calculation data of the logistics report extension items, fill in the logistics report extension items;

[0050] Obtaining logistics system data group;

[0051] Calculate data based on the logistics system data group and logistics report extension items to obtain the report extension item cycle difference coefficient;

[0052] According to the cycle difference coefficient of the report extension item, determine whether the calculated data of the logistics report extension item is abnormal. If not, mark the calculated data of the logistics report extension item as normal. If so, mark the calculated data of the logistics report extension item as abnormal, record the cycle difference coefficient of the report extension item, and obtain the logistics report evaluation item information;

[0053] Fill in the logistics report according to the evaluation item information of the logistics report to generate the logistics report;

[0054] Among them, if the report extension item cycle difference coefficient R(y)≤0.82, the logistics report extension item calculation data is abnormal; if R(y)>0.82, the logistics report extension item calculation data is normal. The calculation formula of the report extension item cycle difference coefficient is:

[0055]

[0056] Where R(y) is the period difference coefficient of the report expansion item of the y-th logistics data expansion item, f(y, D1) represents the calculation data of the y-th logistics data expansion item with the first logistics system data group as input, and f(y, D g ) represents the calculation data of the yth logistics data extension item with the gth logistics system data group as input, and T is the total number of logistics system data groups.

[0057] Furthermore, a logistics report intelligent generation system based on business data is proposed to implement the above generation method, including:

[0058] A main control module, the main control module is used to screen the logistics data expansion item information according to the data expansion related index, obtain the logistics report expansion item information, determine whether the logistics report expansion item calculation data is abnormal according to the report expansion item period difference coefficient, analyze the logical relationship between different logistics system data attributes, obtain the logistics data topology structure information, and obtain the logistics data topology structure network based on the topological network construction according to the logistics data topology structure information, set weights for logistics system data of different categories according to user interaction information, obtain the logistics data expansion item information according to the logistics system data and the logistics report analysis requirements, fill the logistics report according to the logistics report data item information and the logistics report data, and generate the logistics report;

[0059] An information acquisition module, which is used to acquire logistics system data, warehouse management system data, transportation management system data and order management system data, and acquires logistics system data attribute information based on named entity recognition according to the logistics system data, acquires user interaction information, user identity information and report requirement information, and acquires report generation cycle information according to the report requirement information;

[0060] An evaluation module, wherein the evaluation module is used to obtain a data attribute evaluation index based on the weight of the logistics system data and the logistics data topological structure network, sort the logistics data attributes in descending order according to the data attribute evaluation index, obtain data attribute sorting information, obtain data extension related information corresponding to each logistics data extension item based on the logistics data extension item information, obtain a data extension related index based on the logistics data extension item information, the data extension related information and the data attribute evaluation index, calculate data based on the logistics system data group and the logistics report extension item, and obtain a report extension item cycle difference coefficient;

[0061] The display module interacts with the main control module and is used to display basic item information of logistics data, extended item information of logistics data, report generation cycle information and logistics reports.

[0062] Optionally, the main control module specifically includes:

[0063] A control unit, the control unit is used to analyze the logical relationship between different logistics system data attributes, obtain logistics data topology structure information, and obtain the logistics data topology structure network based on the topology network construction according to the logistics data topology structure information, and set weights for logistics system data of different categories according to user interaction information, and obtain logistics data extension item information based on the logistics system data and logistics report analysis requirements, and fill the logistics report according to the logistics report data item information and the logistics report data, and generate the logistics report;

[0064] An information receiving unit, which interacts with the information acquisition module and the evaluation module to receive data and transmit it to the judgment unit;

[0065] The judgment unit is used to screen the logistics data expansion item information according to the data expansion related index, obtain the logistics report expansion item information, and judge whether the logistics report expansion item calculation data is abnormal according to the report expansion item period difference coefficient.

[0066] Optionally, the information acquisition module specifically includes:

[0067] A first acquisition unit, the first acquisition unit is used to acquire logistics system data, warehouse management system data, transportation management system data and order management system data, and acquire logistics system data attribute information based on named entity recognition according to the logistics system data;

[0068] The second acquisition unit is used to acquire user interaction information, user identity information and report requirement information, and acquire report generation cycle information according to the report requirement information.

[0069] Optionally, the evaluation module specifically includes:

[0070] A data attribute evaluation unit, the data attribute evaluation unit is used to obtain a data attribute evaluation index based on the weight of the logistics system data and the logistics data topological structure network, sort the logistics data attributes in descending order according to the data attribute evaluation index, and obtain data attribute sorting information;

[0071] A data expansion evaluation unit, the data expansion evaluation unit is used to obtain data expansion related information corresponding to each logistics data expansion item based on the logistics data expansion item information, and obtain a data expansion related index according to the logistics data expansion item information, the data expansion related information and the data attribute evaluation index;

[0072] The cycle difference evaluation unit is used to calculate data based on the logistics system data group and the logistics report extension items to obtain the cycle difference coefficient of the report extension item.

[0073] Compared with the prior art, the present invention has the following beneficial effects:

[0074] The present invention proposes a method and system for intelligently generating logistics reports based on business data. The data attributes of different logistics data are analyzed through a logistics data topological structure network, thereby improving data processing efficiency. The basic data in the logistics report is arranged through a data attribute evaluation index, thereby highlighting important data in the logistics report. By screening the information of logistics data extension items, a large number of logistics data extension items is avoided. By using the periodic difference coefficient of the report extension items, abnormal extension items in the logistics report are marked, thereby improving reading efficiency, ensuring rapid acquisition of required data analysis results, reducing time costs, and improving overall operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 A flow chart of a method for intelligently generating logistics reports based on business data proposed by the present invention;

[0076] Figure 2 This is a flow chart for obtaining basic information of logistics report in the present invention;

[0077] Figure 3 This is a flow chart for obtaining information about logistics report extension items in the present invention;

[0078] Figure 4 This is a flow chart for obtaining logistics report data in the present invention;

[0079] Figure 5 This is a flow chart for obtaining information on logistics report evaluation items in the present invention;

[0080] Figure 6 This is a structural block diagram of a logistics report intelligent generation system based on business data proposed by the present invention. DETAILED DESCRIPTION

[0081] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0082] Reference Figure 1 - Figure 5 As shown, a method for intelligently generating a logistics report based on business data in an embodiment of the present invention includes:

[0083] Acquire logistics system data, wherein the logistics system includes a warehouse management system, a transportation management system, and an order management system;

[0084] According to the logistics system data, based on the topological structure analysis, the logistics data topological structure network is obtained;

[0085] Specifically, based on the logistics system data and the topological structure analysis, the logistics data topological structure network is obtained, which includes:

[0086] According to the logistics system data, based on named entity recognition, the logistics system data attribute information is obtained, wherein the logistics system data attributes include logistics transportation time, logistics transportation mode, logistics order time and logistics warehousing information;

[0087] Analyze the logical relationship between data attributes of different logistics systems to obtain logistics data topology information;

[0088] According to the logistics data topology structure information, based on the topology network construction, a logistics data topology structure network is obtained, wherein the logistics data topology structure network includes a plurality of logistics data attribute nodes;

[0089] Among them, for any logistics data attribute node in the logistics data topology structure network, the logistics data attribute node that points to the node in logical order is the upper node of the node, and the logistics data attribute node that the node points to in logical order is the lower node.

[0090] In this scheme, the named entities of the logistics system data are identified to obtain the attribute information of the logistics system data, that is, the type information of the logistics system data. The topological structure information of the logistics data is obtained by analyzing the logical relationship between different attributes of the logistics system data. According to the topological structure information of the logistics data, the topological structure network of the logistics data is obtained based on the topological network construction.

[0091] It can be understood that in a topological network, if node A points to node B in logical order, then node A is the upper node of node B, and node B is the lower node of node A. If node A does not pass through an intermediate node in the process of pointing to node B in logical order, then node A and node B are adjacent nodes.

[0092] Acquire user interaction information, the user interaction information including user identity information and report requirement information, the report requirement is divided into daily report requirement, weekly report requirement and monthly report requirement;

[0093] According to the user interaction information, the basic information of the logistics report is arranged and generated, and the basic item information of the logistics report is obtained, and each type of logistics system data in the basic item information of the logistics report is arranged according to the data attribute sorting information;

[0094] Specifically, according to the user interaction information, the basic information of the logistics report is arranged and generated, and the basic item information of the logistics report is obtained, including:

[0095] Based on system function analysis, the logistics system data is classified to obtain warehouse management system data, transportation management system data and order management system data;

[0096] According to user interaction information, weights are set for different categories of logistics system data;

[0097] Based on the weight of logistics system data and the logistics data topological structure network, obtain the data attribute evaluation index;

[0098] Sort the logistics data attributes in descending order according to the data attribute evaluation index to obtain data attribute sorting information;

[0099] Based on the data attribute sorting information, the basic information of the logistics report is arranged and generated to obtain the basic item information of the logistics report;

[0100] The calculation formula of the data attribute evaluation index is:

[0101]

[0102] In the formula, Q(x, τ) represents the data attribute evaluation index of the logistics data attribute represented by the x-th logistics data attribute node, τ is the user identity recognition coefficient, if τ = 1, the weight ratio of the warehouse management system data, transportation management system data and order management system data is 1:2:1, if τ = 2, the weight ratio of the warehouse management system data, transportation management system data and order management system data is 2:1:1, if τ = 3, the weight ratio of the warehouse management system data, transportation management system data and order management system data is 1:1:2, α x is the logistics data weight of the x-th logistics data attribute node, α i is the logistics data weight of the ith upper node of the xth logistics data attribute node, w i is the number of intermediate nodes between the ith upper node of the xth logistics data attribute node and the xth logistics data attribute node, ki is the total number of adjacent logistics data attribute nodes pointed to by the ith upper node of the xth logistics data attribute node in logical order, α j is the logistics data weight of the jth subordinate node of the xth logistics data attribute node, w j is the number of intermediate nodes between the jth subordinate node of the xth logistics data attribute node and the xth logistics data attribute node, k j is the total number of logistics data attribute nodes that point to the jth subordinate node of the xth logistics data attribute node in logical order among the adjacent nodes of the jth subordinate node of the xth logistics data attribute node, n is the total number of upper nodes of the xth logistics data attribute node, and m is the total number of subordinate nodes of the xth logistics data attribute node.

[0103] In this solution, by classifying the logistics system data, obtaining the warehouse management system data, the transportation management system data and the order management system data, setting weights for the logistics system data of different categories according to the user interaction information, obtaining the data attribute evaluation index based on the weight of the logistics system data and the logistics data topological structure network, sorting the logistics data attributes in descending order according to the data attribute evaluation index, obtaining the data attribute sorting information, and generating the basic information arrangement of the logistics report based on the data attribute sorting information, obtaining the basic item information of the logistics report, thereby achieving the highlighting of the important data of the logistics report and ensuring the accuracy and consistency of the data;

[0104] It is understandable that for logistics reports, logistics system data as basic data needs to be displayed in full, but for users of different identities, the logistics report information they focus on is completely different. Therefore, different weights are set for logistics system data according to user identity information. In this embodiment, user identities are divided into three categories according to the logistics report information that users focus on, and are distinguished by user identity recognition coefficients.

[0105] According to the logistics system data and based on the logistics report analysis requirements, obtain the logistics report extension item information;

[0106] Specifically, based on the logistics system data and logistics report analysis requirements, the logistics report extension information is obtained, including:

[0107] According to the logistics system data, based on the logistics report analysis requirements, the logistics data extension item information is obtained, and the logistics data extension item information includes inventory turnover rate, order completion rate, return rate, on-time delivery rate, transportation rate and profit rate;

[0108] Based on the logistics data extension item information, obtain data extension related information corresponding to each logistics data extension item, wherein the data extension related information represents the logistics data attributes required for the logistics data extension item calculation;

[0109] According to the logistics data extension item information, data extension related information and data attribute evaluation index, obtain the data extension related index;

[0110] According to the data expansion related index, the logistics data expansion item information is filtered to obtain the logistics report expansion item information;

[0111] Among them, if the data expansion related index E(y, τ) ≤ 0.08, the logistics data expansion item does not meet the logistics report requirements. If the data expansion related index E(y, τ)> 0.08, the logistics data expansion item is available. The calculation formula of the data expansion related index is:

[0112]

[0113] Where E(y, τ) is the data extension related index of the y-th logistics data extension item, Q(b) is the data attribute evaluation index of the b-th logistics data required by the y-th logistics data extension item, τ is the user identity recognition coefficient, if τ = 1, then Q(c) is the data attribute evaluation index of the c-th logistics data in the transportation management system data, s is the total number of logistics data attribute types in the transportation management system data, if τ = 2, then Q(c) is the data attribute evaluation index of the c-th logistics data in the warehouse management system data, s is the total number of logistics data attribute types in the warehouse management system data, if τ = 3, then Q(c) is the data attribute evaluation index of the c-th logistics data in the order management system data, s is the total number of logistics data attribute types in the order management system data, H is the total number of logistics data attribute types required by the y-th logistics data extension item, and δ is the number of occurrences of the b-th logistics data in the calculation process of the y-th logistics data extension item.

[0114] In this solution, logistics system data is used to obtain logistics data extension item information based on logistics report analysis needs. According to the logistics data extension item information, data extension related information and data attribute evaluation index, the data extension related index is obtained. According to the data extension related index, the logistics data extension item information is screened to obtain the logistics report extension item information. This improves the efficiency of logistics report generation and avoids the impact of numerous logistics data extension items on logistics report reading.

[0115] Obtain logistics report data item information based on logistics report extension item information and logistics report basic item information;

[0116] Based on the report requirement information, filter the logistics system data and obtain the logistics report data;

[0117] Specifically, based on the report requirement information, the logistics system data is screened to obtain logistics report data, including:

[0118] According to the report requirement information, obtain the report generation cycle information;

[0119] According to the logistics system data, based on data feature recognition, obtain data time tag information;

[0120] According to the user interaction information, obtain the user report requirement instruction time information;

[0121] Taking the user report demand instruction time information as the starting point, and the report generation cycle information as the benchmark, the logistics system data is classified according to the data time tag information to obtain the logistics system data group;

[0122] The logistics system data group represents the logistics system data within a report generation cycle;

[0123] Based on the data time tag information, the logistics system data groups are numbered, and the logistics system data group within a report generation cycle from the user report demand instruction time is taken as the first logistics system data group;

[0124] The first logistics system data set is used as logistics report data.

[0125] In this solution, by taking the user report demand instruction time information as the starting point and the report generation cycle information as the benchmark, the logistics system data is classified according to the data time tag information to obtain the logistics system data group, and the logistics system data group that is within one report generation cycle from the user report demand instruction time is taken as the first logistics system data group, and the first logistics system data group is used as the logistics report data, thereby improving the efficiency of logistics report generation.

[0126] Fill in the logistics report based on the logistics report data item information and logistics report data to generate the logistics report.

[0127] Specifically, the logistics report is filled in according to the logistics report data item information and the logistics report data to generate the logistics report, which specifically includes:

[0128] According to the logistics report data item information, obtain the logistics report extension item information and logistics report basic item information;

[0129] Based on the logistics report data, fill in the basic items of the logistics report;

[0130] Based on the logistics report data and logistics report extension information, obtain the logistics report extension item calculation data;

[0131] Based on the calculation data of the logistics report extension items, fill in the logistics report extension items;

[0132] Obtaining logistics system data group;

[0133] Calculate data based on the logistics system data group and logistics report extension items to obtain the report extension item cycle difference coefficient;

[0134] According to the cycle difference coefficient of the report extension item, determine whether the calculated data of the logistics report extension item is abnormal. If not, mark the calculated data of the logistics report extension item as normal. If so, mark the calculated data of the logistics report extension item as abnormal, record the cycle difference coefficient of the report extension item, and obtain the logistics report evaluation item information;

[0135] Fill in the logistics report according to the evaluation item information of the logistics report to generate the logistics report;

[0136] Among them, if the report extension item cycle difference coefficient R(y)≤0.82, the logistics report extension item calculation data is abnormal; if R(y)>0.82, the logistics report extension item calculation data is normal. The calculation formula of the report extension item cycle difference coefficient is:

[0137]

[0138] Where R(y) is the period difference coefficient of the report expansion item of the y-th logistics data expansion item, f(y, D1) represents the calculation data of the y-th logistics data expansion item with the first logistics system data group as input, and f(y, D g ) represents the calculation data of the yth logistics data extension item with the gth logistics system data group as input, and T is the total number of logistics system data groups.

[0139] In this solution, the basic items of the logistics report are filled based on the logistics report data, and the logistics report extension items are filled through the logistics report extension item calculation data. According to the logistics system data group and the logistics report extension item calculation data, the report extension item cycle difference coefficient is obtained. According to the report extension item cycle difference coefficient, it is judged whether the logistics report extension item calculation data is abnormal. According to the report extension item cycle difference coefficient, the abnormal extension items in the logistics report are marked, which improves the reading efficiency, ensures the rapid acquisition of the required data analysis results, reduces the time cost, and improves the overall operational efficiency.

[0140] Reference Figure 5 As shown, further, in combination with the above-mentioned method for intelligently generating a logistics report based on business data, a system for intelligently generating a logistics report based on business data is proposed, including:

[0141] A main control module, the main control module is used to screen the logistics data expansion item information according to the data expansion related index, obtain the logistics report expansion item information, determine whether the logistics report expansion item calculation data is abnormal according to the report expansion item period difference coefficient, analyze the logical relationship between different logistics system data attributes, obtain the logistics data topology structure information, and obtain the logistics data topology structure network based on the topological network construction according to the logistics data topology structure information, set weights for logistics system data of different categories according to user interaction information, obtain the logistics data expansion item information according to the logistics system data and the logistics report analysis requirements, fill the logistics report according to the logistics report data item information and the logistics report data, and generate the logistics report;

[0142] An information acquisition module, which is used to acquire logistics system data, warehouse management system data, transportation management system data and order management system data, and acquires logistics system data attribute information based on named entity recognition according to the logistics system data, acquires user interaction information, user identity information and report requirement information, and acquires report generation cycle information according to the report requirement information;

[0143] An evaluation module, wherein the evaluation module is used to obtain a data attribute evaluation index based on the weight of the logistics system data and the logistics data topological structure network, sort the logistics data attributes in descending order according to the data attribute evaluation index, obtain data attribute sorting information, obtain data extension related information corresponding to each logistics data extension item based on the logistics data extension item information, obtain a data extension related index based on the logistics data extension item information, the data extension related information and the data attribute evaluation index, calculate data based on the logistics system data group and the logistics report extension item, and obtain a report extension item cycle difference coefficient;

[0144] The display module interacts with the main control module and is used to display basic item information of logistics data, extended item information of logistics data, report generation cycle information and logistics reports.

[0145] Main control module, specifically including:

[0146] A control unit, the control unit is used to analyze the logical relationship between different logistics system data attributes, obtain logistics data topology structure information, and obtain the logistics data topology structure network based on the topology network construction according to the logistics data topology structure information, and set weights for logistics system data of different categories according to user interaction information, and obtain logistics data extension item information based on the logistics system data and logistics report analysis requirements, and fill the logistics report according to the logistics report data item information and the logistics report data, and generate the logistics report;

[0147] An information receiving unit, which interacts with the information acquisition module and the evaluation module to receive data and transmit it to the judgment unit;

[0148] The judgment unit is used to screen the logistics data expansion item information according to the data expansion related index, obtain the logistics report expansion item information, and judge whether the logistics report expansion item calculation data is abnormal according to the report expansion item period difference coefficient.

[0149] Information acquisition module, specifically including:

[0150] A first acquisition unit, the first acquisition unit is used to acquire logistics system data, warehouse management system data, transportation management system data and order management system data, and acquire logistics system data attribute information based on named entity recognition according to the logistics system data;

[0151] The second acquisition unit is used to acquire user interaction information, user identity information and report requirement information, and acquire report generation cycle information according to the report requirement information.

[0152] Assessment modules include:

[0153] A data attribute evaluation unit, the data attribute evaluation unit is used to obtain a data attribute evaluation index based on the weight of the logistics system data and the logistics data topological structure network, sort the logistics data attributes in descending order according to the data attribute evaluation index, and obtain data attribute sorting information;

[0154] A data expansion evaluation unit, the data expansion evaluation unit is used to obtain data expansion related information corresponding to each logistics data expansion item based on the logistics data expansion item information, and obtain a data expansion related index according to the logistics data expansion item information, the data expansion related information and the data attribute evaluation index;

[0155] The cycle difference evaluation unit is used to calculate data based on the logistics system data group and the logistics report extension items to obtain the cycle difference coefficient of the report extension item.

[0156] In summary, the advantages of the present invention are: analyzing the data attributes of different logistics data through the logistics data topology structure network, improving the data processing efficiency, facilitating the subsequent data evaluation, obtaining the data attribute evaluation index through the weight of the logistics system data and the logistics data topology structure network, arranging the basic data in the logistics report through the data attribute evaluation index, realizing the highlighting of the important data of the logistics report, ensuring the accuracy and consistency of the data, obtaining the data extension related index through the logistics data extension item information, data extension related information and the data attribute evaluation index, screening the logistics data extension item information through the data extension related index, improving the efficiency of logistics report generation, avoiding the large number of logistics data extension items, calculating data through the logistics system data group and the logistics report extension item, obtaining the report extension item cycle difference coefficient, and marking the abnormal extension items in the logistics report through the report extension item cycle difference coefficient, improving the reading efficiency, ensuring the rapid acquisition of the required data analysis results, reducing the time cost, and improving the overall operational efficiency.

[0157] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for intelligently generating logistics reports based on business data, characterized in that: include: Acquire logistics system data, wherein the logistics system includes a warehouse management system, a transportation management system, and an order management system; According to the logistics system data, based on the topological structure analysis, the logistics data topological structure network is obtained; Acquire user interaction information, the user interaction information including user identity information and report requirement information, the report requirement is divided into daily report requirement, weekly report requirement and monthly report requirement; According to the user interaction information, the basic information of the logistics report is arranged and generated, and the basic item information of the logistics report is obtained, and each type of logistics system data in the basic item information of the logistics report is arranged according to the data attribute sorting information; According to the logistics system data and based on the logistics report analysis requirements, obtain the logistics report extension item information; Obtain logistics report data item information based on logistics report extension item information and logistics report basic item information; Based on the report requirement information, filter the logistics system data and obtain the logistics report data; Fill in the logistics report based on the logistics report data item information and logistics report data to generate the logistics report.

2. According to claim 1, a method for intelligently generating logistics reports based on business data is characterized in that: The obtaining of the logistics data topology network based on the logistics system data and the topology structure analysis specifically includes: According to the logistics system data, based on named entity recognition, the logistics system data attribute information is obtained, wherein the logistics system data attributes include logistics transportation time, logistics transportation mode, logistics order time and logistics warehousing information; Analyze the logical relationship between data attributes of different logistics systems to obtain logistics data topology information; According to the logistics data topology structure information, based on the topology network construction, a logistics data topology structure network is obtained, wherein the logistics data topology structure network includes a plurality of logistics data attribute nodes; Among them, for any logistics data attribute node in the logistics data topology structure network, the logistics data attribute node that points to the node in logical order is the upper node of the node, and the logistics data attribute node that the node points to in logical order is the lower node.

3. According to claim 1, a method for intelligently generating logistics reports based on business data is characterized in that: The generating of arranging the basic information of the logistics report according to the user interaction information and obtaining the basic item information of the logistics report specifically includes: Based on system function analysis, the logistics system data is classified to obtain warehouse management system data, transportation management system data and order management system data; According to user interaction information, weights are set for different categories of logistics system data; Based on the weight of logistics system data and the logistics data topological structure network, obtain the data attribute evaluation index; Sort the logistics data attributes in descending order according to the data attribute evaluation index to obtain data attribute sorting information; Based on the data attribute sorting information, the basic information of the logistics report is arranged and generated to obtain the basic item information of the logistics report; The calculation formula of the data attribute evaluation index is: In the formula, Q(x, τ) represents the data attribute evaluation index of the logistics data attribute represented by the x-th logistics data attribute node, τ is the user identity recognition coefficient, if τ = 1, the weight ratio of the warehouse management system data, transportation management system data and order management system data is 1:2:1, if τ = 2, the weight ratio of the warehouse management system data, transportation management system data and order management system data is 2:1:1, if τ = 3, the weight ratio of the warehouse management system data, transportation management system data and order management system data is 1:1:2, α x is the logistics data weight of the x-th logistics data attribute node, α i is the logistics data weight of the ith upper node of the xth logistics data attribute node, w i is the number of intermediate nodes between the ith upper node of the xth logistics data attribute node and the xth logistics data attribute node, k i is the total number of adjacent logistics data attribute nodes pointed to by the ith upper node of the xth logistics data attribute node in logical order, α j is the logistics data weight of the jth subordinate node of the xth logistics data attribute node, w j is the number of intermediate nodes between the jth subordinate node of the xth logistics data attribute node and the xth logistics data attribute node, k j is the total number of logistics data attribute nodes that point to the jth subordinate node of the xth logistics data attribute node in logical order among the adjacent nodes of the jth subordinate node of the xth logistics data attribute node, n is the total number of upper nodes of the xth logistics data attribute node, and m is the total number of subordinate nodes of the xth logistics data attribute node.

4. According to claim 1, a method for intelligently generating logistics reports based on business data is characterized in that: The method of obtaining logistics report extension item information based on logistics system data and logistics report analysis requirements specifically includes: According to the logistics system data, based on the logistics report analysis requirements, the logistics data extension item information is obtained, and the logistics data extension item information includes inventory turnover rate, order completion rate, return rate, on-time delivery rate, transportation rate and profit rate; Based on the logistics data extension item information, obtain data extension related information corresponding to each logistics data extension item, wherein the data extension related information represents the logistics data attributes required for the logistics data extension item calculation; According to the logistics data extension item information, data extension related information and data attribute evaluation index, obtain the data extension related index; According to the data expansion related index, the logistics data expansion item information is filtered to obtain the logistics report expansion item information; Among them, if the data expansion related index E(y, τ) ≤ 0.08, the logistics data expansion item does not meet the logistics report requirements. If the data expansion related index E(y, τ)> 0.08, the logistics data expansion item is available. The calculation formula of the data expansion related index is: Where E(y, τ) is the data extension related index of the y-th logistics data extension item, Q(b) is the data attribute evaluation index of the b-th logistics data required by the y-th logistics data extension item, τ is the user identity recognition coefficient, if τ = 1, then Q(c) is the data attribute evaluation index of the c-th logistics data in the transportation management system data, s is the total number of logistics data attribute types in the transportation management system data, if τ = 2, then Q(c) is the data attribute evaluation index of the c-th logistics data in the warehouse management system data, s is the total number of logistics data attribute types in the warehouse management system data, if τ = 3, then Q(c) is the data attribute evaluation index of the c-th logistics data in the order management system data, s is the total number of logistics data attribute types in the order management system data, H is the total number of logistics data attribute types required by the y-th logistics data extension item, and δ is the number of occurrences of the b-th logistics data in the calculation process of the y-th logistics data extension item.

5. According to claim 1, a method for intelligently generating logistics reports based on business data is characterized in that: The method of screening the logistics system data based on the report requirement information and obtaining the logistics report data specifically includes: According to the report requirement information, obtain the report generation cycle information; According to the logistics system data, based on data feature recognition, obtain data time tag information; According to the user interaction information, obtain the user report requirement instruction time information; Taking the user report demand instruction time information as the starting point, and the report generation cycle information as the benchmark, the logistics system data is classified according to the data time tag information to obtain the logistics system data group; The logistics system data group represents the logistics system data within a report generation cycle; Based on the data time tag information, the logistics system data groups are numbered, and the logistics system data group within a report generation cycle from the user report demand instruction time is taken as the first logistics system data group; The first logistics system data set is used as logistics report data.

6. According to claim 1, a method for intelligently generating logistics reports based on business data is characterized in that: The step of filling the logistics report according to the logistics report data item information and the logistics report data to generate the logistics report specifically includes: According to the logistics report data item information, obtain the logistics report extension item information and logistics report basic item information; Based on the logistics report data, fill in the basic items of the logistics report; Based on the logistics report data and logistics report extension information, obtain the logistics report extension item calculation data; Based on the calculation data of the logistics report extension items, fill in the logistics report extension items; Obtaining logistics system data group; Calculate data based on the logistics system data group and logistics report extension items to obtain the report extension item cycle difference coefficient; According to the cycle difference coefficient of the report extension item, determine whether the calculated data of the logistics report extension item is abnormal. If not, mark the calculated data of the logistics report extension item as normal. If so, mark the calculated data of the logistics report extension item as abnormal, record the cycle difference coefficient of the report extension item, and obtain the logistics report evaluation item information; Fill in the logistics report according to the evaluation item information of the logistics report to generate the logistics report; Among them, if the report extension item cycle difference coefficient R(y)≤0.82, the logistics report extension item calculation data is abnormal; if R(y)>0.82, the logistics report extension item calculation data is normal. The calculation formula of the report extension item cycle difference coefficient is: Where R(y) is the period difference coefficient of the report expansion item of the y-th logistics data expansion item, f(y, D1) represents the calculation data of the y-th logistics data expansion item with the first logistics system data group as input, and f(y, D g ) represents the calculation data of the yth logistics data extension item with the gth logistics system data group as input, and T is the total number of logistics system data groups.

7. A logistics report intelligent generation system based on business data, used to implement the generation method according to any one of claims 1 to 6, characterized in that: include: A main control module, the main control module is used to screen the logistics data expansion item information according to the data expansion related index, obtain the logistics report expansion item information, determine whether the logistics report expansion item calculation data is abnormal according to the report expansion item period difference coefficient, analyze the logical relationship between different logistics system data attributes, obtain the logistics data topology structure information, and obtain the logistics data topology structure network based on the topological network construction according to the logistics data topology structure information, set weights for logistics system data of different categories according to user interaction information, obtain the logistics data expansion item information according to the logistics system data and the logistics report analysis requirements, fill the logistics report according to the logistics report data item information and the logistics report data, and generate the logistics report; An information acquisition module, which is used to acquire logistics system data, warehouse management system data, transportation management system data and order management system data, and acquires logistics system data attribute information based on named entity recognition according to the logistics system data, acquires user interaction information, user identity information and report requirement information, and acquires report generation cycle information according to the report requirement information; An evaluation module, wherein the evaluation module is used to obtain a data attribute evaluation index based on the weight of the logistics system data and the logistics data topological structure network, sort the logistics data attributes in descending order according to the data attribute evaluation index, obtain data attribute sorting information, obtain data extension related information corresponding to each logistics data extension item based on the logistics data extension item information, obtain a data extension related index based on the logistics data extension item information, the data extension related information and the data attribute evaluation index, calculate data based on the logistics system data group and the logistics report extension item, and obtain a report extension item cycle difference coefficient; The display module interacts with the main control module and is used to display basic item information of logistics data, extended item information of logistics data, report generation cycle information and logistics reports.

8. The intelligent generation system of logistics report based on business data according to claim 7 is characterized in that: The main control module specifically includes: A control unit, the control unit is used to analyze the logical relationship between different logistics system data attributes, obtain logistics data topology structure information, and obtain the logistics data topology structure network based on the topology network construction according to the logistics data topology structure information, and set weights for logistics system data of different categories according to user interaction information, and obtain logistics data extension item information based on the logistics system data and logistics report analysis requirements, and fill the logistics report according to the logistics report data item information and the logistics report data, and generate the logistics report; An information receiving unit, which interacts with the information acquisition module and the evaluation module to receive data and transmit it to the judgment unit; The judgment unit is used to screen the logistics data expansion item information according to the data expansion related index, obtain the logistics report expansion item information, and judge whether the logistics report expansion item calculation data is abnormal according to the report expansion item period difference coefficient.

9. The intelligent generation system of logistics reports based on business data according to claim 7 is characterized in that: The information acquisition module specifically includes: A first acquisition unit, the first acquisition unit is used to acquire logistics system data, warehouse management system data, transportation management system data and order management system data, and acquire logistics system data attribute information based on named entity recognition according to the logistics system data; The second acquisition unit is used to acquire user interaction information, user identity information and report requirement information, and acquire report generation cycle information according to the report requirement information.

10. The intelligent generation system of logistics report based on business data according to claim 7 is characterized in that: The evaluation module specifically includes: A data attribute evaluation unit, the data attribute evaluation unit is used to obtain a data attribute evaluation index based on the weight of the logistics system data and the logistics data topological structure network, sort the logistics data attributes in descending order according to the data attribute evaluation index, and obtain data attribute sorting information; A data expansion evaluation unit, the data expansion evaluation unit is used to obtain data expansion related information corresponding to each logistics data expansion item based on the logistics data expansion item information, and obtain a data expansion related index according to the logistics data expansion item information, the data expansion related information and the data attribute evaluation index; The cycle difference evaluation unit is used to calculate data based on the logistics system data group and the logistics report extension items to obtain the cycle difference coefficient of the report extension item.

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