CN113159118A - Logistics data index processing method, device, equipment and storage medium - Google Patents
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Abstract
The invention relates to the field of logistics management, and discloses a method, a device, equipment and a storage medium for processing logistics data indexes, wherein the method comprises the following steps: acquiring logistics data, and determining data meanings of all indexes in the logistics data and service types corresponding to all the indexes; classifying a plurality of indexes in the logistics data to obtain at least one data subject domain, and establishing a mapping relation between the indexes in each data subject domain and the data subject domain; carrying out hierarchical division on each index in the mapping relation to obtain an index system; and generating an index white paper according to the index system. According to the technical scheme provided by the invention, the indexes in the logistics data are processed to form an index system, the indexes in the logistics data are subjected to standardized management, and mass logistics data can be accurately and effectively processed and analyzed during data analysis according to the formed index system, so that the efficiency and accuracy of data analysis are improved.
Description
Technical Field
The present invention relates to the field of logistics management, and in particular, to a method, an apparatus, a device, and a storage medium for processing a logistics data index.
Background
Currently, the express logistics industry is rapidly developed over a decade, and logistics merchants accumulate massive logistics data, tens of thousands of data reports, tens of thousands of logistics data indexes and the like. Such huge data assets do not form a unified standard system for logistics data indexes without refined unified management, which brings inconvenience in practical use.
How to better utilize the accumulated historical logistics data becomes a concern of the logistics industry. In the data analysis process, indexes in the logistics data are analyzed, so that the accuracy and the effectiveness of data analysis results are related. Therefore, in the logistics industry, the establishment of a unified index system by using historical logistics data has become an urgent problem to be solved.
Disclosure of Invention
The invention mainly aims to solve the technical problem that in the prior art, the logistics data indexes do not form a uniform index system, so that the efficiency of processing and analyzing mass logistics data is low.
The first aspect of the present invention provides a method for processing a logistics data index, where the method for processing a logistics data index includes:
acquiring logistics data, wherein the logistics data comprises a plurality of indexes;
determining the data meaning of each index and the service type corresponding to each index in the logistics data;
classifying a plurality of indexes in the logistics data based on the data meaning and the service type to obtain at least one data subject domain, and establishing a mapping relation between the indexes in each data subject domain and the data subject domain, wherein the mapping relation is that one data subject domain corresponds to at least one index;
carrying out hierarchical division on each index in the mapping relation to obtain an index system;
and generating an index white paper according to the index system.
Optionally, in a first implementation manner of the first aspect of the present invention, the determining the data meaning of each index and the service type corresponding to each index in the logistics data includes:
calling a preset semantic recognition rule, recognizing the semantics of each index in the logistics data, and obtaining the data meaning of each index;
and extracting the service characteristic information in each index, analyzing the relevance between the service characteristic information and each service in the logistics industry, and determining the service type of each index based on the relevance.
Optionally, in a second implementation manner of the first aspect of the present invention, the classifying a plurality of indicators in the logistics data based on the data meaning and the service type to obtain at least one data topic domain, and establishing a mapping relationship between the indicator in each data topic domain and the data topic domain includes:
calculating a matching value between the data meaning of the same index in the logistics data and the service type;
judging whether the matching value is smaller than a preset matching threshold value or not;
if the matching value is smaller than the preset matching threshold value, removing corresponding indexes to obtain an index set;
comparing whether the service types of the indexes in the index set are consistent or not;
if so, summarizing the multiple indexes with the consistent service types to obtain at least one data subject domain;
and establishing a mapping relation between each index in each data subject field and the data subject field based on at least one data subject field.
Optionally, in a third implementation manner of the first aspect of the present invention, the calculating a matching value between the data meaning of the same index in the logistics data and the service type includes:
in a semantic space, performing semantic dimension analysis on the service type of each index in the logistics data to obtain service type dimension;
analyzing the semantic dimension of the data meaning of each index to obtain the data meaning dimension;
calculating the similarity of the service type dimension and the data meaning dimension in the same index to obtain a dimension similarity value;
and using the dimension similarity value as a matching value between the data meaning of the same index and the service type.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the performing hierarchical division on each index in the mapping relationship to obtain an index system includes:
performing hierarchical analysis of service types on each index in the mapping relation, sequencing the service types based on the result of the hierarchical analysis, and generating service levels of all the indexes;
constructing a connection relation among the indexes based on the service levels to obtain index levels;
and generating an index system according to the index hierarchy and the mapping relation.
Optionally, in a fifth implementation manner of the first aspect of the present invention, generating an index white paper according to the index system includes:
analyzing related information of each index in the index system based on the index system to obtain an analysis result, wherein the related information at least comprises index attributes and index hierarchical relations;
and performing file conversion on the analysis result based on a preset file conversion rule to generate an index white paper.
Optionally, in a sixth implementation manner of the first aspect of the present invention, after the generating an index white paper according to the index system, the method further includes:
acquiring source information of the logistics data, and determining an output form of the index system based on the source information;
extracting indexes with the same data meaning in the same data subject field in the index system according to the output form, and combining to obtain a new index system;
coding each index in the new index system to generate an index code;
and establishing a mapping relation between the indexes in the new index system and the index codes to obtain an index code system.
A second aspect of the present invention provides a device for processing a logistics data index, where the device for processing a logistics data index includes:
the acquisition module is used for acquiring logistics data;
the determining module is used for determining the data meaning of each index in the logistics data and the service type corresponding to each index;
the classification module is used for classifying a plurality of indexes in the logistics data based on the data meaning and the service type to obtain at least one data subject domain and establishing a mapping relation between the indexes in each data subject domain and the data subject domain;
the hierarchical division module is used for carrying out hierarchical division on each index in the mapping relation to obtain an index system;
and the generating module is used for generating an index white paper according to the index system.
Optionally, in a first implementation manner of the second aspect of the present invention, the determining module is specifically configured to:
calling a preset semantic recognition rule, recognizing the semantics of each index in the logistics data, and obtaining the data meaning of each index;
and extracting the service characteristic information in each index, analyzing the relevance between the service characteristic information and each service in the logistics industry, and determining the service type of each index based on the relevance.
Optionally, in a second implementation manner of the second aspect of the present invention, the classification module includes:
the calculation unit is used for calculating a matching value between the data meaning of the same index in the logistics data and the service type;
the removing unit is used for presetting a matching threshold value, and removing corresponding indexes to obtain an index set if the matching value is smaller than the matching threshold value;
the judging unit is used for judging whether the matching value is smaller than a preset matching threshold value or not;
the rejecting unit is used for rejecting corresponding indexes to obtain an index set when the matching value is smaller than the preset matching threshold value;
the comparison unit is used for comparing whether the service types of the indexes in the index set are consistent or not;
the classification unit is used for summarizing a plurality of indexes with consistent service types to obtain at least one data subject domain when the service types between the indexes are consistent;
and the mapping unit is used for establishing a mapping relation between each index in each data topic domain and the data topic domain based on at least one data topic domain.
Optionally, in a third implementation manner of the second aspect of the present invention, the calculating unit is specifically configured to:
in a semantic space, performing semantic dimension analysis on the service type of each index in the logistics data to obtain service type dimension;
analyzing the semantic dimension of the data meaning of each index to obtain the data meaning dimension;
calculating the similarity of the service type dimension and the data meaning dimension in the same index to obtain a dimension similarity value;
and using the dimension similarity value as a matching value between the data meaning of the same index and the service type.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the hierarchical dividing module is specifically configured to:
performing hierarchical analysis of service types on each index in the mapping relation, sequencing the service types based on the result of the hierarchical analysis, and generating service levels of all the indexes;
constructing a connection relation among the indexes based on the service levels to obtain index levels;
and generating an index system according to the index hierarchy and the mapping relation.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the generating module is specifically configured to:
analyzing related information of each index in the index system based on the index system to obtain an analysis result;
and performing file conversion on the analysis result based on a preset file conversion rule to generate an index white paper.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the device for processing the logistics data index further includes an updating module, where the updating module is specifically configured to:
acquiring source information of the logistics data, and determining an output form of the index system based on the source information;
extracting indexes with the same data meaning in the same data subject field in the index system according to the output form, and combining to obtain a new index system;
coding each index in the new index system to generate an index code;
and establishing a mapping relation between the indexes in the new index system and the index codes to obtain an index code system.
A third aspect of the present invention provides a device for processing a logistics data index, including: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line; the at least one processor calls the instructions in the memory to cause the processing equipment of the physical distribution data index to execute the steps of the physical distribution data index processing method.
A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon instructions, which, when run on a computer, cause the computer to perform the steps of the above-mentioned method for processing a logistics data index.
In the technical scheme provided by the invention, the data meaning of each index and the service type corresponding to each index in the logistics data are determined by acquiring the logistics data; comparing the data meaning of each index with the service type corresponding to each index, classifying a plurality of indexes in the logistics data based on the comparison result to obtain at least one data theme domain, and establishing a mapping relation between the indexes in each data theme domain and the data theme domain; carrying out hierarchical division on each index in the mapping relation to obtain an index system; and generating an index white paper according to the index system. According to the technical scheme provided by the invention, the index system is constructed by processing each index in the logistics data, so that each index in the logistics data can be conveniently processed by utilizing the formed index system subsequently, the efficiency and flexibility of processing the logistics data index are improved, meanwhile, the construction of the index system can improve the analysis efficiency and accuracy of the logistics data, and the time cost is saved.
Drawings
FIG. 1 is a schematic diagram of a first embodiment of a method for processing a logistics data index according to an embodiment of the invention;
FIG. 2 is a schematic diagram of a second embodiment of a method for processing a logistics data index according to an embodiment of the invention;
FIG. 3 is a schematic diagram of a third embodiment of a method for processing a logistics data index according to an embodiment of the invention;
FIG. 4 is a schematic diagram of a fourth embodiment of the method for processing the logistics data index according to the embodiment of the invention;
FIG. 5 is a schematic diagram of an embodiment of a device for processing physical distribution data indicators according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of another embodiment of a device for processing physical distribution data indicators according to an embodiment of the present invention;
fig. 7 is a schematic diagram of an embodiment of a device for processing logistics data indexes in the embodiment of the invention.
Detailed Description
The embodiment of the invention provides a method, a device, equipment and a storage medium for processing indexes of logistics data, wherein the data meaning of each index and the service type corresponding to each index in the logistics data are determined by acquiring the logistics data; comparing the data meaning of each index with the service type corresponding to each index, classifying a plurality of indexes in the logistics data based on the comparison result to obtain at least one data theme domain, and establishing a mapping relation between the indexes in each data theme domain and the data theme domain; carrying out hierarchical division on each index in the mapping relation to obtain an index system; and generating an index white paper according to the index system. According to the technical scheme provided by the invention, the index system is constructed by processing each index in the logistics data, so that each index in the logistics data can be conveniently processed by utilizing the formed index system subsequently, the efficiency and flexibility of processing the logistics data index are improved, meanwhile, the construction of the index system can improve the analysis efficiency and accuracy of the logistics data, and the time cost is saved.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For the sake of understanding, the following describes specific contents of an embodiment of the present invention, and referring to fig. 1, a first embodiment of a method for processing a logistics data index according to an embodiment of the present invention includes:
101, acquiring logistics data;
collecting data reports of management departments such as operation departments, network points, centers and the like of all merchants in the logistics industry as data sources, namely advanced business investigation, confirming business departments and responsible persons, confirming relevant core reports and data sources, confirming data use and significance, confirming field meanings and dimensionality of the data reports, and acquiring relevant logistics data from the collected data reports, wherein the logistics data are data related to a plurality of businesses in the logistics industry.
Specifically, the logistics data may be data generated in a logistics service process, and may include one or more of order data, business data, and capacity data. The order data may be data related to an order submitted by a user, such as order number, pickup address, delivery address, etc. The operation data may be profit or fee data related to the transaction order, such as profit corresponding to one transaction order. The capacity data may be data related to capacity resources, such as the number of couriers, the delivery status of the couriers, and the like.
102, determining data meanings of all indexes in the logistics data and service types corresponding to all the indexes;
according to the obtained related logistics data, performing semantic analysis on each index in each logistics data in a semantic space to obtain the data meaning of each index, analyzing the service characteristic information of each index, and determining the service type corresponding to each index.
Specifically, a preset semantic recognition rule is called, text extraction is performed on data attributes of each index in the logistics data in a semantic space, namely, the label attributes of the index are extracted, the label attributes are in a text form, word segmentation processing is performed on the label attributes, semantic recognition is performed according to the word segmentation processing result, and therefore the data meaning of each index is obtained through recognition.
The logistics data is data related to a plurality of services in the logistics industry, each index in the logistics data carries service characteristic information of corresponding services, the service characteristic information of each index is extracted, the relevance between the service characteristic information and each service in the logistics industry is analyzed according to the service characteristic information carried by each index, the relevance is obtained according to relevance analysis, and therefore the service type corresponding to each index can be determined according to the relevance.
103, classifying a plurality of indexes in the logistics data based on data meaning and service type to obtain at least one data subject domain, and establishing a mapping relation between the indexes in each data subject domain and the data subject domain;
and performing semantic analysis on the data meaning and the service type corresponding to the same index, namely analyzing whether the semantics of the data meaning in the same index are consistent with the semantics of the corresponding service type, and when the semantics are consistent, indicating that the data meaning of the index is matched with the service type corresponding to the index, namely the attribute information of the index is correct, so as to screen out the index with correct attribute information, and classifying the indexes with correct attribute information according to the corresponding service types to obtain at least one index set. One service type corresponds to one index set, one service type corresponds to at least one index, and the index set is used as a data subject field. And establishing a mapping relation between each index in each data topic domain and the data topic domain, wherein the mapping relation is that one data topic domain at least corresponds to one index.
104, carrying out hierarchical division on each index in the mapping relation to obtain an index system;
and according to the mapping relation between the data subject domain and each index, carrying out hierarchical division on each index in each data subject domain in the mapping relation. The method comprises the steps that a plurality of services exist in the logistics industry, hierarchical relations exist among the services, each index corresponds to different service types, one service corresponds to different service types, the hierarchical relation of the service types of the corresponding indexes is analyzed according to the hierarchical relation among the services, accordingly, the hierarchical connection relation among the indexes is obtained, and the indexes are converted into an index system according to the hierarchical connection relation among the indexes obtained through analysis. In the process, an index mapping relation between each service field and each data subject field can be established according to the service type corresponding to the index, so that each index in the data sources of different services can be integrated into an index system according to the mapping relation, and the index system is continuously perfected according to a new data source.
According to the embodiment, the system can automatically complete the conversion from the data to the index system through the configurable interface, the visual analysis result is generated, and the visual analysis result is presented, so that the link of manual participation is saved, a large amount of labor cost can be saved, meanwhile, the data analysis result finally subjected to data analysis by using the index system is ensured not to be wrong due to human negligence, the data processing efficiency is improved, and the comprehensiveness and the accuracy of the data analysis result are ensured.
105, generating an index white paper according to the index system.
The logistics industry has a plurality of index sources, and in order to better manage the indexes, a unified index system and a calculation logic system must be formed, namely, an index white paper is generated on the basis of the formed index system and is used for carrying out standard management on various indexes. According to the obtained index system, the related information of the indexes in the index system is analyzed, specifically, the attribute information, the hierarchical relationship and other information of each index are analyzed, and based on the analysis process, the related information of each index, such as the attribute information, the hierarchical relationship and other information, is subjected to unified standard definition, namely, the related information of each index is summarized, summarized and summarized to form a unified standard, an index white paper is generated, and the index white paper can be called to process each index subsequently, so that the index aperture is unified, the index ambiguity is eliminated, and the efficiency of data analysis is improved.
In addition, after the index system is constructed, a complete and uniform data source can be provided for data analysis of the business by providing a new public service interface. The new business report forms of each business layer are completed through a public service interface, so that the phenomenon that logistics data in each data report form are inconsistent due to independent development and independent formation of the data report forms of each business department is avoided; when the server needs to switch the data source and the bottom layer change of the database, the client does not need any change, and only needs the public service interface to switch the bottom layer source or modify the internal data processing logic of the interface, so that the loose coupling architecture of the server and the client is realized.
Specifically, under the condition of preferentially ensuring stable business operation, a public service hall and a new cockpit APP are erected, then independent data reports of all existing business systems are gradually replaced, and finally, a brand-new auxiliary decision-making system approved by all departments with unified core standards is formed for companies.
In the embodiment of the invention, when the application scene is a logistics company, the data assets of the logistics company are integrated by processing each index in the logistics data, the data subject field is divided, an index system and an index white paper are generated, the index ambiguity is eliminated, and the index calibers are unified; data interfaces are uniformly provided through the public service hall, and the same dimension and the same index adopt the same interface to provide data, so that the situation of data inconsistency is avoided, and the data analysis efficiency is improved.
In the embodiment of the invention, the data topic domain is obtained by classifying a plurality of indexes in the logistics data, and the indexes in the data topic domain are hierarchically divided to form an index system, so that an index white paper is generated, the standardized management of the indexes is realized, the data can be conveniently analyzed in the follow-up process, and the data analysis efficiency is improved.
Referring to fig. 2, a second embodiment of the method for processing a logistics data index according to the embodiment of the invention includes:
201, acquiring logistics data;
202, determining the data meaning of each index in the logistics data and the service type corresponding to each index;
203, analyzing semantic dimensions of the service types of each index in the logistics data in a semantic space to obtain service type dimensions;
in the semantic space, performing dimension analysis on the service type of each index in the logistics data is to perform semantic analysis on the service type of each index, namely, taking the service type as a basic vocabulary, and analyzing and determining the dimension of the basic vocabulary, so as to obtain the dimension of the corresponding service type.
In the embodiment, the method of combining the basic vocabulary and the upper and lower level vocabularies is adopted to capture the semantics of the basic vocabulary expression and the semantic relation with other vocabularies. The basic vocabulary is used as the basic formalized vocabulary of the semantic upper and lower vocabularies, the basic vocabulary is the vocabulary which can basically reach consensus, and the semantic upper and lower vocabularies formed by the basic vocabulary are used as the basis of semantic interoperation. The basic vocabulary represents a basic dimension, the upper and lower level vocabularies related to the basic vocabulary represent the upper and lower level dimensions of the semantics, and the dimensional relationship is obtained by analyzing the semantic relationship between the basic vocabulary and the upper and lower level vocabularies. For example, the service type of the first index is "price", the "price" is a basic vocabulary, and represents a basic dimension, and the dimension of the upper and lower vocabularies related to the basic dimension may be "express", "logistics merchant", "rmb", and the like, so that a semantic upper and lower dimensional relationship including information of "price", "express", "logistics merchant", and "rmb" is established, that is, when the service type corresponding to the second index is "logistics merchant", the service types of the first index and the second index are in a semantic dimensional relationship belonging to the upper and lower levels in the semantic dimension.
204, analyzing the semantic dimension of the data meaning of each index to obtain the data meaning dimension;
according to the semantic dimension analysis step, corresponding semantic dimension analysis is also carried out on the data meaning of each index in the semantic space to obtain the data meaning dimension. And dimension analysis is carried out on the data meaning, namely the data meaning is used as a basic vocabulary, whether the basic vocabulary is in semantic relation with the basic vocabulary of the data meaning corresponding to other indexes is analyzed, and the semantic relation is expressed by the dimension.
205, calculating the similarity of the service type dimension and the data meaning dimension in the same index to obtain a dimension similarity value;
206, using the dimension similarity value as a matching value between the data meaning and the service type of the same index;
calculating the similarity of the service type dimension and the data meaning dimension in the same index, namely calculating the semantic similarity of the service type and the data meaning of the same index on the semantic dimension level in a semantic space, specifically, the similarity of the calculation dimension is to analyze whether the service type and the data meaning corresponding to the same index belong to the same semantic dimension, namely, whether the data meaning corresponding to the index is consistent with the semantics of the service type of the index, predefining a calculation rule of the dimension similarity, calling the calculation rule, calculating the dimension similarity of the service type dimension and the data meaning dimension of the same index to obtain a dimension similarity value, wherein the dimension similarity value is a matching value between the data meaning and the service type of the index.
207, judging whether the matching value is smaller than a preset matching threshold value;
208, when the matching value is smaller than a preset matching threshold value, removing corresponding indexes to obtain an index set;
and presetting a matching threshold value for comparing with the matching value, and when the matching value is smaller than the matching threshold value, indicating that the data meaning corresponding to the index and the service type do not belong to the same dimension in a semantic space, namely the data meaning is not matched with the service type, and indicating that the attribute information of the index is wrong, eliminating the index, and summarizing all the indexes after the processing to form an index set.
209, comparing whether the service types of the indexes in the index set are consistent;
210, when the indexes are consistent with the service types of the indexes, summarizing the indexes with consistent service types to obtain at least one data topic domain;
comparing the service types of all the indexes in the index set, comparing whether the service types corresponding to all the indexes are consistent or not, if the service types are consistent, summarizing the indexes corresponding to the service types to form a new index set, wherein the new index set comprises at least one index, and because the service types corresponding to all the indexes are more than one, the obtained new index set is more than one, and the new index set is used as a data theme domain, so that at least one data theme domain can be obtained.
211, establishing a mapping relation between each index in each data topic domain and the data topic domain based on at least one data topic domain;
and establishing a mapping relation between each index in the data subject domains and the data subject domains according to the obtained at least one data subject domain, namely, one data subject domain corresponds to at least one index, and one-to-many mapping relations are presented between the data subject domains and the indexes.
212, carrying out hierarchical division on each index in the mapping relation to obtain an index system;
213, generating an index white paper according to the index system.
In the embodiment of the present invention, the steps 201-.
In the embodiment of the invention, the indexes with wrong attribute information are filtered and removed by calculating the data meaning of the same index and the matching value of the service type, and the indexes with consistent service types are summarized to form a data subject field, thereby eliminating index ambiguity and ensuring the accuracy of the index attribute information.
Referring to fig. 3, a third embodiment of the method for processing a logistics data index according to the embodiment of the invention includes:
301, acquiring logistics data;
302, determining the data meaning of each index in the logistics data and the service type corresponding to each index;
303, classifying a plurality of indexes in the logistics data based on the data meaning and the service type to obtain at least one data subject domain, and establishing a mapping relation between the indexes in each data subject domain and the data subject domain;
304, performing hierarchical analysis of the service types on each index in the mapping relation, sequencing the service types based on the result of the hierarchical analysis, and generating the service levels of all the indexes;
and performing hierarchical analysis on the service types of the corresponding indexes under the data subject domain according to the mapping relation between the data subject domain and the indexes, extracting the service characteristic information of each index in the last step, and analyzing the relevance between the service characteristic information and each service in the logistics industry so as to determine the service types of the corresponding indexes, wherein the corresponding relation exists between each index and each service through the service characteristic information, and the corresponding relation is that one service corresponds to at least one index.
Because there is also relevance between businesses in the logistics industry, that is, there is a hierarchical attribute relationship between businesses, the hierarchical attribute relationship can be analyzed for each index according to the corresponding relationship between the business and the index and the hierarchical attribute relationship between businesses, thereby determining the hierarchical relationship between the indexes. Specifically, the service types corresponding to each index are subjected to hierarchical analysis, the service types are subjected to corresponding hierarchical ordering according to the corresponding hierarchical attribute relationship to obtain service type ordering, then the indexes corresponding to the service types in the service type ordering are subjected to corresponding ordering according to the service type ordering to form hierarchical ordering of all indexes, namely, the service levels of all the indexes are generated.
305, constructing a connection relation among all indexes based on the service levels to obtain index levels;
establishing a connection relation among the indexes according to the obtained service levels of all the indexes, namely establishing a connection relation among the indexes associated with the service level relation, wherein the connection relation includes establishing a connection relation of the same level, establishing a connection relation of an upper level and a lower level, and obtaining the levels of all the indexes after establishing the connection relation among the levels of all the indexes.
306, generating an index system according to the index levels and the mapping relation;
according to the mapping relation between the data theme domain and each index and the hierarchical connection relation between the indexes, all the indexes are hierarchically structured, namely the data theme domain is used as a root node, the corresponding indexes under the data theme domain are used as child nodes, the index hierarchy is used as the hierarchical connection relation between the indexes, and the corresponding child nodes are connected, namely the corresponding indexes are connected, so that an index system is formed.
307, analyzing relevant information of each index in the index system based on the index system to obtain an analysis result;
and analyzing and defining the relevant information of each index in the index system according to the generated index system, wherein the relevant information of each index at least comprises index attributes and index hierarchical relation, namely analyzing the obtained relevant information of each index in the index system in the step, and then defining the standards of each index in the commodity circulation industry to form a uniform index definition, namely eliminating index ambiguity and unifying index calibers.
Specifically, the relationship between the index data meaning and the service type can be analyzed according to different service types and data meanings corresponding to each index in the index system, and then the definition of the data meaning of each index under different service types is determined, namely, the index attribute, the index dimension, the index type of each index under different service types, the condition for creating the index according to the service type and the like are determined; the condition for establishing the connection relation between the indexes can be determined by analyzing the connection relation of each index between the index levels in the index system, and the index level relation is defined; summarizing and summarizing the calculation logics of all indexes in an index system, and defining the calculation logics corresponding to different indexes; and analyzing the related information of each index in the index system, thereby performing unified standardized definition on the related information of each index in the logistics industry to obtain an analysis result.
And 308, performing file conversion on the analysis result based on a preset file conversion rule to generate an index white paper.
In the embodiment of the invention, the file conversion rule is preset, and the file conversion rule can be called to convert the file format to generate the file. Specifically, the analysis result of the relevant information about the indexes obtained in the previous step is converted into a file format, the file format is output, the output text is used as an index white paper, and the relevant information of each index is uniformly managed.
In the embodiment of the present invention, the steps 301-303 are the same as the steps 101-103 in the first embodiment of the method for processing a logistics data index, and are not described herein again.
In the embodiment of the invention, the connection relation among the indexes is constructed, the index system is converted by each index, and the index system is converted into the index white paper, so that the related information of each index is standardized and managed, the index caliber is unified, the index white paper can be conveniently called to perform data analysis on logistics data in the follow-up process, and the data analysis efficiency is improved.
Referring to fig. 4, a fourth embodiment of the method for processing a logistics data index according to the embodiment of the invention includes:
401, acquiring logistics data;
402, determining data meanings of all indexes in the logistics data and service types corresponding to all the indexes;
403, classifying a plurality of indexes in the logistics data based on data meaning and service type to obtain at least one data topic domain, and establishing a mapping relationship between the indexes in each data topic domain and the data topic domain;
404, performing hierarchical division on each index in the mapping relation to obtain an index system;
405, generating an index white paper according to the index system;
406, acquiring source information of the logistics data, and determining an output form of the index system based on the source information;
analyzing and researching the source of each logistics data according to the index level of each index in the logistics data specified in the index white paper to obtain the source information of each logistics data, and determining the output form of the index system corresponding to the logistics data according to the source information of the logistics data.
Specifically, the index white paper may be defined as different index levels divided by different logistics merchants, and each index is analyzed and defined according to the different index levels, so that which logistics merchant the logistics data originates from may be analyzed and researched according to the hierarchy type corresponding to each index in the logistics data in the index white paper, and according to the definition of the logistics merchant on the hierarchy of the index, the output form of the corresponding index system is obtained.
407, extracting indexes with the same data meaning in the same data subject field in the index system according to the output form, and merging to obtain a new index system;
and converting the generated index system into a corresponding output format according to the obtained output form of the index system for outputting, detecting whether indexes with the same data meaning exist in the data meaning of each index under the same data subject field in the output index system, extracting the indexes with the same data meaning, namely performing semantic analysis on the attributes of each index according to the data meaning of each index, and screening the indexes with the same attribute, wherein the indexes with the same attribute refer to the same type and the same meaning of the indexes, namely the indexes are parameters for measuring the same target. And when the indexes with the same data meaning are detected, merging the indexes in the index system to obtain a new index system.
408, encoding each index in the new index system to generate an index code;
and coding each index in the formed new index system, specifically, numbering each index in the new index system for distinguishing each index, wherein the numbering of the indexes can be set as sequencing numbering according to different levels of each index, or different numbering can be directly set according to different services corresponding to the indexes, the specific numbering form is not limited, and after each index in the new index system is numbered, the numbering set for each index is used as index coding.
409, establishing a mapping relation between indexes in a new index system and index codes to obtain an index code system.
And establishing a mapping relation between each index in the new index system and the index code to form a corresponding relation between the index and the index code, namely, the mapping relation is that one index code corresponds to one index, and the conversion from the index system to the index code system can be realized according to the mapping relation between the index and the index code.
In the embodiment of the present invention, the step 401-.
In the embodiment of the invention, the generated output form of the index system is determined, the index system is output in the corresponding output form, each index in the index system is coded, and the mapping relation between the index codes and the indexes is established, so that the conversion from the index system to the index coding system can be automatically completed, the visual analysis result of each index is generated, the labor cost is saved, and the accuracy of the displayed visual analysis result is ensured.
With reference to fig. 5, the method for processing a logistics data index in the embodiment of the present invention is described above, and a device for processing a logistics data index in the embodiment of the present invention is described below, where an embodiment of the device for processing a logistics data index in the embodiment of the present invention includes:
an obtaining module 501, configured to obtain logistics data;
a determining module 502, configured to determine a data meaning of each indicator in the logistics data and a service type corresponding to each indicator;
a classification module 503, configured to perform classification processing on multiple indexes in the logistics data based on the data meaning and the service type to obtain at least one data topic domain, and establish a mapping relationship between the indexes in each data topic domain and the data topic domain;
a hierarchical division module 504, configured to perform hierarchical division on each index in the mapping relationship to obtain an index system;
and a generating module 505, configured to generate an index white paper according to the index system.
According to the embodiment of the invention, the steps of the method for processing the logistics data indexes are executed by the device for processing the logistics data indexes, each index in the logistics data is processed, an index system is automatically constructed, and an index white paper is formed, so that the unified management of the indexes is realized, and the efficiency of the logistics data index processing is improved.
Referring to fig. 6, another embodiment of the device for processing logistics data index according to the embodiment of the invention includes:
an obtaining module 501, configured to obtain logistics data;
a determining module 502, configured to determine a data meaning of each indicator in the logistics data and a service type corresponding to each indicator;
a classification module 503, configured to perform classification processing on multiple indexes in the logistics data based on the data meaning and the service type to obtain at least one data topic domain, and establish a mapping relationship between the indexes in each data topic domain and the data topic domain;
a hierarchical division module 504, configured to perform hierarchical division on each index in the mapping relationship to obtain an index system;
and a generating module 505, configured to generate an index white paper according to the index system.
Optionally, the determining module 502 is specifically configured to:
calling a preset semantic recognition rule, recognizing the semantics of each index in the logistics data, and obtaining the data meaning of each index;
and extracting the service characteristic information in each index, analyzing the relevance between the service characteristic information and each service in the logistics industry, and determining the service type of each index based on the relevance.
Optionally, the classifying module 503 includes:
a calculating unit 5031, configured to calculate a matching value between the data meaning of the same index in the logistics data and the service type;
a determining unit 5032, configured to determine whether the matching value is smaller than a preset matching threshold;
a rejecting unit 5033, configured to reject a corresponding index to obtain an index set when the matching value is smaller than the preset matching threshold;
a comparing unit 5034, configured to compare whether the service types of the indexes in the index set are consistent;
a classifying unit 5035, configured to, when the service types of the indicators are consistent, summarize multiple indicators that the service types are consistent to obtain at least one data topic domain;
a mapping unit 5036, configured to establish a mapping relationship between each indicator in each data topic domain and the data topic domain based on at least one data topic domain.
Optionally, the calculating unit 5031 is specifically configured to:
in a semantic space, performing semantic dimension analysis on the service type of each index in the logistics data to obtain service type dimension;
analyzing the semantic dimension of the data meaning of each index to obtain the data meaning dimension;
calculating the similarity of the service type dimension and the data meaning dimension in the same index to obtain a dimension similarity value;
and using the dimension similarity value as a matching value between the data meaning of the same index and the service type.
Optionally, the hierarchical dividing module 504 is specifically configured to:
performing hierarchical analysis of service types on each index in the mapping relation, sequencing the service types based on the result of the hierarchical analysis, and generating service levels of all the indexes;
constructing a connection relation among the indexes based on the service levels to obtain index levels;
and generating an index system according to the index hierarchy and the mapping relation.
Optionally, the generating module 505 is specifically configured to:
analyzing related information of each index in the index system based on the index system to obtain an analysis result;
and performing file conversion on the analysis result based on a preset file conversion rule to generate an index white paper.
Optionally, the device for processing the logistics data index further includes an updating module 506, which is specifically configured to:
acquiring source information of the logistics data, and determining an output form of the index system based on the source information;
extracting indexes with the same data meaning in the same data subject field in the index system according to the output form, and combining to obtain a new index system;
coding each index in the new index system to generate an index code;
and establishing a mapping relation between the indexes in the new index system and the index codes to obtain an index code system.
In the embodiment of the invention, the processing device of the logistics data index can output a new index system according to different output modes of the index system, and codes each index in the index system to obtain an index coding system, thereby realizing the conversion from the index system to the index coding system.
Referring to fig. 7, an embodiment of a processing apparatus for logistics data index according to an embodiment of the present invention is described in detail below from the perspective of hardware processing.
Fig. 7 is a schematic structural diagram of a processing device for physical distribution data indicators according to an embodiment of the present invention, where the processing device 700 for physical distribution data indicators may generate relatively large differences due to different configurations or performances, and may include one or more processors (CPUs) 710 (e.g., one or more processors) and a memory 720, and one or more storage media 730 (e.g., one or more mass storage devices) for storing an application 733 or data 732. Memory 720 and storage medium 730 may be, among other things, transient storage or persistent storage. The program stored in the storage medium 730 may include one or more modules (not shown), each of which may include a series of instruction operations in the processing device 700 for the logistics data index. Further, the processor 710 may be configured to communicate with the storage medium 730, and execute a series of instruction operations in the storage medium 730 on the processing device 700 of the physical distribution data index.
The logistics data index processing apparatus 700 may also include one or more power supplies 740, one or more wired or wireless network interfaces 750, one or more input-output interfaces 760, and/or one or more operating systems 731, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art will appreciate that the configuration of the processing equipment for the logistics data index shown in FIG. 7 does not constitute a limitation of the processing equipment for the logistics data index, and may include more or fewer components than shown, or some components may be combined, or a different arrangement of components.
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, having stored therein instructions, which, when executed on a computer, cause the computer to perform the steps of the method for processing the logistics data index.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A processing method of logistics data indexes is characterized by comprising the following steps:
acquiring logistics data, wherein the logistics data comprises a plurality of indexes;
determining the data meaning of each index and the service type corresponding to each index in the logistics data;
classifying a plurality of indexes in the logistics data based on the data meaning and the service type to obtain at least one data subject domain, and establishing a mapping relation between the indexes in each data subject domain and the data subject domain, wherein the mapping relation is that one data subject domain corresponds to at least one index;
carrying out hierarchical division on each index in the mapping relation to obtain an index system;
and generating an index white paper according to the index system.
2. The method for processing index of logistics data according to claim 1, wherein the determining the data meaning of each index and the service type corresponding to each index in the logistics data comprises:
calling a preset semantic recognition rule, recognizing the semantics of each index in the logistics data, and obtaining the data meaning of each index;
and extracting the service characteristic information in each index, analyzing the relevance between the service characteristic information and each service in the logistics industry, and determining the service type of each index based on the relevance.
3. The method for processing index of logistics data according to claim 2, wherein the classifying a plurality of indexes in the logistics data based on the data meaning and the service type to obtain at least one data topic domain, and the establishing of the mapping relationship between the index in each data topic domain and the data topic domain comprises:
calculating a matching value between the data meaning of the same index in the logistics data and the service type;
judging whether the matching value is smaller than a preset matching threshold value or not;
if the matching value is smaller than the preset matching threshold value, removing corresponding indexes to obtain an index set;
comparing whether the service types of the indexes in the index set are consistent or not;
if so, summarizing the multiple indexes with the consistent service types to obtain at least one data subject domain;
and establishing a mapping relation between each index in each data subject field and the data subject field based on at least one data subject field.
4. The method for processing index of logistics data as claimed in claim 3, wherein the calculating the matching value between the data meaning and the service type of the same index in the logistics data comprises:
in a semantic space, performing semantic dimension analysis on the service type of each index in the logistics data to obtain service type dimension;
analyzing the semantic dimension of the data meaning of each index to obtain the data meaning dimension;
calculating the similarity of the service type dimension and the data meaning dimension in the same index to obtain a dimension similarity value;
and using the dimension similarity value as a matching value between the data meaning of the same index and the service type.
5. The method for processing index of logistics data according to any one of claims 1 to 4, wherein the step of performing hierarchical division on each index in the mapping relationship to obtain an index system comprises:
performing hierarchical analysis of service types on each index in the mapping relation, sequencing the service types based on the result of the hierarchical analysis, and generating service levels of all the indexes;
constructing a connection relation among the indexes based on the service levels to obtain index levels;
and generating an index system according to the index hierarchy and the mapping relation.
6. The method for processing index of logistics data as claimed in claim 5, wherein said generating index white paper according to the index system comprises:
analyzing related information of each index in the index system based on the index system to obtain an analysis result, wherein the related information at least comprises index attributes and index hierarchical relations;
and performing file conversion on the analysis result based on a preset file conversion rule to generate an index white paper.
7. The method for processing index of logistics data according to any one of claims 1 to 4, wherein after generating index white paper according to the index system, the method further comprises:
acquiring source information of the logistics data, and determining an output form of the index system based on the source information;
extracting indexes with the same data meaning in the same data subject field in the index system according to the output form, and combining to obtain a new index system;
coding each index in the new index system to generate an index code;
and establishing a mapping relation between the indexes in the new index system and the index codes to obtain an index code system.
8. A processing device of logistics data indexes is characterized in that the processing device of logistics data indexes comprises:
the acquisition module is used for acquiring logistics data;
the determining module is used for determining the data meaning of each index in the logistics data and the service type corresponding to each index;
the classification module is used for classifying a plurality of indexes in the logistics data based on the data meaning and the service type to obtain at least one data subject domain and establishing a mapping relation between the indexes in each data subject domain and the data subject domain;
the hierarchical division module is used for carrying out hierarchical division on each index in the mapping relation to obtain an index system;
and the generating module is used for generating an index white paper according to the index system.
9. A processing device of logistics data indexes is characterized in that the processing device of logistics data indexes comprises:
a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;
the at least one processor invokes the instructions in the memory to cause the network access probe device to perform the steps of the method of processing the logistics data indicator of any one of claims 1-7.
10. A computer-readable storage medium having instructions stored thereon, wherein the instructions, when executed by a processor, implement the steps of the method for processing logistics data indicators of any one of claims 1-7.
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| CN114881508A (en) * | 2022-05-24 | 2022-08-09 | 中国能源建设集团广东省电力设计研究院有限公司 | Data processing method, device and equipment for power grid index report |
| CN115858691A (en) * | 2022-11-17 | 2023-03-28 | 北京白龙马云行科技有限公司 | Report creation method and device, electronic equipment and medium |
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| CN114881508A (en) * | 2022-05-24 | 2022-08-09 | 中国能源建设集团广东省电力设计研究院有限公司 | Data processing method, device and equipment for power grid index report |
| CN115858691A (en) * | 2022-11-17 | 2023-03-28 | 北京白龙马云行科技有限公司 | Report creation method and device, electronic equipment and medium |
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