Highway data element collection method and device and electronic equipment

Abstract

The invention relates to the technical field of data processing, in particular to an expressway data element collection method and device and electronic equipment. The method comprises the following steps: acquiring a data dictionary from a business system of an expressway; constructing a plurality of data classification dictionaries according to the description information of the data dictionaries; performing word segmentation processing on each data classification dictionary, and removing semantic irrelevant words from a word segmentation result to obtain a word segmentation text; and determining at least one data element from the word segmentation texts according to the similarity between the word segmentation texts, and collecting the at least one data element into a database. By the adoption of the method, the problem that in the business scene of the expressway, when a data table and a data field reach tens of thousands of orders of magnitude, huge data verification is difficult to complete manually, and consequently the quality of input or collected data is low is solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device and electronic equipment for collecting highway data elements. Background Art

[0002] With the widespread application of information technology and Internet technology, highway toll collection systems generate a large amount of vehicle traffic data every day. These data include toll information, infrastructure information, monitoring information, operation and maintenance information, etc. It is of great significance to collect and classify data elements of highway toll collection, operation and maintenance, monitoring and other data, and then verify the existing data based on data elements to ensure data quality and improve the quality and efficiency of the toll collection system.

[0003] At present, the existing data element collection and classification methods are suitable for scenarios with fewer data tables and data fields. When the number of data tables and data fields reaches tens of thousands, it is difficult to complete such a large amount of data verification manually, and the quality of the entered or collected data is low. Summary of the invention

[0004] The present invention provides a method, device and electronic device for collecting highway data elements, which are used to solve the problem that in highway business scenarios, when data tables and data fields reach tens of thousands, it is difficult to manually complete such a large amount of data verification, resulting in low quality of input or collected data.

[0005] The present invention provides a method for collecting highway data elements, comprising the following steps: Get the data dictionary from the expressway's business system; Constructing multiple data classification dictionaries according to the description information of the data dictionary; Performing word segmentation processing on each of the data classification dictionaries, and removing semantically irrelevant words from the word segmentation results to obtain a word segmentation text; According to the similarity between the segmented texts, at least one data element is determined from the segmented texts, and the at least one data element is aggregated into a database.

[0006] According to the method for collecting highway data elements provided by the present invention, the method of constructing multiple data classification dictionaries based on the description information of the data dictionary includes: Performing Chinese word segmentation processing on the Chinese description information of the data dictionary, and constructing a Chinese data classification dictionary according to the Chinese word segmentation result; Mapping the Chinese word segmentation results into pinyin words, and constructing a pinyin data classification dictionary based on the pinyin words; Determine the mapping relationship between the Chinese word segmentation data in the Chinese word segmentation result, the mapping relationship includes an equivalence relationship, a containment relationship and a synonym relationship, and construct a Chinese synonym data classification dictionary according to the mapping relationship.

[0007] According to the method for collecting highway data elements provided by the present invention, the step of constructing multiple data classification dictionaries based on the description information of the data dictionary further includes: If there is English description information in the description information of the data dictionary, perform English word segmentation processing on the English description information of the data dictionary, and construct an English data classification dictionary according to the English word segmentation result; Determine the mapping relationship between the English word segmentation data in the English word segmentation result, wherein the mapping relationship includes an equivalence relationship, a containment relationship, and a synonym relationship, and construct an English synonym data classification dictionary according to the mapping relationship.

[0008] According to the method for collecting highway data elements provided by the present invention, the word segmentation processing is performed on each of the data classification dictionaries, and semantically irrelevant words are removed from the word segmentation results to obtain the word segmentation text, which specifically includes: Taking each of the data classification dictionaries as a data element to be identified, and performing preliminary segmentation on the data element to be identified according to stop words; The data elements to be identified after preliminary segmentation are segmented, and semantically irrelevant words are removed from the segmentation results to obtain segmented text.

[0009] According to the method for collecting highway data elements provided by the present invention, determining at least one data element from the segmented texts according to the similarity between the segmented texts, and collecting the at least one data element into a database, comprises: The similarity between each of the segmented texts is calculated, and the segmented texts with similarity greater than or equal to a preset similarity threshold are merged to obtain data elements, which are then aggregated into a database.

[0010] According to the method for collecting highway data elements provided by the present invention, the method further comprises: determining at least one data element from the segmented texts according to the similarity between the segmented texts, and collecting the at least one data element into a database; If the similarity between any of the segmented texts and the other segmented texts is less than a preset similarity threshold, they are directly taken as data elements and collected into the database.

[0011] The present invention also provides a device for collecting highway data elements, comprising: A data acquisition unit, used to obtain a data dictionary from the highway's business system; A data classification unit, used for constructing a plurality of data classification dictionaries according to the description information of the data dictionary; A data processing unit, used for performing word segmentation processing on each of the data classification dictionaries, and removing semantically irrelevant words from the word segmentation results to obtain a word segmentation text; The data collection unit is used to determine at least one data element from the segmented texts according to the similarity between the segmented texts, and collect the at least one data element into a database.

[0012] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for collecting highway data elements as described above is implemented.

[0013] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method for collecting highway data elements as described in any one of the above is implemented.

[0014] The present invention also provides a computer program product, including a computer program, wherein when the computer program is executed by a processor, the method for collecting highway data elements as described in any one of the above is implemented.

[0015] The method, device and electronic device for collecting highway data elements provided by the present invention automatically obtain a data dictionary from the business system of the highway and construct and classify data elements based on the data dictionary, thereby achieving efficient and accurate processing of large-scale data tables and data fields, significantly improving the efficiency of data verification and the quality of data entry, thereby ensuring the stability and operating efficiency of the highway toll collection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 This is one of the flow charts of the method for collecting highway data elements provided by the present invention.

[0018] Figure 2 This is the second flow chart of the method for collecting highway data elements provided by the present invention.

[0019] Figure 3 This is the third flow chart of the method for collecting highway data elements provided by the present invention.

[0020] Figure 4It is a structural schematic diagram of the highway data element collection device provided by the present invention.

[0021] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the descriptions used in this way can be interchanged where appropriate, so that the embodiments can be implemented in a sequence other than that illustrated or described in the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. The naming or numbering of the steps that appear in the present application does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The process steps that have been named or numbered can change the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved. The division of modules in this application is a logical division. There may be other division methods when it is implemented in actual applications. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection between units can be electrical or other similar forms, which are not limited in this application. In addition, the modules or submodules described as separate components may or may not be physically separated, may or may not be physical units, or may be distributed in multiple circuit units, and some or all of the units may be selected according to actual needs to achieve the purpose of the present application.

[0024] The present invention provides an efficient and automated highway data element collection method, device and electronic equipment to cope with the data verification and classification problems in the case of large-scale data tables and data fields, thereby improving data quality and system efficiency.

[0025] Combine the following Figure 1-Figure 5 The specific contents of the present invention are described.

[0026] Figure 1 It is a flowchart of a method for collecting highway data elements provided by the present invention, including steps S101-S104.

[0027] Step S101, obtaining a data dictionary from a highway business system.

[0028] Specifically, the highway toll collection system generates a large amount of vehicle traffic data every day. These data include toll information, infrastructure information, monitoring information, operation and maintenance information, etc. The highway business system in the embodiment of the present invention includes but is not limited to the business data collected by various types of business systems constructed in the above business scenarios, and obtains a data dictionary.

[0029] In the embodiment of the present invention, the data dictionary includes data fields and description information. The data dictionary is written into a MySQL database and stored in a classified and graded manner according to the business type.

[0030] Step S102: construct multiple data classification dictionaries according to the description information of the data dictionary.

[0031] In the embodiments of the present invention, for a data dictionary generated in any business scenario, its description information characterizes the data features of the data dictionary. Based on the description information, multiple different types of data classification dictionaries are constructed, including but not limited to the Chinese data classification dictionary, Pinyin data classification dictionary, Chinese synonym data classification dictionary, English data classification dictionary, and English synonym data classification dictionary in the following embodiments. Different types of data classification dictionaries can meet the data processing requirements under different scenarios and needs.

[0032] Step S103, performing word segmentation processing on each data classification dictionary, and removing semantically irrelevant words from the word segmentation results to obtain a word segmentation text.

[0033] Specifically, before calculating the similarity between the segmented texts, semantically irrelevant words are removed to improve the accuracy of the subsequent data element determination process.

[0034] Step S104, determining at least one data element from the segmented texts according to the similarity between the segmented texts, and grouping the at least one data element into a database.

[0035] Specifically, according to the similarity between the segmented texts, the texts in the segmented texts are merged and differentiated to reduce the amount of data elements collected in the database. For details, please refer to the subsequent embodiments.

[0036] In a possible implementation, Figure 2 As shown, in step S102, multiple data classification dictionaries are constructed according to the description information of the data dictionary, including steps S201-S203.

[0037] Step S201 , performing Chinese word segmentation processing on the Chinese description information of the data dictionary, and constructing a Chinese data classification dictionary according to the Chinese word segmentation result.

[0038] In the embodiment of the present invention, a word segmentation plug-in is used to perform word segmentation processing on the Chinese description information of the data dictionary, and the Chinese word segmentation results are stored in the word library table of the Mysql database. Later, the word library table is queried as needed, and the Chinese data classification dictionary is constructed or updated according to the words in the word library table. The Chinese data classification dictionary is stored in the Mysql database as a row of a data table, and the table structure is converted into a dictionary tree structure and stored in the memory.

[0039] Step S202, mapping the Chinese word segmentation results into pinyin words, and constructing a pinyin data classification dictionary based on the pinyin words.

[0040] In an embodiment of the present invention, the Chinese word segmentation result in step S201 is mapped to pinyin words, and a pinyin data classification dictionary is constructed based on the pinyin words. Pinyin words include: full pinyin, partial full pinyin, initial lowercase abbreviation, initial uppercase abbreviation or more; the pinyin data classification dictionary is stored in the memory in the structure of a pinyin word table, and each pinyin word is a node in the pinyin word table.

[0041] Step S203, determining the mapping relationship between the Chinese word segmentation data in the Chinese word segmentation result, the mapping relationship includes an equivalence relationship, a containment relationship and a synonym relationship, and constructing a Chinese synonym data classification dictionary according to the mapping relationship.

[0042] In an embodiment of the present invention, a mapping relationship between Chinese word segmentation data in a Chinese word segmentation result is established and stored in a Mysql database table, and the mapping relationship between Chinese word segmentation data includes: equivalence, inclusion, and synonymy. By regularly querying the Mysql database table, a synonym data classification dictionary is constructed according to the mapping relationship therein, and the synonym data classification dictionary uses a linked list or a tree to store data.

[0043] In a possible implementation, Figure 3 As shown, in step S102, multiple data classification dictionaries are constructed according to the description information of the data dictionary, and steps S301-S302 are also included.

[0044] Step S301: If there is English description information in the description information of the data dictionary, English word segmentation is performed on the English description information of the data dictionary, and an English data classification dictionary is constructed according to the English word segmentation result.

[0045] In an embodiment of the present invention, if there is English description information in the description information of the data dictionary, an English data classification dictionary of the English description information is constructed. The English description information separates English words with spaces, constructs an English dictionary tree, and establishes a mapping relationship between English words to construct an English data classification dictionary.

[0046] In a possible implementation, if there is no English description information in the description information of the data dictionary, and the data field of the data dictionary contains English, an English data classification dictionary is constructed according to the data field. Exemplarily, the English data classification dictionary is formed by separating words according to "_", "-", " " or camel case capital letters in the field data.

[0047] Step S302, determining the mapping relationship between the English word segmentation data in the English word segmentation result, the mapping relationship includes an equivalence relationship, a containment relationship and a synonym relationship, and constructing an English synonym data classification dictionary according to the mapping relationship.

[0048] In the embodiment of the present invention, the mapping relationship between English word segmentation data can refer to the construction process of the mapping relationship between the above-mentioned Chinese word segmentation data, and the present invention will not go into details here.

[0049] In a possible implementation, in step S103, each data classification dictionary is segmented, and semantically irrelevant words are removed from the segmentation results to obtain segmented text, which specifically includes: Each data classification dictionary is used as a data element to be identified, and the data element to be identified is preliminarily segmented according to stop words; the data element to be identified after the preliminary segmentation is segmented, and semantically irrelevant words are removed from the segmentation results to obtain the segmented text.

[0050] Specifically, each data classification dictionary is segmented, and in the segmentation results, semantic analysis is performed on the segmented words and business-irrelevant words are removed. For example, the primary key ID field of the data dictionary can be described in Chinese as a unique identifier, identifier, etc. This type of business-irrelevant word dictionary is constructed, and fields or field descriptions found in the business-irrelevant word dictionary are removed to ensure that only meaningful data is retained.

[0051] In a possible implementation, in step S104, based on the similarity between the segmented texts, at least one data element is determined from the segmented texts, and the at least one data element is aggregated into a database, including: calculating the similarity between the segmented texts, merging the segmented texts whose similarity is greater than or equal to a preset similarity threshold to obtain data elements, and aggregating the data elements into the database.

[0052] In the embodiment of the present invention, the similarity between each segmented text is calculated by using cosine similarity.

[0053] For example, a data classification dictionary is segmented to obtain segmented texts A, B, and C; if the similarity between segmented text A and segmented text B is greater than or equal to a preset similarity threshold; the similarity between segmented text A and segmented text C is less than the preset similarity threshold; the similarity between segmented text B and segmented text C is less than the preset similarity threshold. Then the segmented texts A and B are merged to obtain a data element and aggregated into a database; at the same time, the segmented text C is taken as a separate data element and aggregated into the database.

[0054] In a possible implementation, in step S104, according to the similarity between the segmented texts, at least one data element is determined from the segmented texts, and the at least one data element is aggregated into a database, further comprising: If the similarity between any segmented text and other segmented texts is less than the preset similarity threshold, it will be directly used as a data element and collected into the database.

[0055] The present invention can achieve the following beneficial effects by adopting the above method: 1. By automatically acquiring data dictionaries from the highway business system and building a data classification system based on these data dictionaries, the initial sorting and classification of massive data is achieved. This step lays a solid foundation for subsequent data processing, verification and collection, significantly improves the automation level of the data processing process, reduces manual intervention, and thus improves overall work efficiency and data processing accuracy.

[0056] 2. Construct various types of data classification dictionaries through the description information of the data dictionary, including Chinese, Pinyin, Chinese synonyms, etc. The multi-level and multi-dimensional classification method not only enhances the accuracy of data classification, but also improves the flexibility of data processing. By constructing a synonym data classification dictionary, it can effectively solve the classification inconsistency problem caused by expression differences, and further improve the consistency of data.

[0057] 3. The scope of data classification dictionary construction has been expanded to include the processing of English description information. The construction of English synonym data classification dictionary helps to achieve more accurate data classification and verification in the English environment, improving the accuracy and efficiency of overall data processing.

[0058] 4. Automatic merging and classification of similar data items are realized, avoiding data redundancy and duplication. At the same time, the introduction of preset similarity thresholds makes the determination of data elements more flexible and controllable, further improving the accuracy and efficiency of data classification.

[0059] The following is a description of the highway data element collection device provided by the present invention. The highway data element collection device described below and the highway data element collection method described above can be referred to each other.

[0060] Figure 4 A schematic diagram of the structure of a highway data element collection device provided by the present invention includes the following parts: The data acquisition unit 410 is used to obtain a data dictionary from the business system of the expressway.

[0061] The data classification unit 420 is used to construct multiple data classification dictionaries according to the description information of the data dictionary.

[0062] The data processing unit 430 is used to perform word segmentation processing on each data classification dictionary and remove semantically irrelevant words from the word segmentation results to obtain the word segmentation text.

[0063] The data collection unit 440 is used to determine at least one data element from the segmented texts according to the similarity between the segmented texts, and collect the at least one data element into a database.

[0064] In a possible implementation, the data classification unit 420 is specifically configured to: Perform Chinese word segmentation on the Chinese description information in the data dictionary, and build a Chinese data classification dictionary based on the Chinese word segmentation results; Map the Chinese word segmentation results into pinyin words, and build a pinyin data classification dictionary based on the pinyin words; Determine the mapping relationship between the Chinese word segmentation data in the Chinese word segmentation result, the mapping relationship includes an equivalence relationship, a containment relationship and a synonym relationship, and build a Chinese synonym data classification dictionary based on the mapping relationship.

[0065] In a possible implementation, the data classification unit 420 is specifically configured to: If there is English description information in the description information of the data dictionary, perform English word segmentation on the English description information of the data dictionary, and construct an English data classification dictionary based on the English word segmentation result; Determine the mapping relationship between the English word segmentation data in the English word segmentation results, the mapping relationship includes an equivalence relationship, a containment relationship and a synonym relationship, and build an English synonym data classification dictionary based on the mapping relationship.

[0066] In a possible implementation manner, the data processing unit 430 is specifically configured to: Each data classification dictionary is used as a data element to be identified, and the data element to be identified is preliminarily segmented according to stop words; The data elements to be identified after preliminary segmentation are segmented, and semantically irrelevant words are removed from the segmentation results to obtain the segmented text.

[0067] In a possible implementation, the data collection unit 440 is specifically configured to: The similarity between each segmented text is calculated, and the segmented texts with similarity greater than or equal to the preset similarity threshold are merged to obtain data elements, which are then collected into the database.

[0068] In a possible implementation manner, the data collection unit 440 is further configured to: If the similarity between any segmented text and other segmented texts is less than the preset similarity threshold, it will be directly used as a data element and collected into the database.

[0069] Figure 5 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 5 As shown, the electronic device may include: a processor 510, a communications interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communications interface 520 and the memory 530 communicate with each other via the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute a method for collecting highway data elements, the method comprising: Get the data dictionary from the expressway's business system; Construct multiple data classification dictionaries based on the description information of the data dictionary; Perform word segmentation on each data classification dictionary and remove semantically irrelevant words from the word segmentation results to obtain the word segmentation text; According to the similarity between the segmented texts, at least one data element is determined from the segmented texts, and the at least one data element is aggregated into a database.

[0070] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0071] On the other hand, the present invention further provides a computer program product, the computer program product includes a computer program, the computer program can be stored in a non-transitory computer-readable storage medium, when the computer program is executed by a processor, the computer can execute a method for collecting highway data elements provided by the above methods, the method comprising: Get the data dictionary from the expressway's business system; Construct multiple data classification dictionaries based on the description information of the data dictionary; Perform word segmentation on each data classification dictionary and remove semantically irrelevant words from the word segmentation results to obtain the word segmentation text; According to the similarity between the segmented texts, at least one data element is determined from the segmented texts, and the at least one data element is aggregated into a database.

[0072] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for collecting highway data elements provided by the above methods is implemented, and the method comprises: Get the data dictionary from the expressway's business system; Construct multiple data classification dictionaries based on the description information of the data dictionary; Perform word segmentation on each data classification dictionary and remove semantically irrelevant words from the word segmentation results to obtain the word segmentation text; According to the similarity between the segmented texts, at least one data element is determined from the segmented texts, and the at least one data element is aggregated into a database.

[0073] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0074] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0075] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for collecting highway data elements, characterized in that: include: Get the data dictionary from the expressway's business system; Constructing multiple data classification dictionaries according to the description information of the data dictionary; Performing word segmentation processing on each of the data classification dictionaries, and removing semantically irrelevant words from the word segmentation results to obtain a word segmentation text; According to the similarity between the segmented texts, at least one data element is determined from the segmented texts, and the at least one data element is aggregated into a database.

2. The highway data element collection method according to claim 1 is characterized in that: The step of constructing a plurality of data classification dictionaries according to the description information of the data dictionary includes: Performing Chinese word segmentation processing on the Chinese description information of the data dictionary, and constructing a Chinese data classification dictionary according to the Chinese word segmentation result; Mapping the Chinese word segmentation results into pinyin words, and constructing a pinyin data classification dictionary based on the pinyin words; Determine the mapping relationship between the Chinese word segmentation data in the Chinese word segmentation result, the mapping relationship includes an equivalence relationship, a containment relationship and a synonym relationship, and construct a Chinese synonym data classification dictionary according to the mapping relationship.

3. The highway data element collection method according to claim 2 is characterized in that: The step of constructing a plurality of data classification dictionaries according to the description information of the data dictionary further includes: If there is English description information in the description information of the data dictionary, perform English word segmentation processing on the English description information of the data dictionary, and construct an English data classification dictionary according to the English word segmentation result; Determine the mapping relationship between the English word segmentation data in the English word segmentation result, wherein the mapping relationship includes an equivalence relationship, a containment relationship, and a synonym relationship, and construct an English synonym data classification dictionary according to the mapping relationship.

4. The highway data element collection method according to claim 1, characterized in that: The word segmentation process is performed on each of the data classification dictionaries, and semantically irrelevant words are removed from the word segmentation results to obtain the word segmentation text, which specifically includes: Taking each of the data classification dictionaries as a data element to be identified, and performing preliminary segmentation on the data element to be identified according to stop words; The data elements to be identified after preliminary segmentation are segmented, and semantically irrelevant words are removed from the segmentation results to obtain segmented text.

5. The method for collecting highway data elements according to claim 1, characterized in that: The step of determining at least one data element from the segmented texts according to the similarity between the segmented texts, and collecting the at least one data element into a database includes: The similarity between each of the segmented texts is calculated, and the segmented texts with similarity greater than or equal to a preset similarity threshold are merged to obtain data elements, which are then aggregated into a database.

6. The method for collecting highway data elements according to claim 5, characterized in that: The method of determining at least one data element from the segmented texts according to the similarity between the segmented texts, and collecting the at least one data element into a database, further includes: If the similarity between any of the segmented texts and the other segmented texts is less than a preset similarity threshold, they are directly taken as data elements and collected into the database.

7. A device for collecting highway data elements, characterized in that: include: A data acquisition unit, used to obtain a data dictionary from the highway's business system; A data classification unit, used for constructing a plurality of data classification dictionaries according to the description information of the data dictionary; A data processing unit, used for performing word segmentation processing on each of the data classification dictionaries, and removing semantically irrelevant words from the word segmentation results to obtain a word segmentation text; The data collection unit is used to determine at least one data element from the segmented texts according to the similarity between the segmented texts, and collect the at least one data element into a database.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for collecting highway data elements according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for collecting highway data elements according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for collecting highway data elements according to any one of claims 1 to 6 is implemented.

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