CN113609407B - Regional consistency verification method and device - Google Patents
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- G—PHYSICS
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Abstract
The invention discloses a regional consistency verification method and device, a storage medium and electronic equipment, wherein the method comprises the following steps: acquiring enterprise detailed information of a target enterprise, wherein the enterprise detailed information comprises display area information; determining first region information of the target enterprise according to the enterprise detailed information; and carrying out region consistency check on the target enterprise according to the first region information and the display region information, and obtaining a region consistency check result. By analyzing the enterprise detailed information, the method and the device can accurately determine the region where the enterprise is located, and perform region consistency check according to the determined region where the enterprise is located, so that enterprises with inconsistent regions can be efficiently and rapidly determined, the accuracy of the displayed enterprise detailed information can be effectively improved, and the user experience is improved.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method and apparatus for verifying regional consistency, and a storage medium and an electronic device.
Background
The region where the enterprise is located is one of enterprise information which is generally focused on by users. However, since the region where the enterprise is located is not directly disclosed data, but the information dimension related to the enterprise is more, and the problems of complex data and low reliability exist, how to automatically and accurately identify the region where the enterprise is located from the disclosed information related to the enterprise is a technical problem which is difficult to solve at present.
The existing technical scheme mainly determines the region where the enterprise is located in a manual calibration mode, so that the problems of low efficiency and low accuracy exist. And when the calibrated enterprise area is inconsistent with the actual enterprise area, the problem cannot be automatically and rapidly found, so that the user experience degree is poor.
Disclosure of Invention
The method and the device solve the problems that the regional information displayed by the enterprise is inconsistent with the regional information actually located by the enterprise, so that the regional information needs to be checked, the region where the enterprise is located is deduced according to the enterprise detailed information of the enterprise, and the regional information displayed by the enterprise is checked, so that the accuracy of the regional information displayed by the enterprise is determined.
The invention is provided for solving the technical problems of deducing the region where the enterprise is located and checking the region information displayed by the enterprise. The embodiment of the invention provides a regional consistency verification method and device, a storage medium and electronic equipment.
According to an aspect of the embodiment of the present invention, there is provided a region consistency check method, including:
acquiring enterprise detailed information of a target enterprise, wherein the enterprise detailed information comprises display area information;
Determining first region information of the target enterprise according to the enterprise detailed information;
and carrying out region consistency check on the target enterprise according to the first region information and the display region information, and obtaining a region consistency check result.
Preferably, the method further comprises:
traversing the database according to a preset time interval to obtain enterprise detailed information of the target enterprise.
Preferably, the determining the first region information of the target enterprise according to the enterprise detailed information includes:
when the tax payer identification number dimension in the enterprise detailed information has data, extracting data for identifying first region information from the tax payer identification number, determining region words according to the data of the first region information, and taking the region words as the first region information of the target enterprise.
Preferably, the method further comprises:
and extracting the data for identifying the first region information according to the number of digits of the tax payer identification number and a preset extraction rule.
Preferably, the method further comprises:
when the dimension of the tax payer identification number in the enterprise detailed information is empty or the first region information cannot be determined according to the tax payer identification number, determining the first region information of the target enterprise according to the preset first dimension information of the first dimension in the enterprise detailed information.
Preferably, the determining the first regional information of the target enterprise according to the first dimension information of the preset first dimension in the enterprise detailed information includes:
word segmentation is carried out on the first dimension information so as to obtain regional words in the first dimension information;
determining the word weight of each regional word in the first dimension information, sequencing the word weights, and determining the first word weight according to the maximum word weight;
when the first word weight is greater than or equal to a preset word weight threshold, determining first region information of the target enterprise according to a first region word corresponding to the first word weight.
Preferably, the method further comprises:
and when the first word weight is smaller than a preset word weight threshold, determining a first global voting weight of a first regional word corresponding to the first word weight.
Preferably, the preset first dimension is a annual report dimension.
Preferably, the method further comprises:
determining the dimension of the tax payer identification number and the preset first dimension in the enterprise detailed information as a second dimension;
and determining a second global voting weight of a second regional word in each second dimension information according to a preset strategy according to the type of the second dimension information of the second dimension.
Preferably, the determining, according to a preset policy, the second global voting weight of the second regional word in each second dimension information according to the type of the second dimension information of the second dimension includes:
when the type of second dimension information of the second dimension is a text type, word segmentation is carried out on the second dimension information to obtain regional words in the second dimension information, word weights of each regional word in the second dimension information are calculated, word weights are ordered, the second word weights are determined according to the largest word weights, and second global voting weights of the second regional words corresponding to the second word weights are calculated;
and when the type of the second dimension information of the second dimension is IP or telephone number, inquiring the attribution according to the second dimension information to acquire second regional words in the second dimension information, and performing global voting weight matching according to the type of the second dimension information to determine a second global voting weight of each second regional word.
Preferably, the method further comprises: and counting according to the global voting weight of the first regional word and the global voting weight of the second regional word, determining the total global voting weight of the same regional word, and determining the first regional information of the target enterprise according to the regional word with the maximum total global voting weight.
Preferably, the method further comprises:
splitting the dimension information, obtaining regional words in the dimension information, and counting word frequency of each regional word in the dimension information;
for any regional word, determining the weight of the any regional word according to the preset keyword in the above where the any regional word is located, and determining the word weight of the any regional word according to the weight and word frequency of the any regional word.
Preferably, the method further comprises: for any regional word, determining the weight corresponding to each sentence with the regional word according to the preset keyword in the context of each sentence with the regional word, and selecting the maximum weight as the weight of the any regional word.
Preferably, the determining the first region information of the target enterprise according to the enterprise detailed information includes:
determining regional words according to the enterprise detailed information;
acquiring the word weight of the regional word; and
and taking the regional word and the word right of the regional word as first regional information of the target enterprise.
Preferably, the method further comprises:
when the regional consistency check result indicates that the first regional information is inconsistent with the display regional information in the enterprise detailed information, determining that the target enterprise is abnormal, and sending abnormal warning information to a monitoring terminal.
According to still another aspect of the embodiment of the present invention, there is provided a region consistency check apparatus, the apparatus including:
the enterprise detailed information acquisition module is used for acquiring enterprise detailed information of a target enterprise, wherein the enterprise detailed information comprises display area information;
the first region information determining module is used for determining first region information of the target enterprise according to the enterprise detailed information;
and the verification module is used for carrying out region consistency verification on the target enterprise according to the first region information and the display region information, and obtaining a region consistency verification result.
According to a further aspect of an embodiment of the present invention, there is provided a computer readable storage medium, wherein the computer readable storage medium stores a computer program for executing the method according to any one of the above embodiments of the present invention.
According to still another aspect of an embodiment of the present invention, there is provided an electronic device, including: a memory and a processor; wherein,
the memory is used for storing the processor executable instructions;
the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any of the foregoing embodiments of the present invention.
By analyzing the enterprise detailed information, the method and the device can accurately determine the region where the enterprise is located, and perform region consistency check according to the determined region where the enterprise is located, so that enterprises with inconsistent regions can be efficiently and rapidly determined, the accuracy of the displayed enterprise detailed information can be effectively improved, and the user experience is improved.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
Exemplary embodiments of the present invention may be more completely understood in consideration of the following drawings:
FIG. 1 is a flow chart of a region consistency check method 100 provided in accordance with an exemplary embodiment of the present invention;
FIG. 2 is a flowchart of a method 200 for determining first regional information of a target enterprise based on annual report information, in accordance with an exemplary embodiment of the present invention;
FIG. 3 is a schematic diagram of a region consistency check device 300 according to an exemplary embodiment of the present invention;
fig. 4 is a structure of an electronic device provided in an exemplary embodiment of the present invention.
Detailed Description
Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present invention and not all embodiments of the present invention, and it should be understood that the present invention is not limited by the example embodiments described herein.
It should be noted that: the relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.
It will be appreciated by those of skill in the art that the terms "first," "second," etc. in embodiments of the present invention are used merely to distinguish between different steps, devices or modules, etc., and do not represent any particular technical meaning nor necessarily logical order between them.
It should also be understood that in embodiments of the present invention, "plurality" may refer to two or more, and "at least one" may refer to one, two or more.
It should also be appreciated that any component, data, or structure referred to in an embodiment of the invention may be generally understood as one or more without explicit limitation or the contrary in the context.
In addition, the term "and/or" in the present invention is merely an association relationship describing the association object, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist together, and B exists alone. In the present invention, the character "/" generally indicates that the front and rear related objects are an or relationship.
It should also be understood that the description of the embodiments of the present invention emphasizes the differences between the embodiments, and that the same or similar features may be referred to each other, and for brevity, will not be described in detail.
Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.
The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the techniques, methods, and apparatus should be considered part of the specification.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
Embodiments of the invention are operational with numerous other general purpose or special purpose computing system environments or configurations with electronic devices, such as terminal devices, computer systems, servers, etc. Examples of well known terminal devices, computing systems, environments, and/or configurations that may be suitable for use with the terminal device, computer system, server, or other electronic device include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, mainframe computer systems, and distributed cloud computing technology environments that include any of the foregoing, and the like.
Electronic devices such as terminal devices, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. The computer system/server may be implemented in a distributed cloud computing environment in which tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including memory storage devices.
Exemplary method
Fig. 1 is a flowchart of a region consistency check method 100 according to an exemplary embodiment of the present invention. The embodiment can be applied to an electronic device, as shown in fig. 1, and includes the following steps:
step 101, acquiring enterprise detailed information of a target enterprise, wherein the enterprise detailed information comprises display area information.
The enterprise detailed information includes: tax payer identification number, annual report, telephone number, company name, etc., and also includes a plurality of dimensions for displaying region information for display, etc. The dimension information such as tax payer identification number, annual report, telephone number and the like may be null.
In some alternative embodiments, enterprise details of the target enterprise may also be obtained by: traversing the database according to a preset time interval to obtain enterprise detailed information of the target enterprise.
The enterprise detailed information of the enterprise can also be acquired from the database through the enterprise detailed information acquisition interface. When the enterprise detailed information is acquired, a target enterprise can be customized, and the enterprise detailed information of all the companies in the database can be traversed according to preset time.
For example, in one embodiment of the present invention, enterprise details of all enterprises in the database are obtained once a week at preset time intervals. The business details of each business are a record. For example, the enterprise details of a certain enterprise a include: the tax payer identification number is "1234567890112345", the annual report information is "the headquarter of the company is located in Beijing, there are five branches and the like", the telephone number is "18888888888", the company name "A Limited company" and the display area information "Beijing".
And 102, determining first region information of the target enterprise according to the enterprise detailed information.
Taking the example that the enterprise detailed information includes a tax payer identification number, determining the first region information of the target enterprise according to the enterprise detailed information includes: when the tax payer identification number dimension in the enterprise detailed information has data, extracting data for identifying first region information from the tax payer identification number, determining region words according to the data of the first region information, and taking the region words as the first region information of the target enterprise.
In some alternative embodiments, the preset extraction rule corresponding to the expected number of digits of the tax payer identification number may be determined, and the data for identifying the first region information may be extracted based on the preset extraction rule.
For example, in the present invention, the first region information may be determined according to the tax payer identification number. The taxpayer identification number is typically 15, 17, 18 or 20 bits. The tax payer identification number comprises the following components:
(1) 15 bits: the code of tax payer issued by the national tax administration is 15 bits, wherein: 1-2 bits are province and city codes, 3-6 bits are region codes, 7-8 bits are economic property codes, 9-10 bits are industry codes, and 11-15 bits are sequence codes which are self-arranged in all places;
(2) 17 bits: 15 resident identification card number+2 digit sequence code;
(3) 18 bits: 18 resident identification card numbers;
(4) 20 bits: 18 resident identification card number+2 digit sequence codes (01 to 99).
Part of the tax payer identification number contains boss identification card information. For example, an individual business merchant uses a resident identification number (18 digits or 15 digits) as its "tax payer identification number".
In this embodiment of the present invention, the extraction rule for identifying the data of the first region information is set as: when the taxpayer identification number is 15, 17, 18, or 20 bits, the first 1-6 bits are extracted as data for identifying the first region information. Then, the first region information is determined based on the extracted data for identifying the first region information and the number of digits of the taxpayer identification number. Wherein, different zone information databases are associated with tax payer identification numbers with different digits, therefore, the zone information databases can be determined according to the tax payer identification numbers, and then the data for identifying the first zone information and the zone information are matched from the selected zone information databases, so as to determine the first zone information. The regional information of about 95% of enterprises is accurately identified by the tax payer identification number.
For example, the area information database a corresponds to the tax payer identification number of 15 bits, and the area information database B corresponds to the tax payer identification number of 17, 18, or 20 bits. When the tax payer identification number is "11010098765432111", the tax payer identification number is determined to be 17 bits first, the corresponding regional information database is determined to be B, then the first 6 bits are extracted to be "110100", and the regional information corresponding to "110100" is matched in the regional information database B to be "beijing", so that the first regional information can be determined to be "beijing".
In some optional embodiments, when the dimension of the tax payer identification number in the enterprise detailed information is null or the first region information cannot be determined according to the tax payer identification number, the first region information of the target enterprise is determined according to the preset first dimension information of the first dimension in the enterprise detailed information.
The preset first dimension may be a annual report dimension.
Specifically, when the tax payer identification number dimension in the enterprise detailed information is empty or when the tax payer identification number has a problem and cannot determine the first region information according to the tax payer identification number, determining the first region information of the target enterprise according to the annual report information of the annual report dimension in the enterprise detailed information.
Preferably, the determining the first regional information of the target enterprise according to the first dimension information of the preset first dimension in the enterprise detailed information includes: word segmentation is carried out on the first dimension information so as to obtain regional words in the first dimension information; determining the word weight of each regional word in the first dimension information, sequencing the word weights, and determining the first word weight according to the maximum word weight; when the first word weight is greater than or equal to a preset word weight threshold, determining first region information of the target enterprise according to a first region word corresponding to the first word weight.
Preferably, the method further comprises:
splitting the dimension information, obtaining regional words in the dimension information, and counting word frequency of each regional word in the dimension information;
for any regional word, determining the weight of the any regional word according to the preset keyword in the above where the any regional word is located, and determining the word weight of the any regional word according to the weight and word frequency of the any regional word.
Preferably, the method further comprises:
for any regional word, determining the weight corresponding to each sentence with the regional word according to the preset keyword in the context of each sentence with the regional word, and selecting the maximum weight as the weight of the any regional word.
In the invention, for annual report information, splitting is firstly carried out, and regional words and word frequency of each regional word are determined; then, determining the weight of each regional word; and finally, determining the word weight of each regional word according to the word frequency and the weight.
For any regional word, if the preset keyword does not exist in all the contexts where the regional word is located, the weight of the any regional word can be directly determined to be 0.
For any regional word, if the any regional word appears in a plurality of sentences, calculating the weight of the any regional word in each corresponding sentence, and selecting the maximum weight as the weight of the any regional word. For example, if the regional word "beijing" is located in the 1 st, the 2 nd and the 4 th sentences of the annual report information, and the corresponding weights are 0.1,0.2,0.3 according to the context of the beijing in the 1 st, the 2 nd and the 4 th sentences, then 0.3 is taken as the weight corresponding to beijing. In the present invention, the word weight corresponding to each regional word may be calculated using the following formula, including: tfidf=tfxidf; tf= (countWordStr/countAll); idf=log e (pageAll/wordCount+1) Wherein TFIDF is word weight, TF is word frequency, IDF is weight; countwordstris the number of times a regional word appears in a document; countAll is the total word quantity of the document; pageall is the total number of documents in the corpus; wordCount is the number of documents that contain the word.
Fig. 2 is a flowchart for determining first region information of a target enterprise according to annual report information according to an exemplary embodiment of the present invention. As shown in fig. 2, determining first region information of an enterprise according to annual report information includes:
step 201, splitting annual report information of annual report dimension, obtaining regional words in the annual report information, and counting word frequency of each regional word;
step 202, for any regional word, determining the weight of the any regional word according to the preset keyword in the above position of the any regional word, and determining the word weight of the any regional word according to the weight and word frequency of the any regional word;
step 203, ordering the word weights, and determining a first word weight according to the maximum word weight;
step 204, when the first word weight is greater than or equal to a preset word weight threshold, determining first region information of the target enterprise according to a first region word corresponding to the first word weight.
For example, the annual report information of a certain enterprise B is "the headquarters of the own company is located in beijing, which is the headquarters of the own company and brings huge benefits to the company, and Shanghai and Tianjin are all parts of the own company.
Then, the step of determining the first area information according to the annual report information of the enterprise B may specifically include:
Splitting the annual report information, determining that regional words in the annual report information comprise Beijing, shanghai and Tianjin, and then determining that the word frequency of the Beijing is 2, the word frequency of the Shanghai is 1, and the word frequency of the Tianjin is 1;
according to preset keywords such as headquarter/position/subsection and the like in the context of the regional word, determining that the weight of Beijing is 0.5, and the weights of Shanghai and Tianjin are 0.25 respectively;
according to the weight and word frequency of each regional word, the word weight of each regional word can be determined by using the calculation formula of the word weight, the word weight corresponding to Beijing can be 1, the word weight corresponding to Shanghai is 0.25, and the word weight corresponding to Tianjin is 0.25;
selecting the largest word weight 1 as a first word weight;
if the preset word weight threshold value n is 0.6, the first word weight is greater than or equal to the preset word weight threshold value, so that the regional word Beijing corresponding to the first word weight 1 is determined to be the first regional information, or if the preset word weight threshold value n is 1.1, the first word weight is smaller than the preset word weight threshold value n, so that the first global voting weight corresponding to the regional word Beijing corresponding to the first word weight 1 needs to be determined.
The specific value of the preset word weight threshold is not limited to the above example, and may be set according to the requirement.
In some alternative embodiments, the method further comprises: and when the first word weight is smaller than a preset word weight threshold, determining a first global voting weight of a first regional word corresponding to the first word weight.
In the invention, when the first word weight is smaller than a preset word weight threshold, normalization processing is carried out on the first word weight according to the word weights of all regional words in the annual report information so as to determine a first global voting weight of a first regional word corresponding to the first word weight. And then, determining the first region information of the target enterprise according to the dimension information of other dimensions.
In some alternative embodiments, the method further comprises: determining the dimension of the tax payer identification number and the preset first dimension in the enterprise detailed information as a second dimension; and determining a second global voting weight of a second regional word in each second dimension information according to a preset strategy according to the type of the second dimension information of the second dimension.
In the invention, the dimensions of the identification number dimension of the tax payer and the preset first dimension (annual report dimension) in the enterprise detailed information comprise: business name, IP address, phone number, litigation information, etc., all of which are secondary dimensions. Since the types of values of different dimensions are different, a global voting weight is determined according to the type of the second dimension information.
Preferably, the determining, according to a preset policy, the second global voting weight of the second regional word in each second dimension information according to the type of the second dimension information of the second dimension includes:
when the type of second dimension information of the second dimension is a text type, word segmentation is carried out on the second dimension information to obtain regional words in the second dimension information, word weights of each regional word in the second dimension information are calculated, word weights are ordered, the second word weights are determined according to the largest word weights, and second global voting weights of the second regional words corresponding to the second word weights are calculated;
and when the type of the second dimension information of the second dimension is IP or telephone number, inquiring the attribution according to the second dimension information to acquire second regional words in the second dimension information, and performing global voting weight matching according to the type of the second dimension information to determine a second global voting weight of each second regional word.
In some alternative embodiments, the method further comprises: and counting according to the global voting weight of the first regional word and the global voting weight of the second regional word, determining the total global voting weight of the same regional word, and determining the first regional information of the target enterprise according to the regional word with the maximum total global voting weight.
In the invention, for each dimension information except for the tax payer identification number dimension and the annual report dimension in the enterprise detailed information, when the dimension information belongs to a text type, the principle of calculating the second global voting weight of the second regional word corresponding to the second word weight of each dimension information is the same as the principle of calculating the first global voting weight in the annual report information, and the description is omitted here.
When the dimension information belongs to the IP address or the telephone number, inquiring the attribution according to the second dimension information to acquire second regional words in the second dimension information, and performing global voting weight matching according to the type of the second dimension information to determine second global voting weights of each second regional word. For example, the second regional word is determined to be "Tianjin" by the attribution of the telephone number, then the weight matched with the telephone number dimension is determined to be 0.3, and then the second global voting weight of the second regional word "Tianjin" of the telephone number dimension is 0.3.
After the global voting weight is obtained, statistics is carried out according to the global voting weight of the first regional word and the global voting weight of the second regional word, the total global voting weight of the same regional word is determined, and the first regional information of the target enterprise is determined according to the regional word with the maximum total global voting weight. For example, if the regional word and the corresponding global voting weight determined by the annual report dimension, the IP address dimension, and the telephone number dimension are (beijing, 0.1) (beijing, 0.15) (beijing, 0.07), the total global voting weight of beijing can be obtained by statistics to be 0.17, and the total global voting weight of beijing is greater than 0.15, and the first regional information can be determined to be "beijing".
And step 103, performing region consistency check on the target enterprise according to the first region information and the display region information, and obtaining a region consistency check result.
In some optional embodiments, if the region consistency check result indicates that the first region information and the display region information in the enterprise detailed information are inconsistent, it is determined that the target enterprise has an abnormality, and an abnormality warning message may be sent to the monitoring terminal.
In the invention, the first region information determined by the enterprise detailed information can be used as a default correct value, the first region information and the display region information (displayed on the enterprise detail page) in the enterprise detailed information are compared, if the first region information and the display region information are inconsistent, the existence of an abnormality of the enterprise is determined, and the abnormality warning information is sent to the monitoring terminal.
In some optional embodiments, the determining the first region information of the target enterprise according to the enterprise detailed information includes:
determining regional words according to the enterprise detailed information;
acquiring the word weight of the regional word; and
and taking the regional word and the word right of the regional word as first regional information of the target enterprise.
Specifically, the enterprise detailed information includes: tax payer identification number, annual report, telephone number, company name, etc., and also includes a plurality of dimensions for displaying region information for display, etc. When determining the regional word, it may be first determined whether the regional word can be determined based on the value of the taxpayer identification number dimension.
If the regional word can be determined according to the tax payer identification number, determining the regional word according to the tax payer identification number, directly calling a preset word weight corresponding to the regional word from a database according to the regional word, and taking the determined regional word and the preset word weight corresponding to the regional word as first regional information of the target enterprise. Wherein, for the preset word weight, since there is only one regional word determined according to the tax payer identification number, it can be set to be null or a fixed value of 1. The region acquired at this time is directly the first region information. The principle of how to determine the regional word according to the value of the tax payer identification number dimension is the same as that of the above embodiment, and is not described here again.
If the regional word cannot be determined according to the tax payer identification number, the regional word can be determined according to the information of other dimensions except the tax payer identification number dimension and the display regional information dimension. For example, when determining the regional word, it may be first determined whether the regional word can be determined according to the annual report information of the annual report dimension, if so, the first regional information is determined directly according to the regional word corresponding to the annual report dimension, otherwise, the first regional information may be determined based on the values of other dimensions.
The process for determining the first region information according to the annual report information of the annual report dimension comprises the following steps: splitting annual report information of annual report dimension, obtaining regional words in the annual report information, and counting word frequency of each regional word; for any regional word, determining the weight of the any regional word according to the preset keyword in the above where the any regional word is located, and determining the word weight of the any regional word according to the weight and word frequency of the any regional word; ordering the word weights, and determining a first word weight according to the maximum word weight; if the first word weight is greater than or equal to a preset word weight threshold, the first regional information can be determined according to the annual report dimension, and the first regional information of the target enterprise can be determined directly according to the first regional word corresponding to the first word weight. The principle how to determine the first region information according to the annual report dimension information is the same as that of the first region information according to the annual report dimension information in the above embodiment, and will not be described herein.
When the first word weight is smaller than a preset word weight threshold, the fact that the first region information cannot be determined according to the annual report dimension is indicated, the first global voting weight of the first region word corresponding to the first word weight is determined, and then the first region information is determined according to the first global voting weight and dimension information of other dimensions. The principle of determining the first region information by combining other dimension information when the first region information cannot be determined according to the annual report dimension information is the same as the principle of determining the first region information by combining other dimension information in the above embodiment, and will not be described herein.
The method can effectively identify enterprises with abnormal regional information through the information of multiple dimensions such as tax payer identification numbers, annual reports, company names and the like, and can effectively improve the accuracy of the detailed information of the displayed enterprises and the user experience.
Exemplary apparatus
Fig. 3 is a schematic structural diagram of a region consistency check device 300 according to an exemplary embodiment of the present invention. As shown in fig. 3, the present embodiment includes:
the enterprise detailed information obtaining module 301 is configured to obtain enterprise detailed information of a target enterprise, where the enterprise detailed information includes display area information.
Preferably, the enterprise detailed information obtaining module 301 further includes: traversing the database according to a preset time interval to obtain enterprise detailed information of the target enterprise.
And the first region information determining module 302 is configured to determine, according to the enterprise detailed information, first region information of the target enterprise.
Preferably, the first region information determining module 302 determines the first region information of the target enterprise according to the enterprise detailed information, including: when the tax payer identification number dimension in the enterprise detailed information has data, extracting data for identifying first region information from the tax payer identification number, determining region words according to the data of the first region information, and taking the region words as the first region information of the target enterprise.
Preferably, the first region information determining module 302 further includes an extracting unit, configured to extract the data for identifying the first region information according to a preset extraction rule according to a number of digits of the tax payer identification number.
Preferably, the first region information determining module 302 further includes: when the dimension of the tax payer identification number in the enterprise detailed information is empty or the first region information cannot be determined according to the tax payer identification number, determining the first region information of the target enterprise according to the preset first dimension information of the first dimension in the enterprise detailed information.
Preferably, the first region information determining module 302 determines the first region information of the target enterprise according to the first dimension information of the preset first dimension in the enterprise detailed information, including: word segmentation is carried out on the first dimension information so as to obtain regional words in the first dimension information; determining the word weight of each regional word in the first dimension information, sequencing the word weights, and determining the first word weight according to the maximum word weight; when the first word weight is greater than or equal to a preset word weight threshold, determining first region information of the target enterprise according to a first region word corresponding to the first word weight.
Preferably, in the first area information determining module 302, the preset first dimension is a annual report dimension.
Preferably, the first region information determining module 302 further includes: and the global voting weight calculation unit is used for determining a first global voting weight of a first regional word corresponding to the first word weight when the first word weight is smaller than a preset word weight threshold.
Preferably, the first region information determining module 302 further includes: determining the dimension of the tax payer identification number and the preset first dimension in the enterprise detailed information as a second dimension; and determining a second global voting weight of a second regional word in each second dimension information according to a preset strategy according to the type of the second dimension information of the second dimension.
Preferably, the first regional information determining module 302 determines, according to a preset policy, a second global voting weight of a second regional word in each second dimension information according to a type of the second dimension information of the second dimension, including: when the type of second dimension information of the second dimension is a text type, word segmentation is carried out on the second dimension information to obtain regional words in the second dimension information, word weights of each regional word in the second dimension information are calculated, word weights are ordered, the second word weights are determined according to the largest word weights, and second global voting weights of the second regional words corresponding to the second word weights are calculated; and when the type of the second dimension information of the second dimension is IP or telephone number, inquiring the attribution according to the second dimension information to acquire second regional words in the second dimension information, and performing global voting weight matching according to the type of the second dimension information to determine a second global voting weight of each second regional word.
Preferably, the first region information determining module 302 further includes: and counting according to the global voting weight of the first regional word and the global voting weight of the second regional word, determining the total global voting weight of the same regional word, and determining the first regional information of the target enterprise according to the regional word with the maximum total global voting weight.
Preferably, the first region information determining module 302 further includes: splitting the dimension information, obtaining regional words in the dimension information, and counting word frequency of each regional word in the dimension information;
for any regional word, determining the weight of the any regional word according to the preset keyword in the above where the any regional word is located, and determining the word weight of the any regional word according to the weight and word frequency of the any regional word.
Preferably, the first region information determining module 302 further includes: for any regional word, determining the weight corresponding to each sentence with the regional word according to the preset keyword in the context of each sentence with the regional word, and selecting the maximum weight as the weight of the any regional word.
And the verification module 303 is configured to perform region consistency verification on the target enterprise according to the first region information and the display region information, and obtain a region consistency verification result.
Preferably, the verification module 303 further includes: when the regional consistency check result indicates that the first regional information is inconsistent with the display regional information in the enterprise detailed information, determining that the target enterprise is abnormal, and sending abnormal warning information to a monitoring terminal.
The region consistency check device 300 according to the embodiment of the present invention corresponds to the region consistency check method 100 according to another embodiment of the present invention, and is not described herein.
Exemplary electronicsApparatus and method for controlling the operation of a device
Fig. 4 is a structure of an electronic device provided in an exemplary embodiment of the present invention. The electronic device may be either or both of the first device and the second device, or a stand-alone device independent thereof, which may communicate with the first device and the second device to receive the acquired input signals therefrom. Fig. 4 illustrates a block diagram of an electronic device according to an embodiment of the disclosure. As shown in fig. 4, the electronic device 40 includes one or more processors 41 and memory 42.
The processor 41 may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.
Memory 42 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like. One or more computer program instructions may be stored on the computer readable storage medium that can be executed by the processor 41 to implement the method of information mining historical change records and/or other desired functions of the software program of the various embodiments of the present disclosure described above. In one example, the electronic device may further include: an input device 43 and an output device 44, which are interconnected by a bus system and/or other forms of connection mechanisms (not shown).
In addition, the input device 43 may also include, for example, a keyboard, a mouse, and the like.
The output device 44 can output various information to the outside. The output device 44 may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, etc.
Of course, only some of the components of the electronic device relevant to the present disclosure are shown in fig. 4 for simplicity, components such as buses, input/output interfaces, etc. being omitted. In addition, the electronic device may include any other suitable components depending on the particular application.
Exemplary computer program product and computer readable storage Medium
In addition to the methods and apparatus described above, embodiments of the present disclosure may also be a computer program product comprising computer program instructions which, when executed by a processor, cause the processor to perform the steps in a method of mining historical change records according to various embodiments of the present disclosure described in the "exemplary methods" section of this specification.
The computer program product may write program code for performing the operations of embodiments of the present disclosure in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present disclosure may also be a computer-readable storage medium, having stored thereon computer program instructions that, when executed by a processor, cause the processor to perform steps in a method of mining history change records according to various embodiments of the present disclosure described in the above "exemplary methods" section of the present disclosure.
The computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The basic principles of the present disclosure have been described above in connection with specific embodiments, however, it should be noted that the advantages, benefits, effects, etc. mentioned in the present disclosure are merely examples and not limiting, and these advantages, benefits, effects, etc. are not to be considered as necessarily possessed by the various embodiments of the present disclosure. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, since the disclosure is not necessarily limited to practice with the specific details described.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that the same or similar parts between the embodiments are mutually referred to. For system embodiments, the description is relatively simple as it essentially corresponds to method embodiments, and reference should be made to the description of method embodiments for relevant points.
The block diagrams of the devices, apparatuses, devices, systems referred to in this disclosure are merely illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, apparatuses, devices, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.
The methods and apparatus of the present disclosure may be implemented in a number of ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present disclosure may also be implemented as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.
It is also noted that in the apparatus, devices and methods of the present disclosure, components or steps may be disassembled and/or assembled. Such decomposition and/or recombination should be considered equivalent to the present disclosure. The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the disclosure to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.
Claims (16)
1. A method for verifying regional consistency, the method comprising:
acquiring enterprise detailed information of a target enterprise, wherein the enterprise detailed information comprises display area information;
determining first region information of the target enterprise according to the enterprise detailed information;
performing region consistency check on the target enterprise according to the first region information and the display region information to obtain a region consistency check result;
wherein the method further comprises:
when the dimension of the tax payer identification number in the enterprise detailed information is empty or the first region information cannot be determined according to the tax payer identification number, determining the first region information of the target enterprise according to first dimension information of a first dimension preset in the enterprise detailed information;
wherein the determining the first region information of the target enterprise according to the first dimension information of the first dimension preset in the enterprise detailed information includes:
Word segmentation is carried out on the first dimension information so as to obtain regional words in the first dimension information;
determining the word weight of each regional word in the first dimension information, sequencing the word weights, and determining the first word weight according to the maximum word weight;
when the first word weight is larger than or equal to a preset word weight threshold, determining first region information of the target enterprise according to the first region word corresponding to the first word weight.
2. The method as recited in claim 1, further comprising: traversing the database according to a preset time interval to obtain enterprise detailed information of the target enterprise.
3. The method of claim 1, wherein determining the first regional information of the target business based on the business details comprises:
when the tax payer identification number dimension in the enterprise detailed information has data, extracting data for identifying the first region information from the tax payer identification number, determining region words according to the data of the first region information, and taking the region words as the first region information of the target enterprise.
4. A method according to claim 3, further comprising: and extracting data for identifying the first region information according to the number of digits of the tax payer identification number and a preset extraction rule.
5. The method as recited in claim 1, further comprising: and when the first word weight is smaller than a preset word weight threshold, determining a first global voting weight of a first regional word corresponding to the first word weight.
6. The method of claim 1, wherein the predetermined first dimension is a yearly reporting dimension.
7. The method as recited in claim 5, further comprising:
determining the dimension of the tax payer identification number and the preset dimension of the first dimension in the enterprise detailed information as a second dimension;
and determining a second global voting weight of a second regional word in each second dimension information according to a preset strategy according to the type of the second dimension information of the second dimension.
8. The method of claim 7, wherein determining the second global voting weight of the second regional word in each second dimension information according to the type of the second dimension information and the preset strategy includes:
when the type of the second dimension information of the second dimension is a text type, word segmentation is carried out on the second dimension information to obtain regional words in the second dimension information, word weights of each regional word in the second dimension information are calculated, word weights are ordered, a second word weight is determined according to the largest word weight, and a second global voting weight of a second regional word corresponding to the second word weight is determined;
And when the type of the second dimension information of the second dimension is IP or telephone number, inquiring attribution according to the second dimension information to acquire second regional words in the second dimension information, and performing global voting weight matching according to the type of the second dimension information to determine a second global voting weight of each second regional word.
9. The method as recited in claim 8, further comprising:
and counting according to the first global voting weight and the second global voting weight, determining the total global voting weight of the same regional words, and determining the first regional information of the target enterprise according to the regional word with the maximum total global voting weight.
10. The method according to claim 1 or 8, further comprising:
splitting the dimension information, obtaining regional words in the dimension information, and counting word frequency of each regional word in the dimension information;
for any regional word, determining the weight of the any regional word according to the preset keyword in the above where the any regional word is located, and determining the word weight of the any regional word according to the weight and word frequency of the any regional word.
11. The method as recited in claim 10, further comprising:
for any regional word, determining the weight corresponding to each sentence with the regional word according to the preset keyword in the context of each sentence with the regional word, and selecting the maximum weight as the weight of the regional word.
12. The method of claim 1, wherein determining the first regional information for the target business based on the business details comprises:
determining regional words according to the enterprise detailed information;
acquiring the word weight of the regional word; and
and taking the regional word and the word right of the regional word as first regional information of the target enterprise.
13. The method as recited in claim 1, further comprising:
when the regional consistency check result indicates that the first regional information is inconsistent with the display regional information in the enterprise detailed information, determining that the target enterprise is abnormal, and sending abnormal warning information to a monitoring terminal.
14. A regional consistency verification apparatus, the apparatus comprising:
the enterprise detailed information acquisition module is used for acquiring enterprise detailed information of a target enterprise, wherein the enterprise detailed information comprises display area information;
The first region information determining module is used for determining first region information of the target enterprise according to the enterprise detailed information;
the verification module is used for carrying out region consistency verification on the target enterprise according to the first region information and the display region information, and obtaining a region consistency verification result;
wherein, the first regional information determining module further includes: when the dimension of the tax payer identification number in the enterprise detailed information is empty or the first region information cannot be determined according to the tax payer identification number, determining the first region information of the target enterprise according to the preset first dimension information of the first dimension in the enterprise detailed information;
wherein the determining the first regional information of the target enterprise according to the first dimension information of the preset first dimension in the enterprise detailed information includes: word segmentation is carried out on the first dimension information so as to obtain regional words in the first dimension information; determining the word weight of each regional word in the first dimension information, sequencing the word weights, and determining the first word weight according to the maximum word weight; when the first word weight is greater than or equal to a preset word weight threshold, determining first region information of the target enterprise according to a first region word corresponding to the first word weight.
15. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program for executing the method of any of the preceding claims 1-13.
16. An electronic device, the electronic device comprising: a memory and a processor; wherein,
the memory is configured to store the processor-executable instructions;
the processor being configured to read the executable instructions from the memory and execute the instructions to implement the method of any of the preceding claims 1-13.
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