Key data identification method, electronic equipment, storage medium and program product
By introducing the combination of target regular expressions and verification rules into the traditional key data identification method, the problems of missed reports and false positives in the traditional method are solved, and efficient and accurate key data identification is achieved.
Patent Information
- Application Number
- CN202510757120.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-06
- Publication Date
- 2025-09-26
AI Technical Summary
Traditional key data identification methods rely on predefined keywords and regular expressions, which cannot cover possible variations and lead to frequent missed and false positives.
By obtaining target data and key data identification strategies, using target regular expressions for preliminary matching, and combining target verification rules for accuracy verification, the accuracy and reliability of the identified key data are ensured.
The false alarm rate of key data is significantly reduced, and the accuracy and reliability of identifying key data are improved.
Smart Images
Figure CN120706413A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the field of information security technology, and in particular to a key data identification method, electronic device, storage medium, and program product. Background Art
[0002] In today's information age, data security has become a major challenge facing businesses and organizations. With the explosive growth of data volumes and the diversification of data types, effectively identifying whether files contain critical data has become a pressing issue. Traditional methods for identifying critical data primarily rely on simple pattern matching (regular expression matching) or predefined keyword matching to search files and determine whether they contain critical data.
[0003] Traditional methods for identifying key data often rely on predefined keywords and regular expressions to identify sensitive data. However, in real-world applications, sensitive information is expressed in a variety of ways, and the accuracy of keyword matching is heavily dependent on the completeness and accuracy of the keyword list. Relying solely on keyword matching or regular expressions often fails to cover all possible variations and matches a large amount of irrelevant data, resulting in frequent missed and false positives. Summary of the Invention
[0004] In order to solve the above technical problems, the embodiments of the present disclosure provide a key data identification method, an electronic device, a storage medium and a program product.
[0005] One aspect of an embodiment of the present disclosure provides a key data identification method, including: obtaining target data and a key data identification strategy; in response to the key data identification strategy being a first preset identification strategy, obtaining a target regular expression and a target verification rule corresponding to the target data; based on the target regular expression, determining first initial key data in the target data; performing accuracy verification on the first initial key data based on the target verification rule; and in response to the first initial key data passing the accuracy verification, determining first target key data based on the first initial key data.
[0006] Another aspect of the embodiments of the present disclosure provides a key data identification device, including: a data acquisition module for acquiring target data and a key data identification strategy; a first rule acquisition module for acquiring a target regular expression and a target verification rule corresponding to the target data in response to the key data identification strategy being a first preset identification strategy; a first matching module for determining first initial key data in the target data based on the target regular expression; a first verification module for performing accuracy verification on the first initial key data based on the target verification rule; and a first determination module for determining first target key data based on the first initial key data in response to the first initial key data passing the accuracy verification.
[0007] Another aspect of the embodiments of the present disclosure provides an electronic device, including: a memory for storing a computer program; a processor for executing the computer program stored in the memory, and when the computer program is executed, the above-mentioned key data identification method is implemented.
[0008] Another aspect of the embodiments of the present disclosure provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the above-mentioned key data identification method is implemented.
[0009] According to another aspect of the embodiments of the present disclosure, a computer program product is provided, including computer program instructions, which implement the above-mentioned key data identification method when executed by a processor.
[0010] In the embodiment of the present disclosure, the target data is preliminarily matched through the target regular expression to extract the first initial key data, and then its accuracy is verified through the target verification rule, thereby achieving efficient identification and matching of key data and significantly reducing the false alarm rate of key data, thereby improving the accuracy and reliability of identifying key data.
[0011] The technical solution of the present disclosure is further described in detail below through the accompanying drawings and examples. BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.
[0013] The present disclosure can be more clearly understood from the following detailed description with reference to the accompanying drawings, in which:
[0014] Figure 1 It is a flowchart of a key data identification method provided by an exemplary embodiment of the present disclosure.
[0015] Figure 2It is a flowchart of a key data identification method provided by another exemplary embodiment of the present disclosure.
[0016] Figure 3 It is a flowchart of step S140 provided by an exemplary embodiment of the present disclosure.
[0017] Figure 4 It is a flowchart of a key data identification method provided by another exemplary embodiment of the present disclosure.
[0018] Figure 5 It is a flowchart of a key data identification method provided by another exemplary embodiment of the present disclosure.
[0019] Figure 6 It is a structural diagram of a key data identification device provided by an exemplary embodiment of the present disclosure.
[0020] Figure 7 The figure is a schematic structural diagram of an application embodiment of the electronic device disclosed herein. DETAILED DESCRIPTION
[0021] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present disclosure.
[0022] Those skilled in the art will understand that the terms "first" and "second" in the embodiments of the present disclosure are only used to distinguish different steps, devices or modules, and do not represent any specific technical meanings, nor do they indicate a necessary logical order between them.
[0023] It should also be understood that in the embodiments of the present disclosure, “a plurality of” may refer to two or more than two, and “at least one” may refer to one, two, or more than two.
[0024] It should also be understood that any component, data or structure mentioned in the embodiments of the present disclosure can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.
[0025] In addition, the term "and / or" in this disclosure is merely a description of the association relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this disclosure generally indicates that the related objects are in an "or" relationship.
[0026] It should also be understood that the description of the various embodiments in this disclosure focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced with each other. For the sake of brevity, they will not be described one by one.
[0027] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.
[0028] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present disclosure, its application, or uses.
[0029] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.
[0030] It should be noted that like reference numerals and letters refer to like items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.
[0031] The embodiments of the present disclosure can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate in conjunction with numerous other general-purpose or specialized computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with terminal devices, computer systems, servers, and other electronic devices include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, minicomputer systems, mainframe computer systems, and distributed cloud computing technology environments including any of the above systems, among others.
[0032] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system-executable instructions (such as program modules) executed by a computer system. Generally, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked via a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media, including storage devices.
[0033] In the process of implementing the present disclosure, the inventors discovered that since traditional key data identification methods rely on predefined keywords or regular expressions to identify sensitive data, and relying solely on keyword matching cannot cover possible variants, it leads to frequent omissions. At the same time, a single regular expression may match a large amount of irrelevant data, resulting in a high false positive rate for key data.
[0034] Figure 1This is a flow chart of a key data identification method provided by an exemplary embodiment of the present disclosure. This embodiment can be applied to electronic devices, such as Figure 1 As shown, the key data identification method includes the following steps:
[0035] Step S100: Acquire target data and key data identification strategy.
[0036] The target data may be, for example, text data, and its file format may include at least one of the following: txt, ppt, pdf, csv, and xlsx. The target data content type may include, for example, at least one of the following: contract, project report, purchase order, and bill. The key data identification strategy indicates a strategy for determining required key data.
[0037] Step S110 : In response to the key data identification strategy being the first preset identification strategy, a target regular expression and a target verification rule corresponding to the target data are obtained.
[0038] The target regular expression can be used to identify and match the required key data. The target verification rule can include a specific rule of the required key data. The target verification rule can be used to verify the correctness of the first initial key data to reduce false positives of the required key data.
[0039] In one embodiment, multiple regular matching rules and verification rules can be pre-set, and corresponding regular matching rules and verification rules can be selected as target recognition regular expressions and target verification rules respectively according to the content or text format of the target data. Alternatively, target regular expressions and target verification rules can be created based on the required key data.
[0040] Step S120: determining first initial key data in the target data based on the target regular expression.
[0041] The first initial key data may include, for example, a phone number, ID number, account number, bank card number, email address, work number, mailing address or zip code, user ID, etc. In this embodiment, anonymization, desensitization, encryption, and other measures have been taken when processing the key data, and compliance with relevant privacy regulations has been ensured.
[0042] In one embodiment, regular matching may be performed in the target data based on the target regular expression. When key data that meets the target regular expression is matched in the target data, the key data is used as the first initial key data.
[0043] For example, assuming that the required key data is an international phone number, the target regular expression may be: \+? \d{1,4}?[-.\s]?(\d{1,3}?)?[-.\s]? \d{3}[-.\s]? \d{4}. This target regular expression is used to filter international phone numbers and can be used to identify international phone numbers (first initial key data) in the target data.
[0044] Step S130: performing accuracy verification on the first initial key data based on target verification rules.
[0045] In which, when the first initial key data meets the requirements in the target verification rules, it can be determined that the first initial key data has passed the accuracy verification; when the first initial key data does not meet the requirements in the target verification rules, it can be determined that the first initial key data has not passed the accuracy verification.
[0046] In one embodiment, a target verification rule can be set based on a specific pattern of the required key data. For example, assuming that the required key data is a mobile phone number, the target verification rule can include that the key data is 6 digits (the number of digits in a phone number), when the first initial key data is 6 digits, it is determined that the first initial key data has passed the accuracy verification, and when the first initial key data is not 6 digits, it is determined that the first initial key data has failed the accuracy verification.
[0047] Step S140 : In response to the first initial key data passing the accuracy check, determining the first target key data based on the first initial key data.
[0048] The first initial key data may be determined as the first target key data. The first target key data is the required key data. A key data log may be pre-set, and the first target key data may be recorded in the key data log. The target data may be analyzed based on the frequency of occurrence of the first target key data in the target data and / or the location of occurrence in the target data to determine the confidentiality level of the target data.
[0049] In one embodiment, when the first initial key data fails the accuracy check, the first initial key data is deleted.
[0050] In the embodiment of the present disclosure, the target data is preliminarily matched through the target regular expression to extract the first initial key data, and then its accuracy is verified through the target verification rule, thereby achieving efficient identification and matching of key data and significantly reducing the false alarm rate of key data, thereby improving the accuracy and reliability of identifying key data.
[0051] Figure 2FIG. 1 is a flow chart of a key data identification method provided by another exemplary embodiment of the present disclosure. Figure 2 As shown, after step S120, the following steps are also included:
[0052] Step S150 , in response to the first initial key data having associated information, obtaining a target associated feature matching rule, and performing an accuracy verification operation on the first initial key data based on a target verification rule when the associated information satisfies the target associated feature matching rule.
[0053] The target-related feature matching rule can be used to process the related information to assist in screening the required key data. The target-related feature matching rule can include an identification condition, which can be configured using a regular expression or a keyword. For example, a regular expression or a keyword can be set for screening the related information, and a conditional statement can be used to configure the relationship between the regular expression or the keyword and the data of the key data to be determined. The conditional statement can be "include", "exclude", "conform to", or "do not conform to".
[0054] The associated information of the first initial key data may be related information of the first initial key data in the target data. For example, the above content, below content or context content of the first initial key data in the target data may be used as the associated information of the first initial key data. Exemplarily, the identification conditions in the target association matching rule may include: including features corresponding to at least n regular expressions, not including features corresponding to n regular expressions, including at least n keywords or not including keywords. Taking the identification condition of including features corresponding to at least n regular expressions as an example, when features corresponding to n regular expressions in the identification condition are hit in the associated information of the first initial key data, it is determined that the associated information meets the target association feature matching rule, and when features corresponding to less than n regular expressions are hit in the associated information, it is determined that the associated information does not meet the target association feature matching rule.
[0055] In one embodiment, when the target data contains associated information for the first initial key data, a target associated feature matching rule is obtained, and then a determination is made as to whether the associated information satisfies the target associated feature matching rule. If the associated information satisfies the target associated feature matching rule, step S130 is executed. If the associated information for the first initial key data does not satisfy the target associated feature matching rule, the first initial key data is deleted, and the operation ends. The context of the first target key data in the target data may also be recorded in a key data log.
[0056] It should be noted that there is no execution order between step S150 and step S140 in the embodiment of the present disclosure.
[0057] Step S160, in response to the first initial key data not having associated information, the target data is identified a first preset number of times based on the target regular expression, and when the first initial key data is identified more than a second preset number of times, an operation of performing accuracy verification on the first initial key data based on the target verification rule is performed.
[0058] The second preset number of times is less than or equal to the first preset number of times.
[0059] In one embodiment, when it is determined that the target data does not include the preceding content, following content, or contextual content of the first initial key data, it can be determined that the first initial key data does not have associated information. When the target data does not include the associated information, regular matching (identification) can be performed on the target data based on the target regular expression for a first preset number of times. When the first initial key data is identified more than a second preset number of times, step S130 is executed. When the first initial key data is identified less than the second preset number of times, the first initial key data is deleted.
[0060] Exemplarily, assuming that the first preset number of times is 5 times and the second preset number of times is 3 times, the target data is matched 5 times by the target regular expression, when the first initial key data is matched 4 times in the 5 regular matches, step S130 is executed, and when the first initial key data is matched only 2 times in the 5 regular matches, the first initial key data is deleted. In the embodiment of the present disclosure, when there is associated information, the first initial key data is auxiliary screened by matching the associated information and the target associated feature matching rule. When the first initial key data does not have associated information, the first initial key data is auxiliary screened by the number of times the target regular expression hits the target data (the second preset number), thereby further improving the accuracy of the identified first target key data.
[0061] It should be noted that, in this embodiment, there is no execution order between step S150 and step S160.
[0062] In some optional implementations, the associated information of the first initial key data may be obtained in the following manner in the embodiment of the present disclosure:
[0063] In response to the target data being table data, association information of the first initial key data is determined based on header data of the target data.
[0064] When the target data is table data, header data in the target data may be obtained and used as association information of the first initial key data.
[0065] In one embodiment, when the target data is table data and the target data does not include header data, it is determined that the first initial key data has no associated information.
[0066] Accordingly, in response to the target data not being tabular data, associated information of the first initial key data is determined in contextual content in the target data based on the first initial key data.
[0067] In one embodiment, the first initial key data may be used as the associated information in the previous content, the next content, or the context content of the target data. For example, the last five words (preset bytes) of the previous content may be used as the associated information.
[0068] In the embodiment of the present disclosure, different methods of determining associated information are adopted for target data of tabular data and non-tabular data, respectively, thereby improving the accuracy and flexibility of obtaining associated information. At the same time, when the target data is tabular data, the header data is used as the associated information to achieve fast and accurate determination of the associated information.
[0069] Figure 3 is a flow chart of step S140 provided by an exemplary embodiment of the present disclosure. In some optional implementations, such as Figure 3 As shown, step S140 may include the following steps:
[0070] Step S141: Obtain a first whitening check rule corresponding to the first initial key data.
[0071] The first white check rule is used to indicate a rule that does not conform to the preset key data. The preset key data rule can be set based on the required key data. The first white check rule can be used to eliminate interference information of the key data. In one embodiment, the first white check rule can include a regular expression, a keyword, or a white list.
[0072] Step S142 : In response to the first initial key data not meeting the first whitening check rule, the first initial key data is determined as the first target key data.
[0073] In one embodiment, when the first initial key data meets the first whitening check rule, the first initial key data is deleted.
[0074] For example, assuming that the required key data is a telephone number outside the enterprise, the first white-check rule may include multiple telephone numbers within the enterprise. When the first initial key data is not a telephone number in the first white-check rule, it is determined that the first initial key data does not comply with the first white-check rule, and the first initial key data is determined as the first target key data; when the first initial key data is a telephone number in the first white-check rule, it is determined that the first initial key data complies with the first white-check rule, and the first initial key data is deleted.
[0075] In the embodiment of the present disclosure, by setting the first white check rule to perform correctness check on the first initial key data, interference information can be effectively eliminated, the accuracy of determining the first target key data is improved, and the false alarm rate of the first target key data is reduced.
[0076] In some optional implementations, in the embodiments of the present disclosure, the target association feature matching rule includes an identification condition and a relationship between the association information and the identification condition.
[0077] The identification condition may include a regular expression or a keyword, etc. The relationship between the associated information and the identification condition may be configured through a conditional statement.
[0078] Figure 4 FIG. 1 is a flow chart of a key data identification method provided by another exemplary embodiment of the present disclosure. Figure 4 As shown, whether the association information meets the target association feature matching rule can be determined in the following way:
[0079] Step S210 : matching the associated information of the first initial key data based on the identification condition to obtain a matching result.
[0080] The matching result may include whether the association information includes the identification condition and the number of identification conditions (hits). For example, when the identification condition includes a keyword, the matching result may include whether the association information includes the keyword and the number of hits including the keyword.
[0081] Step S220 : In response to the matching result satisfying the relationship between the association information and the identification condition, determining whether the association information satisfies the target association feature matching rule.
[0082] In one embodiment, the recognition condition is a keyword, and the relationship between the associated information and the recognition condition can be that the associated information includes at least a preset number of keywords. When the recognition result is that the associated information includes more than the preset number of keywords in the recognition condition, the associated information is determined to meet the target association feature matching rule.
[0083] In the embodiment of the present disclosure, by forming a target association feature matching rule based on the identification condition and the relationship between the association information and the identification condition, accurate and efficient analysis of the association information of the first initial key data is achieved.
[0084] The following is an application example of the key data identification method in the present disclosure, which may include:
[0085] S1, when receiving target data identified by a first preset identification strategy, obtaining a target regular expression, a target association feature matching rule, and a target verification rule corresponding to the target data;
[0086] S2, determining first initial key data in the target data based on the target regular expression;
[0087] S3, determining whether the first initial key data has associated information in the target data, and if so, executing S4; if not, executing S7;
[0088] S4, based on the target association feature matching rule, determining whether the association information satisfies the target association feature matching rule, and when the target association feature matching rule is satisfied, executing S5; when the target association feature matching rule is not satisfied, deleting the first initial key data;
[0089] S5, performing accuracy verification on the first initial key data based on the target verification rule. When the first initial key data passes the accuracy verification, executing S6. When the first initial key data fails the accuracy verification, deleting the first initial key data.
[0090] S6, determining whether the first initial key data meets the first whitening check rule; if not, determining the first initial key data as the first target key data; if yes, deleting the first initial key data;
[0091] S7, identifying the target data based on the target regular expression a first preset number of times, and determining whether the number of times the first initial key data is identified exceeds a second preset number of times, if so, executing step S8, if not, deleting the first initial key data;
[0092] S8, performing accuracy verification on the first initial key data based on the target verification rule. When the first initial key data passes the accuracy verification, executing S9. When the first initial key data fails the accuracy verification, deleting the first initial key data.
[0093] S9, determining whether the first initial key data meets the first white check rule, if not, determining the first initial key data as the first target key data, if it meets, delete the first initial key data.
[0094] Figure 5 FIG. 1 is a flow chart of a key data identification method provided by another exemplary embodiment of the present disclosure. In some optional implementations, such as Figure 5 As shown, the key data identification method may further include the following steps:
[0095] Step S310 : In response to the key data identification strategy being the second preset identification strategy, a target keyword rule is obtained.
[0096] Among them, the target keyword rule may include at least one group of target keywords, the relationship between each group of target keywords, and the number of at least hit keywords in each group of target keywords. Each group of target keywords may include at least one target keyword or regular keyword. The relationship between any two groups of target keywords may be defined in an "or" / "and" manner. When the relationship between two target keyword groups is "or", it means that only any one target keyword group can be included in the target data. When the relationship between two target keyword groups is "and", it means that both target keyword groups need to be included in the target data at the same time. The number of at least hit keywords in each group of target keywords indicates the number of target keywords included in at least the group.
[0097] In one embodiment, a keyword library may be pre-established, and corresponding keywords may be selected from the keyword library as target keywords.
[0098] Step S320: determining second initial key data in the target data based on the target keyword rule.
[0099] Based on the target keyword rule, data that meets the target keyword rule is matched in the target data as the second initial key data.
[0100] For example, assume that the target keyword rule includes two groups of target keywords, the first group of target keywords includes mobile phone numbers and real estate, and the second group of target keywords may include housing and personal credit. The relationship between the first group of target keywords and the second group of target keywords is an "and" relationship, and the number of at least hit keywords in the first group of target keywords and the second group of target keywords is 1.
[0101] The target data can be divided into multiple data segments. When a data segment includes a target keyword from the first group of target keywords and a target keyword from the second group of target keywords, it is determined that the data segment meets the target keyword rule and is used as the second initial key data.
[0102] Step S330: Obtain a second whitening check rule corresponding to the second initial key data.
[0103] The second white check rule is used to indicate a rule that does not conform to the preset key data. For example, the second white check rule may include a whitelist, which can be used to exclude interference information of the key data. In one embodiment, the second white check rule may include a regular expression or a keyword.
[0104] Step S340 : In response to the second initial key data not meeting the second whitening check rule, determining the second initial key data as the second target key data.
[0105] Among them, the second target key data is the required key data.
[0106] In one embodiment, when the second initial key data meets the second whitening check rule, the second initial key data is deleted.
[0107] For example, assuming that the required key data is the name of an unsold property, the second white-check rule may include the name of a sold property. When the second initial key data is not the property name in the second white-check rule, it is determined that the second initial key data does not comply with the second white-check rule, and the second initial key data is determined as the second target key data; when the second initial key data is the property name in the second white-check rule, it is determined that the second initial key data complies with the second white-check rule, and the second initial key data is deleted.
[0108] In the embodiment of the present disclosure, the target keyword rule formed by the combination of multiple keywords and the second white check rule are used to comprehensively analyze the target data, thereby effectively covering multiple keywords, improving the flexibility of keyword matching, and reducing the probability of false reporting and omission of the second target key data.
[0109] In an optional implementation, in the embodiment of the present disclosure, step S110 may include: in response to detecting a preset operation on the target webpage information, determining the target data based on the target webpage information.
[0110] The preset operation includes at least one of the following: a download operation, a browse operation, and a send operation.
[0111] In one embodiment, the web page information may be a URL (Uniform Resource Locator) file, and the type (MIME type) of the web page information may be determined based on a header identifier or a file header identifier in the Content-Type (content type) in the web page information. The MIME type is a standard for indicating the nature and format of a document, file, or byte stream. The web page information is decoded using a decoding method corresponding to the sample based on the type of the web page information to obtain the target data. The decoding method may include, for example, Base64, UTF (Unicode Transformation Format), etc.
[0112] Figure 6 FIG. 1 is a schematic diagram of a key data identification device provided by an exemplary embodiment of the present disclosure. Figure 6 As shown, the device of this embodiment may include:
[0113] Data acquisition module 410, used to acquire target data and key data identification strategies;
[0114] A first rule acquisition module 420 is configured to acquire a target regular expression and a target verification rule corresponding to the target data in response to the key data identification strategy being the first preset identification strategy;
[0115] A first matching module 430 is configured to determine first initial key data in the target data based on the target regular expression;
[0116] A first verification module 440 is configured to perform accuracy verification on the first initial key data based on the target verification rule;
[0117] The first determining module 450 is configured to determine first target key data based on the first initial key data in response to the first initial key data passing the accuracy check.
[0118] In some possible implementations of the present disclosure, the key data identification device in the embodiment of the present disclosure further includes:
[0119] a first auxiliary screening module, configured to, in response to the first initial key data having associated information, obtain a target associated feature matching rule, and, when the associated information satisfies the target associated feature matching rule, perform an accuracy verification operation on the first initial key data based on the target verification rule;
[0120] A second auxiliary screening module is used to identify the target data a first preset number of times based on the target regular expression in response to the first initial key data not having associated information, and when the first initial key data is identified more than a second preset number of times, perform an accuracy verification operation on the first initial key data based on the target verification rule.
[0121] In some possible implementations of the present disclosure, the key data identification device in the embodiment of the present disclosure further includes:
[0122] a first association information determination module, configured to determine the association information based on header data of the target data in response to the target data being table data;
[0123] The second association information determination module is configured to determine the association information in contextual content of the target data based on the first initial key data in response to the target data not being tabular data.
[0124] In some possible implementations of the present disclosure, the first determination module 450 in the embodiment of the present disclosure is specifically used to obtain a first whitening check rule corresponding to the first initial key data, where the first whitening check rule is used to indicate a rule that does not comply with preset key data regulations; in response to the first initial key data not complying with the first whitening check rule, the first initial key data is determined as the first target key data.
[0125] In some possible implementations of the present disclosure, the target association feature matching rule in the embodiment of the present disclosure includes an identification condition and a relationship between the association information and the identification condition; the key data identification device in the embodiment of the present disclosure further includes:
[0126] A second matching module, configured to match the associated information based on the identification condition to obtain a matching result;
[0127] The second determining module is configured to determine, in response to the matching result satisfying the relationship between the association information and the identification condition, whether the association information satisfies the target association feature matching rule.
[0128] In some possible implementations of the present disclosure, the key data identification device in the embodiment of the present disclosure further includes:
[0129] a second rule acquisition module, configured to acquire a target keyword rule in response to the key data identification strategy being the second preset identification strategy, the target keyword rule including at least one group of target keywords, a relationship between each group of target keywords, and a number of at least hit keywords in each group of target keywords;
[0130] a third matching module, configured to determine second initial key data in the target data based on the target keyword rule;
[0131] a third rule acquisition module, configured to acquire a second whitening check rule corresponding to the second initial key data, wherein the second whitening check rule is used to indicate a rule that does not conform to the preset key data;
[0132] A fourth determining module is configured to determine that the second initial key data is the second target key data in response to the second initial key data not meeting the second whitening check rule.
[0133] In some possible implementations of the present disclosure, the key data identification device in the embodiment of the present disclosure further includes:
[0134] In response to detecting a preset operation on the target webpage information, the target data is determined based on the target webpage information, where the preset operation includes at least one of the following: a download operation, a browse operation, and a send operation.
[0135] The key data identification device of the embodiment of the present application corresponds to the embodiment of the key data identification method of the present application. The relevant contents can be referenced to each other and will not be repeated here.
[0136] The beneficial technical effects corresponding to the exemplary embodiments of the key data identification device of the embodiments of the present application can be found in the corresponding beneficial technical effects of the above-mentioned corresponding exemplary method part, which will not be repeated here.
[0137] In addition, an embodiment of the present disclosure further provides an electronic device, including:
[0138] memory for storing computer programs;
[0139] The processor is used to execute the computer program stored in the memory, and when the computer program is executed, the key data identification method described in any of the above embodiments of the present disclosure is implemented.
[0140] Figure 7 This is a schematic diagram of the structure of an application embodiment of the electronic device disclosed in the present invention. Figure 7 The electronic device according to the embodiment of the present disclosure is described. The electronic device may be either or both of the first device and the second device, or a standalone device independent of them, and the standalone device may communicate with the first device and the second device to receive collected input signals from them.
[0141] like Figure 7 As shown, the electronic device includes one or more processors and memory.
[0142] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.
[0143] The memory may include one or more computer program products, which 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. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor may execute the program instructions to implement the key data identification method of each embodiment of the present disclosure described above and / or other desired functions.
[0144] In one example, the electronic device may further include an input device and an output device, and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).
[0145] In addition, the input device may also include, for example, a keyboard, a mouse, and the like.
[0146] The output device can output various information to the outside, including determined distance information, direction information, etc. The output device can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, and the like.
[0147] Of course, to simplify, Figure 7 Only some of the components related to the present disclosure in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application scenarios.
[0148] In addition to the above-mentioned methods and devices, an embodiment of the present disclosure may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the key data identification method according to various embodiments of the present disclosure described in the above part of this specification.
[0149] The computer program product may be written in any combination of one or more programming languages to implement the operations of the disclosed embodiments, including object-oriented programming languages such as Java, C++, and conventional procedural programming languages such as C or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.
[0150] In addition, an embodiment of the present disclosure may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the key data identification method according to various embodiments of the present disclosure described in the above part of this specification.
[0151] The computer-readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can, for example, include but is not limited to a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.
[0152] Those skilled in the art will understand that all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk, etc. Various media that can store program codes.
[0153] The basic principles of the present disclosure have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this disclosure are merely illustrative and not restrictive, and should not be construed as necessarily possessed by each embodiment of the present disclosure. Furthermore, the specific details disclosed above are provided for illustrative purposes and to facilitate understanding, rather than as limitations. These details do not limit the present disclosure to necessarily being implemented using these specific details.
[0154] Each embodiment in this specification is described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. References to the same or similar parts between the various embodiments are sufficient. For system embodiments, since they largely correspond to method embodiments, their description is relatively simple. For relevant parts, references to the description of the method embodiments are sufficient.
[0155] The block diagrams of the devices, devices, equipment, and systems involved in this disclosure are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "include," "comprise," "have," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.
[0156] The methods and apparatus of the present disclosure may be implemented in many ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above order of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless otherwise specified. In addition, in some embodiments, the present disclosure may also be implemented as programs recorded in a recording medium, which include machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers recording media that store programs for executing the methods according to the present disclosure.
[0157] It should also be noted that in the apparatus, device, and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.
[0158] The above 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 general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.
[0159] The above description has been provided for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.
Claims
1. A key data identification method, characterized in that: include: Acquire target data and identify key data strategies; In response to the key data identification strategy being the first preset identification strategy, obtaining a target regular expression and a target verification rule corresponding to the target data; Based on the target regular expression, determining first initial key data in the target data; Performing accuracy verification on the first initial key data based on the target verification rule; In response to the first initial key data passing the accuracy check, first target key data is determined based on the first initial key data.
2. The method according to claim 1, characterized in that After determining the first initial key data in the target data, the method further includes: In response to the first initial key data having associated information, obtaining a target associated feature matching rule, and performing an accuracy verification operation on the first initial key data based on the target verification rule when the associated information satisfies the target associated feature matching rule; In response to the first initial key data not having associated information, the target data is identified a first preset number of times based on the target regular expression. When the number of times the first initial key data is identified exceeds a second preset number, an operation of performing accuracy verification on the first initial key data based on the target verification rule is performed.
3. The method according to claim 2, characterized in that After determining the first initial key data in the target data, the method further includes: In response to the target data being table data, determining the associated information based on header data of the target data; In response to the target data not being tabular data, the associated information is determined in contextual content in the target data based on the first initial key data.
4. The method according to any one of claims 1 to 3, characterized in that: The determining of the first target key data based on the first initial key data includes: Obtaining a first whitening check rule corresponding to the first initial key data, where the first whitening check rule is used to indicate a rule that does not conform to preset key data requirements; In response to the first initial key data not meeting the first whitening check rule, the first initial key data is determined as the first target key data.
5. The method according to claim 2, characterized in that The target association feature matching rule includes an identification condition and a relationship between the association information and the identification condition; Determine whether the association information meets the target association feature matching rule by: Matching the associated information based on the identification condition to obtain a matching result; In response to the matching result being consistent with the relationship between the association information and the identification condition, it is determined that the association information satisfies the target association feature matching rule.
6. The method according to any one of claims 1 to 5, characterized in that: After obtaining the target data and key data identification strategy, the following steps are also included: In response to the key data identification strategy being the second preset identification strategy, obtaining a target keyword rule, the target keyword rule including at least one group of target keywords, a relationship between each group of target keywords, and a number of at least hit keywords in each group of target keywords; determining second initial key data in the target data based on the target keyword rule; Obtaining a second whitening check rule corresponding to the second initial key data, where the second whitening check rule is used to indicate a rule that does not comply with preset key data regulations; In response to the second initial key data not meeting the second whitening check rule, the second initial key data is determined to be second target key data.
7. The method according to any one of claims 1 to 6, characterized in that: Obtain target data, including: In response to detecting a preset operation on the target webpage information, the target data is determined based on the target webpage information, where the preset operation includes at least one of the following: a download operation, a browse operation, and a send operation.
8. An electronic device, characterized in that: include: memory for storing computer programs; A processor is used to execute the computer program stored in the memory, and when the computer program is executed, the key data identification method described in any one of claims 1 to 7 is implemented.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the key data identification method described in any one of claims 1 to 7 is implemented.
10. A computer program product comprising computer program instructions, characterized in that When the computer program instructions are executed by a processor, the key data identification method described in any one of claims 1 to 7 is implemented.