CN115357630B - Information detection method, device, device, computer readable medium and program product - Google Patents

Abstract

Embodiments of the present disclosure disclose information detection methods, apparatuses, devices, computer readable media and program products. One embodiment of the method comprises: acquiring engineering project detection information and a first attribute information set, wherein the engineering project detection information comprises a project identifier, a sub-project information group and a project attribute information set, each project attribute information comprises a project attribute name, and each first attribute information comprises a first attribute name; selecting item attribute names different from the first attribute names from the item attribute names as residual attribute names; acquiring a second attribute information set; determining each first attribute information and each second attribute information as target attribute information; extracting the target attribute information set based on the sub-project information group to obtain a target project information set; generating a sub-item attribute detection information set; and displaying the sub-item attribute detection information set for detecting information. This embodiment can shorten the time consumption of information detection.

Description

Information detection method, device, device, computer readable medium and program product

technical field

The embodiments of the present disclosure relate to the field of computer technology, and in particular to an information detection method, device, equipment, computer-readable medium, and program product.

Background technique

The information detection method is a technology for detecting a large amount of engineering business data from different data sources. At present, when performing information detection, the usual way is to manually switch different data sources to detect different engineering business data, or use ETL (Extraction-Transformation-Loading, data extraction, transformation and loading) tools to analyze data from different sources. A large amount of engineering business data from the data source is extracted and calculated, thereby completing information detection.

However, the inventors have found that when the information detection is carried out in the above manner, the following technical problems often exist:

First, a large amount of engineering business data from different data sources often contains a large amount of irrelevant or redundant data that is irrelevant to the inspection task, which is not convenient for inspectors to perform daily inspection on the same engineering business data, resulting in a long time-consuming information detection;

Second, the existing information detection methods do not detect or perform lag detection on the voucher engineering business data from various data sources, which easily makes the wrong voucher engineering business data be ignored, resulting in low accuracy of information detection;

Third, the existing information detection method uses a direct display method to display some engineering business data that is not easy to disclose, which easily leads to a high risk of data leakage.

The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art.

Contents of the invention

The Summary of the Disclosure is provided to introduce concepts in a simplified form that are described in detail in the Detailed Description that follows. The content of this disclosure is not intended to identify the key features or essential features of the claimed technical solution, nor is it intended to be used to limit the scope of the claimed technical solution.

Some embodiments of the present disclosure provide an information detection method, device, device, computer-readable medium, and program product to solve one or more of the technical problems mentioned in the background art section above.

In the first aspect, some embodiments of the present disclosure provide an information detection method, the method includes: obtaining engineering project detection information and a first attribute information set corresponding to the target engineering business, wherein the above-mentioned target engineering business is information detection to be performed engineering business, the above-mentioned engineering project detection information includes project identification, sub-project information group and project attribute information set, each item attribute information in the above-mentioned project attribute information set includes the project attribute name, and each first attribute information in the above-mentioned first attribute information set The attribute information includes the first attribute name; from the item attribute names included in the above-mentioned item attribute information set, the item attribute names different from the first attribute names included in the above-mentioned first attribute information set are selected as the remaining attribute names, and the remaining attribute name group; obtain from a preset data source a second attribute information set that matches the project identification included in the engineering project detection information and the remaining attribute name group, wherein each second attribute in the second attribute information set The information includes a second attribute name; each first attribute information in the first attribute information set and each second attribute information in the second attribute information set are determined as target attribute information to obtain a target attribute information set; based on the above project The sub-item information group included in the item detection information extracts and processes the above-mentioned target attribute information set to obtain the target item information set; based on the above-mentioned target item information set, generates a sub-item attribute detection information set; controls the display device to display the above-mentioned sub-item attribute detection Infosets for instrumentation information.

In a second aspect, some embodiments of the present disclosure provide an information detection device, which includes: a first acquisition unit configured to acquire engineering project detection information and a first attribute information set corresponding to a target engineering business, wherein the above-mentioned target The engineering business is the engineering business to be subjected to information detection. The above-mentioned engineering project detection information includes project identification, sub-project information group and project attribute information set. Each item attribute information in the above-mentioned project attribute information set includes the project attribute name, and the above-mentioned first attribute Each first attribute information in the information set includes a first attribute name; the selection unit is configured to select from each item attribute name included in the above-mentioned item attribute information set and each first attribute name included in the above-mentioned first attribute information set The different project attribute names are used as the remaining attribute names to obtain the remaining attribute name group; the second acquisition unit is configured to obtain from the preset data source and match the project identification included in the above-mentioned engineering project detection information and the above-mentioned remaining attribute name group The second attribute information set, wherein, each second attribute information in the above-mentioned second attribute information set includes a second attribute name; the determining unit is configured to combine each first attribute information in the above-mentioned first attribute information set, the above-mentioned Each second attribute information in the second attribute information set is determined as the target attribute information to obtain the target attribute information set; the extraction processing unit is configured to perform the above-mentioned target attribute information set based on the sub-item information group included in the engineering item detection information Perform extraction processing to obtain the target item information set; the generating unit is configured to generate a sub-item attribute detection information set based on the above-mentioned target item information set; the display unit is configured to control the display device to display the above-mentioned sub-item attribute detection information set, to For testing information.

In a third aspect, some embodiments of the present disclosure provide an electronic device, including: one or more processors; The processor executes, so that one or more processors implement the method described in any implementation manner of the first aspect above.

In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium on which a computer program is stored, wherein when the program is executed by a processor, the method described in any implementation manner of the above-mentioned first aspect is implemented.

In a fifth aspect, some embodiments of the present disclosure provide a computer program product, including a computer program. When the computer program is executed by a processor, the method described in any implementation manner of the above-mentioned first aspect is implemented.

The above-mentioned embodiments of the present disclosure have the following beneficial effects: time-consuming information detection can be shortened through the information detection methods of some embodiments of the present disclosure. Specifically, the reason for the long time-consuming information detection is that a large amount of engineering business data from different data sources often contains a large amount of irrelevant or redundant data related to the detection task, which is not convenient for the detection personnel to carry out daily work on the same engineering business data. detection. Based on this, in the information detection method of some embodiments of the present disclosure, firstly, the engineering item detection information and the first attribute information set corresponding to the target engineering business are acquired. Wherein, the above-mentioned target engineering service is an engineering service to be subjected to information detection, and the above-mentioned engineering project detection information includes a project identification, a sub-project information group, and a project attribute information set, and each item attribute information in the above-mentioned project attribute information set includes a project attribute name, Each first attribute information in the first attribute information set includes a first attribute name. Here, the attributes corresponding to the target engineering business and the source information of some attributes can be determined. Next, select item attribute names different from each first attribute name included in the first attribute information set from each item attribute name included in the above item attribute information set as remaining attribute names to obtain a group of remaining attribute names. In this way, each attribute to be detected with an undetermined source can be obtained, so as to facilitate subsequent determination of source information for each attribute to be detected. Thirdly, a second attribute information set matching the item identification included in the engineering item detection information and the remaining attribute name group is obtained from a preset data source. Wherein, each second attribute information in the above-mentioned second attribute information set includes a second attribute name. Thus, source information can be determined for each attribute to be detected for which source information has not been determined. Subsequently, each first attribute information in the first attribute information set and each second attribute information in the second attribute information set are determined as target attribute information to obtain a target attribute information set. Therefore, the attributes to be detected corresponding to the target engineering business can be combined together, and there is no need to consider attributes that are irrelevant or redundant to the detection task, so as to facilitate subsequent extraction of corresponding attributes according to the sub-item information in the sub-item information group. Then, based on the sub-item information group included in the engineering item detection information, the above-mentioned target attribute information set is extracted to obtain the target item information set. In this way, each attribute set corresponding to each sub-item information can be obtained, which is convenient for subsequently determining the attribute value corresponding to the attribute according to the source information corresponding to the attribute in the attribute set, and for subsequent information detection. Wherein, the above-mentioned target item information may include information of each attribute to be detected. Afterwards, based on the above-mentioned target item information set, a sub-item attribute detection information set is generated. Thus, for each attribute set, the sub-item attribute detection information corresponding to each sub-item information can be determined. Finally, the display device is controlled to display the above-mentioned sub-item attribute detection information set for detection information. In this way, the information detection of the sub-item attribute detection information set can be completed by the detection personnel through the display device. Therefore, for a large amount of engineering business data from different data sources, this disclosure first determines the information of the attributes to be detected corresponding to the target engineering business, then determines the attribute set corresponding to the detection task, and determines the item information corresponding to the detection task through the attribute set , so that inspectors do not need to consider irrelevant or redundant attributes of the inspection task during information inspection, and it is more convenient and quick to conduct daily inspections on business data. Thus, time-consuming information detection can be shortened.

Description of drawings

The above and other features, advantages and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic and elements and elements have not necessarily been drawn to scale.

FIG. 1 is a flowchart of some embodiments of an information detection method according to the present disclosure;

Fig. 2 is a schematic structural diagram of some embodiments of an information detection device according to the present disclosure;

FIG. 3 is a schematic structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure.

detailed description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the disclosure are shown in the drawings, it should be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these examples are provided so that the understanding of this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for exemplary purposes only, and are not intended to limit the protection scope of the present disclosure.

It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings. In the case of no conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other.

It should be noted that concepts such as "first" and "second" mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the sequence of functions performed by these devices, modules or units or interdependence.

It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative and not restrictive, and those skilled in the art should understand that unless the context clearly indicates otherwise, it should be understood as "one or more" Multiple".

The names of messages or information exchanged between multiple devices in the embodiments of the present disclosure are used for illustrative purposes only, and are not used to limit the scope of these messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings and embodiments.

FIG. 1 shows a flow 100 of some embodiments of the information detection method according to the present disclosure. The information detection method includes the following steps:

Step 101, acquiring engineering item detection information and a first attribute information set corresponding to a target engineering business.

In some embodiments, the execution body (such as a computing device) of the information detection method may obtain the engineering item detection information and the first attribute information set corresponding to the target engineering business through a wired connection or a wireless connection. Wherein, the above-mentioned target engineering service may be an engineering service for which information detection is to be performed. For example, the above-mentioned target project may be a specific warehouse project or construction project, or an abstract audit project. The above engineering project detection information may be information to be detected in the target engineering business corresponding to the detection task. The above detection task may be a task of detecting the target engineering business to find problems. In practice, the above detection tasks can be treated as projects. The above engineering item detection information may include item identification, sub-item information set and item attribute information set. The above item identifier may be an identifier corresponding to the detection task. The above item identifiers correspond to the detection tasks one by one. The sub-item information in the above-mentioned sub-item information group may be the information to be detected corresponding to the detection subtask. The above detection subtask may be a task obtained by disassembling the above detection task according to steps. Each item attribute information in the above item attribute information set may include an item attribute name. There is a one-to-one correspondence between the above project attribute names and attributes. The above attribute may be but not limited to one of the following: department name, event number, event name, event occurrence time and document number. The above voucher number can uniquely identify the voucher. Each first attribute information in the first attribute information set may be used to characterize an attribute obtained from a preset data warehouse. The aforementioned preset data warehouse may be a preset data warehouse including some attributes of the target engineering business. Each first attribute information in the first attribute information set may include a first attribute name and first source information. The above-mentioned first attribute name may be the name of the attribute to be detected obtained from a preset data warehouse. The above-mentioned first source information may be information about data tables and columns in the data warehouse corresponding to attributes. The engineering item detection information and the first attribute information set corresponding to the target engineering business can be acquired through a preset data warehouse.

As an example, the above detection task may be to detect whether there is error information in the target engineering business. The above detection subtask may be to detect whether the voucher in the target engineering business is wrong.

Step 102 , selecting item attribute names different from each first attribute name included in the first attribute information set from each item attribute name included in the item attribute information set as remaining attribute names to obtain a group of remaining attribute names.

In some embodiments, the execution subject may select project attribute names different from the first attribute names included in the first attribute information set from the item attribute names included in the item attribute information set as the remaining attribute names, Get the remaining set of attribute names. Wherein, the difference from each first attribute name included in the above-mentioned first attribute information set may be that the project attribute name is different from each first attribute name in each first attribute name. The remaining attribute names in the above remaining attribute name group may be names of attributes not obtained from the above preset data warehouse.

In step 103, a second attribute information set matching the item identification and remaining attribute name groups included in the project detection information is acquired from a preset data source.

In some embodiments, the execution subject may obtain a second attribute information set that matches the item identifier included in the engineering project detection information and the remaining attribute name group from a preset data source. Wherein, the aforementioned preset data source may include a database corresponding to each subsystem of the target engineering business. For example, the above-mentioned subsystem may be but not limited to one of the following: purchasing system, warehouse management system. Each second attribute information in the above second attribute information set may be used to characterize an attribute obtained from a preset data source. Each second attribute information in the above-mentioned second attribute information set includes a second attribute name and second source information. The above-mentioned second attribute name may be the name of the attribute to be detected obtained from a preset data source (for example, credential type, credential detailed information). The above credential type may be a credential file type. The above credential detail information may be used to characterize the credential. The above-mentioned second source information may be information about data tables and columns corresponding to attributes in the preset data source. The second attribute information set that matches the item identification included in the engineering item detection information and the remaining attribute name group can be obtained from a preset data source by establishing a database connection.

Step 104, determining each first attribute information in the first attribute information set and each second attribute information in the second attribute information set as target attribute information to obtain a target attribute information set.

In some embodiments, the execution subject may determine each first attribute information in the first attribute information set and each second attribute information in the second attribute information set as target attribute information to obtain a target attribute information set. Wherein, the target attribute information in the above target attribute information set may be the information of the attribute to be detected. The target attribute information in the above target attribute information set includes target attribute name and attribute source information. The above-mentioned target attribute name may be the name of the attribute to be detected. The above attribute source information may be the information of the data table and column where the corresponding attribute is located.

Step 105, based on the sub-item information group included in the engineering item detection information, extract the target attribute information set to obtain the target item information set.

In some embodiments, the execution subject may extract the target attribute information set based on the sub-item information group included in the engineering item detection information in various ways to obtain the target item information set. Wherein, the target item information in the above target item information set may be the detection type and attribute information corresponding to the detection subtask.

In some optional implementation manners of some embodiments, each sub-item information in the foregoing sub-item information group includes a sub-item identifier, a sub-item attribute identifier group, and a detection type. The above-mentioned sub-item identifier may be an identifier corresponding to the detection subtask. The above sub-item identifiers are in one-to-one correspondence with the detection sub-tasks. The sub-item attribute identifiers in the above-mentioned sub-item attribute identifier group may be identifiers of attributes corresponding to the detection subtasks. The above detection types can be used to characterize the types of detection subtasks. The above-mentioned detection type can be a suspicious point screening type or a comprehensive analysis type. The above suspicion screening type may be a detection subtask type for detecting voucher detailed information. The above comprehensive analysis type may be a detection subtask of detecting each attribute according to the attribute value. The above-mentioned executive body can extract and process the above-mentioned target attribute information set based on the sub-item information group included in the above-mentioned engineering project detection information to obtain the target project information set through the following steps:

In the first step, for each sub-item information in the above-mentioned sub-item information group, perform the following steps:

The first sub-step is to use the target attribute information in the above target attribute information set that matches any sub-item attribute identifier included in the above-mentioned sub-item information as sub-item attribute information to obtain a sub-item attribute information group. Wherein, matching with any sub-item attribute identifier included in the above-mentioned sub-item information may mean that the attribute corresponding to the target attribute information is the same as the attribute corresponding to any sub-item attribute identifier. The sub-item attribute information in the above-mentioned sub-item attribute information group may be information corresponding to the attribute of the same detection subtask.

The second sub-step is to determine the above-mentioned sub-item attribute information group and the sub-item identification included in the above-mentioned sub-item information as the target item information.

Step 106: Generate a sub-item attribute detection information set based on the target item information set.

In some embodiments, the execution subject may generate the sub-item attribute detection information set based on the target item information set in various ways. Wherein, the sub-item attribute detection information in the sub-item attribute detection information set may be the attribute value information corresponding to each attribute at a certain moment.

In some optional implementation manners of some embodiments, the execution subject may generate a sub-item attribute detection information set based on the target item information set. For each target item information in the above target item information set, the following steps can be performed:

The first step is to generate a detailed source information group based on the sub-item attribute information group included in the target item information. Wherein, the detail source information in the above detail source information group may be used to represent the corresponding attribute and the storage location of the attribute value. The above storage location may be the location of the column corresponding to the attribute in the corresponding data table. For each sub-item attribute information in the above-mentioned sub-item attribute information group, the target attribute name and attribute source information corresponding to the above-mentioned sub-item attribute information can be determined as the detail source information.

The second step is to select sub-item attribute information satisfying preset attribute conditions from the sub-item attribute information groups included in the target item information as associated attribute information to obtain an associated attribute information set. Wherein, the aforementioned preset attribute condition may be that the attribute corresponding to the attribute information of the sub-item is a preset attribute. The aforementioned preset attributes may include department name and item number. The associated attribute information in the above-mentioned associated attribute information set may be used to characterize the attribute of department name or item number.

The third step is to generate a sub-item attribute detection information set based on the above-mentioned associated attribute information set and the above-mentioned detail source information set. For each detail source in the above detail source group, the following steps can be performed:

The first sub-step is to determine the aforementioned associated attribute information set and the aforementioned detailed source information as query condition information. Wherein, the above query condition information may be the query condition information required for querying each attribute value.

The second sub-step is to generate sub-item attribute detection information based on the above query condition information. Wherein, the sub-item attribute detection information may be generated based on the above query condition information through a database query method.

Step 107, control the display device to display the sub-item attribute detection information set for detection information.

In some embodiments, the execution subject may control the display device to display the sub-item attribute detection information set for detection information. Wherein, the above-mentioned display device may be a device with a display screen. The above-mentioned sub-item attribute detection information set can be displayed through a display device, so that inspectors can perform query operations on the sub-item attribute detection information set to complete information detection.

Optionally, the above execution subject may also perform the following steps:

In the first step, in response to receiving the user login information for the preset detection interface information, the above preset detection interface information is sent to the target terminal for user query. Wherein, the above-mentioned preset detection interface information may include suspicious point screening tab page information and comprehensive analysis tab page information. The information on the tab page for suspicious screening may be used to represent the tab page for detecting the detailed information of the voucher. The above comprehensive analysis tab page information may be used to characterize the tab page for detecting each attribute according to the attribute value. The user login information may be information input by the user for logging into the interface corresponding to the preset detection interface information. The aforementioned target terminal may be the aforementioned display device.

Step 2: In response to receiving the suspicious point query information for the above suspicious point screening tab page information, generate suspicious point summary information based on the above suspicious point query information and the above sub-item attribute detection information set, and send the above suspicious point summary information to the above target Terminal for viewing. Wherein, the above doubt summary information may be information corresponding to the count of each doubt.

In some optional implementations of some embodiments, the suspicious point query information may include detected department information and detection time information. Wherein, the detected department information may be used to represent the department corresponding to the target engineering business. The above detection time information may be used to characterize the time period corresponding to the detection subtask. The attribute detection information of each sub-item in the above-mentioned sub-item attribute detection information set may include department name, event occurrence time, voucher number, project output value, project consumption value, voucher type and voucher detail information. The above project output value may be the added value of the target engineering business. The above-mentioned item consumption value may be the value of the reduction of the target engineering business. The above credential types may include image type or text type. The above image types can be used to indicate that the credential is a file saved in the form of an image. For example, the certificate of the above picture type may be a JPEG (Joint Photographic Experts Group, Joint Photographic Experts Group) file or a PDF (Portable Document Format, Portable Document Format) file in the form of a picture. The above text type can be used to represent the credential as a file saved in text form. For example, the above-mentioned voucher of the text type may be a PDF file in text form. The above-mentioned executive body can generate suspicious point summary information based on the above-mentioned doubtful point query information and the above-mentioned sub-item attribute detection information set:

The first step is to select the sub-item attribute detection information matching the above-mentioned suspicious point query information from the above-mentioned sub-item attribute detection information set as the target attribute detection information, and obtain the target attribute detection information set. Wherein, matching with the above-mentioned suspicious point query information may be: the department name included in the sub-item attribute detection information is the same as the detected department information included in the above-mentioned suspicious point query information, and the occurrence time of the event included in the sub-item attribute detection information is included in the above-mentioned suspicious point query information. within the time period corresponding to the detection time information. The target attribute detection information in the above target attribute detection information set can be used to characterize the suspicious point information that is queried.

In the second step, for each target attribute detection information in the above target attribute detection information set, the following steps are performed:

In the first sub-step, in response to determining that the voucher type corresponding to the target attribute detection information is an image type, image recognition is performed on the voucher detail information corresponding to the target attribute detection information to obtain the target value and value type. Wherein, the above-mentioned target value may be the real value displayed on the corresponding voucher. The above value types can be used to represent that the real value displayed on the corresponding voucher is the output value of the project or the consumption value of the project. The image recognition of the credential detail information corresponding to the above target attribute detection information can be performed through a preset image recognition method to obtain the target value and value type.

As an example, the above preset image recognition methods may include but not limited to at least one of the following: R-CNN (Region-based Convolutional Neural Networks, regional convolutional neural network) method, SSD (SingleShot MultiBox Detector, multi-scale detection strategy) Law.

In the second sub-step, in response to determining that the voucher type corresponding to the target attribute detection information is a text type, perform text recognition on the voucher detail information corresponding to the target attribute detection information to obtain the target value and value type. The text recognition of the voucher detail information corresponding to the above target attribute detection information can be performed through a preset text recognition method to obtain the target value and value type.

As an example, the aforementioned preset text recognition method may include but not limited to at least one of the following: an attention-based text recognition method, a transformer-based text recognition method.

In the third sub-step, in response to determining that the above-mentioned value type is a preset value type, matching processing is performed on the project output value corresponding to the above-mentioned target attribute detection information and the above-mentioned target value to obtain value matching information. Wherein, the aforementioned preset value type may be a value type that indicates that the real value displayed on the corresponding voucher is the output value of the project. Firstly, it is determined whether the output value of the project corresponding to the above-mentioned target attribute detection information is the same as the above-mentioned target value. Then, if the output value of the project corresponding to the above-mentioned target attribute detection information is the same as the above-mentioned target value, the preset matching success flag is determined as the value matching information. Wherein, the above preset matching success identifier may be used to represent the matching success. Finally, if the project output value corresponding to the above-mentioned target attribute detection information is different from the above-mentioned target value, the preset matching failure flag is determined as the value matching information. Wherein, the above-mentioned preset matching failure identifier may be used to represent the matching failure.

The fourth sub-step, in response to determining that the above value type is not a preset value type, performs matching processing on the item consumption value corresponding to the above target attribute detection information and the above target value to obtain value matching information. First, it is determined whether the item consumption value corresponding to the target attribute detection information is the same as the target value. Then, if the item consumption value corresponding to the above-mentioned target attribute detection information is the same as the above-mentioned target value, the preset matching success flag is determined as the value matching information. Finally, if the item consumption value corresponding to the above-mentioned target attribute detection information is different from the above-mentioned target value, the preset matching failure flag is determined as the value matching information.

In the fifth sub-step, in response to the above-mentioned value matching information not satisfying the preset matching condition, the above-mentioned target attribute detection information is determined as the first suspect information. Wherein, the above-mentioned preset matching condition may be that the above-mentioned value matching information is an identifier of a successful preset matching. The above-mentioned first suspicious point information may be the filtered out suspicious point information.

The third step is to determine each object attribute detection information in the above target attribute detection information set that is different from each determined first suspicious point information as a target attribute detection information group. Wherein, being different from each determined first suspicious point information may be that the target attribute detection information is different from each first suspicious point information included in each first suspicious point information. The target attribute detection information in the above target attribute detection information group may be information about the same item as the value information displayed on the voucher and the corresponding attribute information.

In the fourth step, each voucher number included in the target attribute detection information group is determined as a voucher number set. Wherein, the voucher numbers in the above voucher number set may be used to represent vouchers whose value information is the same as the corresponding attribute information.

The fifth step, for each voucher number in the above voucher number set, perform the following steps:

The first sub-step is to determine the sum of the output values of each project included in the target attribute detection information in the target attribute detection information group that matches the voucher number as the aggregate value of project output. Wherein, matching with the above-mentioned voucher number may mean that the voucher number corresponding to the target attribute detection information is the same as the above-mentioned voucher number. The aggregated value of the above-mentioned project output may be the total value added by the items corresponding to the above-mentioned voucher number.

In the second sub-step, the sum of the consumption values of each item included in the target attribute detection information matching the voucher number in the target attribute detection information group is determined as the summary value of item consumption. Wherein, matching with the above-mentioned voucher number may mean that the voucher number corresponding to the target attribute detection information is the same as the above-mentioned voucher number. The summary value of the above-mentioned item consumption may be the total value of the reduction of items corresponding to the above-mentioned voucher number.

In the third sub-step, in response to determining that the summary value of the project output is different from the summary value of the project consumption, determine the above-mentioned voucher number, the summary value of the project output and the summary value of the project consumption as target doubt information.

The sixth step is to determine the target attribute detection information in the target attribute detection information group that matches the voucher number included in each determined target suspicious point information as the second suspicious point information, and obtain the second suspicious point information set. Wherein, matching the determined voucher number included in each target suspicious point information may mean that the voucher number included in the target attribute detection information is the same as the voucher number included in at least one target suspicious point information. The second suspicious information in the second suspicious information set may be information to be detected corresponding to suspicious items. The above-mentioned doubtful matters may be matters in which the aggregated value of project output and the aggregated value of project consumption are different.

In the seventh step, based on the determined first doubt information and second doubt information sets, generate doubt certificate number sets and doubt numbers. Wherein, the doubtful voucher numbers in the above-mentioned doubtful voucher number set may be the numbers of the vouchers corresponding to the suspicious items. The number of doubts mentioned above may be the total number of doubts corresponding to each item with doubts. First, determine the voucher number corresponding to each first doubtful information included in each first suspicious point information, and the voucher number corresponding to each second suspicious point information in the second suspicious point information set as the redundant suspicious point voucher number, and obtain the redundant suspicious point voucher number set. Wherein, the redundant doubtful voucher numbers in the redundant doubtful voucher number set may be the numbers of the corresponding vouchers of the suspicious items. Then, the number of redundant doubtful voucher numbers in the redundant doubtful voucher number set is determined as the number of doubtful points. Finally, de-redundancy processing is performed on the above redundant doubtful voucher number set to obtain the doubtful voucher number set. Redundancy may be removed from the redundant doubtful voucher number set, and each redundant doubtful voucher number in the redundant doubtful voucher number set after redundancy removal may be determined as a doubtful voucher number to obtain a doubtful voucher label set.

The eighth step is to determine the above-mentioned detected department information, the above-mentioned detection time information, the above-mentioned doubtful point certificate number set, and the above-mentioned doubtful point number as suspicious point summary information.

As an invention point of the embodiment of the present disclosure, the above-mentioned doubtful point summary information generation step and related content solve the technical problem two mentioned in the background technology "the existing information detection method does not detect the voucher engineering business data from various data sources. Testing or lagging testing can easily cause wrong voucher engineering business data to be ignored, resulting in low accuracy of information testing.” The problems that lead to low accuracy of information detection are often as follows: No more detection or lag detection of credential engineering business data from various data sources. If the above problems are solved, the effect of improving the accuracy of information detection can be achieved. In order to achieve this effect, the present disclosure can firstly identify each voucher to determine whether the voucher is the same as the corresponding project output value or project consumption value when performing the information detection task of suspicious point screening. If the voucher is not the same as the corresponding project output value or project consumption value, then determine the item information corresponding to the voucher as suspicious information. Thus, problem data inconsistent with the credential information can be screened out through the credential information. Then, for each item information that is not determined as suspicious point information, it is determined whether the item output summary value corresponding to the item is the same as the project consumption summary value. If the project output summary value corresponding to the determined item is different from the project consumption summary value, the item information corresponding to the item is determined as doubt information. As a result, the problem data in which the summary value of project output is inconsistent with the summary value of project consumption is further screened out. Therefore, the steps of generating the above-mentioned suspicious point summary information and its related content can be pre-tested on the voucher engineering business data from various data sources, and then the value of each specific item can be detected to avoid wrong voucher engineering business Data is ignored. Thus, the accuracy of information detection can be improved.

Optionally, the above execution subject may also perform the following steps:

In the first step, in response to receiving the details view information for the above-mentioned suspicious point summary information, based on the above-mentioned detailed view information and the above-mentioned sub-item attribute detection information set, generate a suspicious point attribute information set, and send the above-mentioned doubtful point attribute information set to the above-mentioned target terminal For selection of any suspicious point attribute information. Wherein, the above detailed viewing information may be information of each doubtful point corresponding to each doubtful point item. The above-mentioned executive body can generate a suspicious point attribute information set based on the above-mentioned detailed view information and the above-mentioned sub-item attribute detection information set in various ways, and send the above-mentioned suspicious point attribute information set to the above-mentioned target terminal for selection of any suspicious point attribute information.

In some optional implementation manners of some embodiments, the above detailed viewing information may include a set of target voucher numbers. Wherein, the target voucher number in the above target voucher number set may be the number of the voucher corresponding to the suspicious item. There is a one-to-one correspondence between the target voucher numbers in the above-mentioned target voucher number set and the doubtful voucher numbers in the above-mentioned doubtful voucher number set. The above-mentioned executive body can generate a suspicious point attribute information set based on the above-mentioned detailed view information and the above-mentioned sub-item attribute detection information set through the following steps:

Step 1: From the above-mentioned sub-item attribute detection information set, select the sub-item attribute detection information that matches any target voucher number in the target voucher number set included in the above-mentioned detail viewing information as attribute detail information, and obtain the attribute detail information set. Wherein, the match with any target voucher number in the target voucher number set included in the detailed viewing information may be that the voucher number corresponding to the sub-item attribute detection information is the same as any target voucher number in the target voucher number set. The attribute detail information in the above attribute detail information set may be any suspicious information corresponding to the suspicious item.

In the second step, for each attribute detail information in the above attribute detail information set, perform the following steps:

The first sub-step is to convert the project output value corresponding to the above attribute detailed information to obtain the hash value of the project output. Among them, the above project output hash value can be used to represent the project output value. The hash algorithm can be used to convert the project output value corresponding to the above attribute details to obtain the hash value of the project output.

The second sub-step is to convert the item consumption value corresponding to the above attribute detail information to obtain the item consumption hash value. Wherein, the above item consumption hash value can be used to represent the item consumption value. The above hash algorithm can be used to convert the item consumption value corresponding to the above attribute detail information to obtain the item consumption hash value.

The third sub-step is to determine the department name, voucher number, project output hash value, and project consumption hash value corresponding to the above attribute details information as suspicious attribute information.

In the second step, in response to receiving selection information for any suspicious point attribute information in the above-mentioned doubtful point attribute information set, based on the above-mentioned selection information, authority verification information is generated, and the above-mentioned authority verification information is sent to the above-mentioned target terminal for confirmation of authority. Wherein, the above-mentioned selected information may be suspicious information selected by the above-mentioned inspector. The authority verification information may be information for verifying whether the detection personnel have the authority to view unprocessed information. The above-mentioned unprocessed information may be suspicious information before conversion and processing. The selection information and the preset authority verification window information may be determined as authority verification information, and the authority verification information may be sent to the target terminal for authority confirmation. Wherein, the above preset authority verification window information may be used to characterize the authority verification window. The authority verification window may include an authority password input control and a password confirmation control. The above permission password input control may be a control for receiving password information input by the user. The above password information may be a character string sequence composed of numbers and letters. The above-mentioned password confirming control may be a control for confirming the password information received by the sending authority password input control to the server.

In a third step, in response to receiving the authority confirmation information for the authority verification information, based on the authority confirmation information, generate target doubt attribute information for display by the target terminal. Wherein, the authority confirmation information may include the selection information and the authority password. The above-mentioned target doubt attribute information may be the information of doubt corresponding to the above-mentioned selection information including the actual value attribute value. The following steps can be used to generate target suspicious point attribute information based on the above permission confirmation information for display by the above target terminal:

The first sub-step is to verify the authority password included in the authority confirmation information to obtain target verification information. Wherein, the above-mentioned target verification information may be used to indicate whether the above-mentioned permission password is the same as the preset viewing permission password. The aforementioned preset viewing authority password may be a preset character string corresponding to the viewing authority. The authority password included in the above authority confirmation information may be verified through a character string matching algorithm to obtain target verification information.

In the second sub-step, in response to determining that the target verification information satisfies the preset verification condition, select the sub-item attribute detection information matching the selection information from the sub-item attribute detection information set as the target suspicious point attribute information. Wherein, the above-mentioned preset verification condition may be that the above-mentioned target verification information indicates that the above-mentioned permission password is the same as the preset viewing permission password. Matching with the selection information may be that each attribute included in the sub-item attribute detection information is in one-to-one correspondence with the attributes included in the selection information.

The third sub-step is to send the attribute information of the above-mentioned target suspicious point to the above-mentioned target terminal for display.

As an invention point of the embodiments of the present disclosure, the above-mentioned suspicious point attribute information generation steps and related contents solve the technical problem three mentioned in the background technology: "The existing information detection method uses a direct display method to display some projects that are not easy to disclose. Business data can easily lead to a higher risk of data leakage.” The reasons for the high risk of data leakage are often as follows: the existing information detection methods directly display some engineering business data that are not easy to disclose. If the above problems are solved, the effect of reducing the risk of data leakage can be achieved. In order to achieve this effect, the present disclosure can perform hash conversion processing on the information to be viewed without affecting the information detection result. If the inspector really needs to view the actual value information before the conversion process, he can obtain the viewing authority through authority verification. Usually, the inspector can view multiple pieces of suspicious information with only one permission verification if the permission has not timed out. Therefore, the disclosure can perform an irreversible conversion operation on some engineering business data that is not easy to disclose during information detection, and then display the converted data to avoid data leakage. Thus, the risk of data leakage can be reduced.

Optionally, the above execution subject may also perform the following steps:

In the first step, in response to receiving the sub-item comprehensive analysis query information for the above-mentioned comprehensive analysis tab page information, a sub-item comprehensive analysis information set is generated based on the above-mentioned sub-item comprehensive analysis query information and the above-mentioned sub-item attribute detection information set. Wherein, the comprehensive analysis and query information of the sub-items may be information about the proportion of the project output value corresponding to each item to the total value. The above sub-item comprehensive query information may include target detection department, target detection time information, target value type and target item name set. The above target detection department may be a department to be detected. The above target detection time information may be used to characterize the time period corresponding to the detection subtask. The above-mentioned target value type can be an output type or a consumption type. The above output types can be used to indicate that the output value of each item corresponding to the item is not empty. The above consumption type can be used to indicate that the consumption value of each item corresponding to the item is not empty. The target item names in the above target item name set may be names of items corresponding to the above target value types. The above total value may be the total project output value corresponding to each item. The comprehensive analysis information of each sub-item in the above-mentioned sub-item comprehensive analysis information set includes item value information and item value percentage. The above project value information may be information on project output value corresponding to the item. The above project value percentage may be the ratio of the project output value corresponding to the item to the total value. The sub-item comprehensive analysis information set can be generated based on the above-mentioned sub-item comprehensive analysis query information and the above-mentioned sub-item attribute detection information set through the following steps:

The first sub-step is to select the sub-item attribute detection information matching the above-mentioned sub-item comprehensive analysis query information from the above-mentioned sub-item attribute detection information set as the target item information, and obtain the target item information set. Wherein, matching with the above-mentioned sub-item comprehensive analysis query information may be: the department name corresponding to the sub-item attribute detection information is the same as the target detection department included in the above-mentioned sub-item comprehensive analysis query information, and the item name corresponding to the sub-item attribute detection information is the same as the above-mentioned Any one of the target items included in the sub-item comprehensive analysis query information has the same name, and the occurrence time of the item corresponding to the sub-item attribute detection information is within the time period represented by the target detection time information included in the sub-item comprehensive analysis query information, and the sub-item attribute detection information The corresponding project output value matches the above-mentioned sub-item comprehensive analysis query information including the target value type. Matching with the above subitem comprehensive analysis query information including the target value type may be: the target value type is an output type, and the item output value corresponding to the subitem attribute detection information is not empty. The target item information in the above target item information set may be the information of each attribute of the item.

In the second sub-step, in response to determining that the above-mentioned target value type is an output type, for each target item name in the above-mentioned target item name set, perform the following steps:

Step 1, determining the sum of the output values of each project corresponding to each target item information in the above-mentioned target item information set and matching the above-mentioned target item name as the target item value. Wherein, matching with the above target item name may mean that the item name corresponding to the target item information is the same as the target item name. The above target item value may be the total project output value corresponding to the item.

Step 2, determining the name of the above-mentioned target item and the value of the above-mentioned target item as item value information. Wherein, the above-mentioned project value information may be the information of the item and the total output value of the item corresponding to the item.

The third sub-step is to determine the sum of the values of each target item included in the determined value information of each item as the total value.

The fourth sub-step, for each item value information included in the determined item value information, determine the percentage of the target item value included in the above item value information in the above total value as the item value percentage, and combine the above item value information and The above item value percentage is determined as the comprehensive analysis information of the subitem.

In the second step, the above-mentioned sub-item comprehensive analysis information set is sent to the above-mentioned target terminal for the target user to select the item value information corresponding to any sub-item comprehensive analysis information.

Step 3: In response to receiving selection confirmation information for any sub-item comprehensive analysis information included in the sub-item comprehensive analysis information set, generate sub-item detailed information for detection information. Wherein, the above-mentioned selection confirmation information may be the comprehensive analysis information of the sub-items selected by the above-mentioned inspector. The above sub-item detailed information may be item value information corresponding to the item. The item value information corresponding to the above selection confirmation information may be determined as sub-item detail information for detection information.

Optionally, the above execution subject may also perform the following steps:

In the first step, in response to receiving the chart request information for the comprehensive analysis tab page information, determine the project value percentage included in each comprehensive analysis information in the above-mentioned sub-item comprehensive analysis information set as the project value percentage set. Wherein, the above chart request information may be information requesting to display the item value percentage corresponding to each item in a chart. The above item value percentage set may be a set of item value percentages corresponding to each item.

In the second step, based on the above-mentioned item value percentage set, generate item value proportion map information, and send the above-mentioned item value proportion map information to the above-mentioned target terminal for information detection. Wherein, the above-mentioned item value ratio chart information may be used to represent a chart showing the item value percentage corresponding to each item. Through the SpringBoot framework and the JAVA programming language, based on the above-mentioned project value percentage set, the project value percentage map information can be generated, and the above-mentioned project value percentage map information can be sent to the above-mentioned target terminal for detection information.

The above-mentioned embodiments of the present disclosure have the following beneficial effects: time-consuming information detection can be shortened through the information detection methods of some embodiments of the present disclosure. Specifically, the reason for the long time-consuming information detection is that a large amount of engineering business data from different data sources often contains a large amount of irrelevant or redundant data related to the detection task, which is not convenient for the detection personnel to carry out daily work on the same engineering business data. detection. Based on this, in the information detection method of some embodiments of the present disclosure, firstly, the engineering item detection information and the first attribute information set corresponding to the target engineering business are acquired. Wherein, the above-mentioned target engineering service is an engineering service to be subjected to information detection, and the above-mentioned engineering project detection information includes a project identification, a sub-project information group, and a project attribute information set, and each item attribute information in the above-mentioned project attribute information set includes a project attribute name, Each first attribute information in the first attribute information set includes a first attribute name. Here, the attributes corresponding to the target engineering business and the source information of some attributes can be determined. Next, select item attribute names different from each first attribute name included in the first attribute information set from each item attribute name included in the above item attribute information set as remaining attribute names to obtain a group of remaining attribute names. In this way, each attribute to be detected with an undetermined source can be obtained, so as to facilitate subsequent determination of source information for each attribute to be detected. Thirdly, a second attribute information set matching the item identification included in the engineering item detection information and the remaining attribute name group is obtained from a preset data source. Wherein, each second attribute information in the above-mentioned second attribute information set includes a second attribute name. Thus, source information can be determined for each attribute to be detected for which source information has not been determined. Subsequently, each first attribute information in the first attribute information set and each second attribute information in the second attribute information set are determined as target attribute information to obtain a target attribute information set. Therefore, the attributes to be detected corresponding to the target engineering business can be combined together, and there is no need to consider attributes that are irrelevant or redundant to the detection task, so as to facilitate subsequent extraction of corresponding attributes according to the sub-item information in the sub-item information group. Then, based on the sub-item information group included in the engineering item detection information, the above-mentioned target attribute information set is extracted to obtain the target item information set. In this way, each attribute set corresponding to each sub-item information can be obtained, which is convenient for subsequently determining the attribute value corresponding to the attribute according to the source information corresponding to the attribute in the attribute set, and for subsequent information detection. Wherein, the above-mentioned target item information may include information of each attribute to be detected. Afterwards, based on the above-mentioned target item information set, a sub-item attribute detection information set is generated. Thus, for each attribute set, the sub-item attribute detection information corresponding to each sub-item information can be determined. Finally, the display device is controlled to display the above-mentioned sub-item attribute detection information set for detection information. In this way, the information detection of the sub-item attribute detection information set can be completed by the detection personnel through the display device. Therefore, for a large amount of engineering business data from different data sources, this disclosure first determines the information of the attributes to be detected corresponding to the target engineering business, then determines the attribute set corresponding to the detection task, and determines the item information corresponding to the detection task through the attribute set , so that inspectors do not need to consider irrelevant or redundant attributes of the inspection task during information inspection, and it is more convenient and quick to conduct daily inspections on business data. Thus, time-consuming information detection can be shortened.

Further referring to FIG. 2 , as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of an information detection device. These device embodiments correspond to those method embodiments shown in FIG. 1 , and the device specifically It can be applied to various electronic devices.

As shown in FIG. 2 , the information detection device 200 of some embodiments includes: a first acquisition unit 201 , a selection unit 202 , a second acquisition unit 203 , a determination unit 204 , an extraction processing unit 205 , a generation unit 206 and a display unit 207 . Wherein, the first acquisition unit 201 is configured to acquire engineering project detection information and a first attribute information set corresponding to the target engineering business, wherein the above-mentioned target engineering business is an engineering business to be subjected to information detection, and the above-mentioned engineering project detection information includes project Identification, sub-item information group, and item attribute information set, each item attribute information in the above-mentioned item attribute information set includes an item attribute name, and each first attribute information in the above-mentioned first attribute information set includes a first attribute name; selection unit 202 , being configured to select, from each item attribute name included in the item attribute information set, an item attribute name different from each first attribute name included in the first attribute information set as a remaining attribute name, to obtain a remaining attribute name group; The second obtaining unit 203 is configured to obtain from a preset data source a second attribute information set that matches the project identification included in the engineering project detection information and the above remaining attribute name group, wherein the second attribute information set in the above-mentioned second attribute information set Each second attribute information includes a second attribute name; the determining unit 204 is configured to determine each first attribute information in the first attribute information set and each second attribute information in the second attribute information set as a target The attribute information is to obtain the target attribute information set; the extraction processing unit 205 is configured to extract the above-mentioned target attribute information set based on the sub-item information group included in the engineering project detection information to obtain the target item information set; the generation unit 206, It is configured to generate a sub-item attribute detection information set based on the above-mentioned target item information set; the display unit 207 is configured to control a display device to display the above-mentioned sub-item attribute detection information set for detection information.

It can be understood that the units recorded in the device 200 correspond to the steps in the method described with reference to FIG. 1 . Therefore, the operations, features and beneficial effects described above for the method are also applicable to the device 200 and the units contained therein, and will not be repeated here.

Further referring to FIG. 3 , it shows a schematic structural diagram of an electronic device 300 suitable for implementing some embodiments of the present disclosure. The electronic device shown in FIG. 3 is only an example, and should not limit the functions and scope of use of the embodiments of the present disclosure.

As shown in FIG. 3 , an electronic device 300 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 301 that can be randomly accessed according to a program stored in a read-only memory (ROM) 302 or loaded from a storage device 308 Various appropriate actions and processes are executed by programs in the memory (RAM) 303 . In the RAM 303, various programs and data necessary for the operation of the electronic device 300 are also stored. The processing device 301 , ROM 302 and RAM 303 are connected to each other through a bus 304 . A production income/production expenditure (I/O) interface 305 is also connected to the bus 304 .

Typically, the following devices can be connected to the I/O interface 305: production revenue devices 306 including, for example, touch screens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; including, for example, liquid crystal displays (LCDs), speakers, A production disbursement device 307 of a vibrator or the like; a storage device 308 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 309 . The communication means 309 may allow the electronic device 300 to perform wireless or wired communication with other devices to exchange data. While FIG. 3 shows electronic device 300 having various means, it should be understood that implementing or having all of the means shown is not a requirement. More or fewer means may alternatively be implemented or provided. Each block shown in FIG. 3 may represent one device, or may represent multiple devices as required.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, where the computer program includes program codes for executing the methods shown in the flowcharts. In some such embodiments, the computer program may be downloaded and installed from a network via communication means 309 , or from storage means 308 , or from ROM 302 . When the computer program is executed by the processing device 301, the above-mentioned functions defined in the methods of some embodiments of the present disclosure are performed.

It should be noted that the above-mentioned computer-readable medium in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, electrical connections with one or more wires, portable computer diskettes, hard disks, 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), optical storage device, magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code therein. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can transmit, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device . Program code embodied on a computer readable medium may be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

In some embodiments, the client and the server can communicate using any currently known or future-developed network protocols such as HTTP (HyperText Transfer Protocol), and can communicate with digital data in any form or medium (eg, communication network) interconnections. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), internetworks (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network of.

The above-mentioned computer-readable medium may be included in the above-mentioned device, or may exist independently without being incorporated into the electronic device. The above-mentioned computer-readable medium carries one or more programs, and when the above-mentioned one or more programs are executed by the electronic device, the electronic device: acquires the engineering item detection information and the first attribute information set corresponding to the target engineering business, wherein , the above-mentioned target engineering business is an engineering business to be subjected to information detection, and the above-mentioned engineering project detection information includes a project identification, a sub-project information group, and a project attribute information set, and each item attribute information in the above-mentioned project attribute information set includes a project attribute name, and the above-mentioned Each first attribute information in the first attribute information set includes a first attribute name; select from each item attribute name included in the above-mentioned item attribute information set that is different from each first attribute name included in the above-mentioned first attribute information set The project attribute name is used as the remaining attribute name to obtain the remaining attribute name group; the second attribute information set matching the project identification included in the engineering project detection information and the above remaining attribute name group is obtained from the preset data source, wherein the above-mentioned first Each second attribute information in the second attribute information set includes a second attribute name; each first attribute information in the first attribute information set and each second attribute information in the second attribute information set are determined as target attribute information , to obtain the target attribute information set; based on the sub-item information group included in the above-mentioned engineering item detection information, extract and process the above-mentioned target attribute information set to obtain the target item information set; based on the above-mentioned target item information set, generate a sub-item attribute detection information set ; Control the display device to display the above-mentioned sub-item attribute detection information set for detection information.

Computer program code for carrying out operations of some embodiments of the present disclosure can be written in one or more programming languages, or combinations thereof, including object-oriented programming languages—such as Java, Smalltalk, C++ , also includes conventional procedural programming languages—such as the "C" language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connected via the Internet).

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or portion of code that contains one or more logical functions for implementing specified executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by a dedicated hardware-based system that performs the specified functions or operations , or may be implemented by a combination of dedicated hardware and computer instructions.

The units described in some embodiments of the present disclosure may be realized by software or by hardware. The described units may also be set in a processor. For example, it may be described as: a processor includes a first acquisition unit, a selection unit, a second acquisition unit, a determination unit, an extraction processing unit, a generation unit, and a display unit. Wherein, the names of these units do not constitute a limitation on the unit itself under certain circumstances. For example, the first acquisition unit can also be described as “acquire the engineering item detection information and the first attribute information set corresponding to the target engineering business, Wherein, the above-mentioned target engineering service is an engineering service to be subjected to information detection, and the above-mentioned engineering project detection information includes a project identification, a sub-project information group, and a project attribute information set, and each item attribute information in the above-mentioned project attribute information set includes a project attribute name, Each first attribute information in the above-mentioned first attribute information set includes a unit of a first attribute name".

The functions described herein above may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), System on Chips (SOCs), Complex Programmable Logical device (CPLD) and so on.

Some embodiments of the present disclosure further provide a computer program product, including a computer program, and when the computer program is executed by a processor, any one of the above information detection methods is implemented.

The above descriptions are only some preferred embodiments of the present disclosure and illustrations of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solution formed by the specific combination of the above-mentioned technical features, but also covers the above-mentioned invention without departing from the above-mentioned inventive concept. Other technical solutions formed by any combination of technical features or equivalent features. For example, a technical solution formed by replacing the above-mentioned features with technical features having similar functions disclosed in (but not limited to) the embodiments of the present disclosure.

Claims (9)

1. An information detection method, comprising: Obtain engineering project detection information and a first attribute information set corresponding to the target engineering business, wherein the target engineering business is an engineering business to be subjected to information detection, and the engineering project detection information includes a project identification, a sub-project information group, and project attributes an information set, each item attribute information in the item attribute information set includes an item attribute name, and each first attribute information in the first attribute information set includes a first attribute name; Selecting item attribute names different from each first attribute name included in the first attribute information set from each item attribute name included in the item attribute information set as remaining attribute names to obtain a remaining attribute name group; Obtain a second attribute information set that matches the item identification included in the engineering item detection information and the remaining attribute name group from a preset data source, wherein each second attribute information in the second attribute information set include the second attribute name; determining each first attribute information in the first attribute information set and each second attribute information in the second attribute information set as target attribute information to obtain a target attribute information set; Extracting the target attribute information set based on the sub-item information group included in the engineering item detection information to obtain a target item information set; Generate a sub-item attribute detection information set based on the target item information set; Controlling the display device to display the sub-item attribute detection information set for detection information. 2. The method of claim 1, wherein each subitem information in the set of subitem information includes a subitem identification, a subitem attribute identification set, and a detection type; and The step of extracting the target attribute information set based on the sub-item information group included in the engineering item detection information to obtain the target item information set includes: For each sub-item information in the sub-item information group, perform the following steps: Using the target attribute information in the target attribute information set that matches any sub-item attribute identifier included in the sub-item information as sub-item attribute information to obtain a sub-item attribute information group; The sub-item attribute information group and the sub-item identifier included in the sub-item information are determined as target item information. 3. The method of claim 2, wherein the method further comprises: In response to receiving the user login information for the preset detection interface information, the preset detection interface information is sent to the target terminal for user query, wherein the preset detection interface information includes suspicious point screening tab page information and comprehensive Analyze tab page information; In response to receiving suspicious point query information for the suspicious point screening tab page information, based on the suspicious point query information and the sub-item attribute detection information set, generate suspicious point summary information, and send the suspicious point summary information to the target endpoint for viewing. 4. The method of claim 3, wherein the method further comprises: In response to receiving the detailed view information for the suspicious point summary information, based on the detailed view information and the sub-item attribute detection information set, generate a suspicious point attribute information set, and send the suspicious point attribute information set to the target The terminal is used to select any suspicious point attribute information; In response to receiving selection information for any suspicious point attribute information in the suspicious point attribute information set, based on the selection information, generating authority verification information, and sending the authority verification information to the target terminal for confirming authority; In response to receiving authority confirmation information for the authority verification information, based on the authority confirmation information, generate target doubt attribute information for display by the target terminal. 5. The method of claim 3, wherein the method further comprises: In response to receiving the sub-item comprehensive analysis query information for the comprehensive analysis tab page information, based on the sub-item comprehensive analysis query information and the sub-item attribute detection information set, a sub-item comprehensive analysis information set is generated, wherein the The comprehensive analysis information of each sub-item in the sub-item comprehensive analysis information set includes item value information and item value percentage; Sending the sub-item comprehensive analysis information set to the target terminal for the target user to select item value information corresponding to any sub-item comprehensive analysis information; In response to receiving selection confirmation information for any one sub-item comprehensive analysis information included in the sub-item comprehensive analysis information set, sub-item detailed information is generated for detection information. 6. The method of claim 5, wherein the method further comprises: In response to receiving the chart request information for the comprehensive analysis tab page information, determine the project value percentage included in each sub-item comprehensive analysis information in the sub-item comprehensive analysis information set as the project value percentage set; Based on the item value percentage set, generate item value percentage map information, and send the item value percentage map information to the target terminal for information detection. 7. An information detection device, comprising: The first acquiring unit is configured to acquire engineering item detection information and a first attribute information set corresponding to a target engineering business, wherein the target engineering business is an engineering business to be subjected to information detection, and the engineering item detection information includes a project identification . A sub-item information group and an item attribute information set, each item attribute information in the item attribute information set includes an item attribute name, and each first attribute information in the first attribute information set includes a first attribute name; The selection unit is configured to select, from each item attribute name included in the item attribute information set, item attribute names different from each first attribute name included in the first attribute information set as remaining attribute names, and obtain the remaining PropertyNameGroup; The second acquiring unit is configured to acquire a second attribute information set that matches the item identification included in the engineering item detection information and the remaining attribute name group from a preset data source, wherein the second attribute information Each second attribute information in the set includes a second attribute name; A determining unit configured to determine each first attribute information in the first attribute information set and each second attribute information in the second attribute information set as target attribute information to obtain a target attribute information set; The extraction processing unit is configured to extract the target attribute information set based on the sub-item information group included in the engineering item detection information to obtain the target item information set; a generating unit configured to generate a sub-item attribute detection information set based on the target item information set; The display unit is configured to control the display device to display the sub-item attribute detection information set for detection information. 8. An electronic device comprising: one or more processors; a storage device on which one or more programs are stored, When the one or more programs are executed by the one or more processors, the one or more processors are made to implement the method according to any one of claims 1-6. 9. A computer-readable medium, on which a computer program is stored, wherein when the program is executed by a processor, the method according to any one of claims 1-6 is implemented.

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