CN120353812A

CN120353812A - Conflict detection map construction method, device, computer equipment and storage medium

Info

Publication number: CN120353812A
Application number: CN202411359206.3A
Authority: CN
Inventors: 李弦; 吴育人; 庄伯金
Original assignee: Ping An Technology Shenzhen Co Ltd
Current assignee: Ping An Technology Shenzhen Co Ltd
Priority date: 2024-09-26
Filing date: 2024-09-26
Publication date: 2025-07-22

Abstract

The present application relates to information query technology, and discloses a conflict detection graph construction method, device, computer equipment and storage medium, the method comprising: searching for a target table associated with an indicator name according to a statement sample, and determining the hierarchical information corresponding to the indicator name based on the target table; determining the business associated with the indicator name based on a business data set; setting a conflict detection node corresponding to the indicator name according to the indicator name and the hierarchical information; setting data nodes and indicator name nodes, the data nodes including hierarchical nodes, individual nodes and business nodes; setting association paths between mutually associated indicator name nodes, data nodes and conflict detection nodes to obtain a conflict detection graph. By coupling multiple types of business data with the help of conflict detection nodes, a conflict detection graph that can reflect the association relationship between different types of data is generated, so that multiple words contained in the query statement are effectively analyzed for conflicts based on the conflict detection graph, and clear and accurate conflict analysis results are given.

Description

Conflict detection map construction method, device, computer equipment and storage medium

Technical Field

The present application relates to the field of information query technologies, and in particular, to a method and apparatus for constructing a conflict detection spectrum, a computer device, and a storage medium.

Background

The search function of the business analysis platform is to support the user to find business analysis index data to be queried. In order to find accurate values, the search criteria entered by the user will often be a combination of words (or elements). If the words (or elements) input by the user are not in conflict based on the database of the management analysis platform, the search platform needs to return all results meeting the search condition, otherwise, the user needs to be prompted to input the elements in conflict and prompt the conflict type (namely, which element conflicts), and different conflict processing results are returned according to different data types.

A traditional conflict detection method is to analyze a search condition to obtain a plurality of words, search the words in a plurality of data tables with different data types, and then evaluate the conflict according to the search results in the different data tables.

In addition, the method utilizes the atlas expressing the association relation between each word (or element) to perform conflict analysis, but the construction of the atlas at present depends on a large amount of management data input, has long period and large workload, and can cause the conflict analysis result to be ambiguous when a large amount of management data exists.

Disclosure of Invention

The embodiment of the application provides a conflict detection pattern construction method, a device, computer equipment and a storage medium, which aim to couple a plurality of types of business data to construct a conflict detection pattern capable of reflecting the correlation relationship between different types of data in the business data, so that when a user inputs a query statement, a plurality of words contained in the input query statement can be effectively conflict-analyzed according to the conflict detection pattern, clear and high-accuracy conflict analysis results are provided, and whether conflicts occur among the words contained in a search condition and particularly whether the conflicts occur among the words are conveniently determined.

In a first aspect, an embodiment of the present application provides a method for constructing a collision detection map, including:

Acquiring a query statement data set and an operation data set, wherein the query statement data set comprises a plurality of statement samples corresponding to index names, and the operation data set comprises a plurality of operation data tables of target individuals;

Searching a target table associated with the index name in the management data set according to the statement sample, and determining the level information corresponding to the index name based on the target table;

Determining an operation business associated with the index name based on the operation data set;

setting conflict detection nodes corresponding to the index names one by one on the initial map according to the index names and the corresponding level information;

setting data nodes and index name nodes representing index names on an initial map, wherein the data nodes comprise hierarchy nodes corresponding to hierarchy information, individual nodes corresponding to target individuals and service nodes corresponding to business operation;

setting association paths among the index name nodes, the data nodes and the conflict detection nodes which are associated with each other to obtain a conflict detection map;

If the user inputs different index names contained in the query statement, connection can be formed through the conflict detection node, the data node and the associated path, the first index name and the second index name do not form conflict, and otherwise, the first index name and the second index name conflict with each other.

In some embodiments, looking up a target table associated with an index name in the business data set from the statement sample includes:

word segmentation processing is carried out on the sentence sample to obtain at least one candidate field;

screening target fields corresponding to the index names from the candidate fields;

and traversing the camping data set to search a management data table containing the target field as a target table.

In some embodiments, determining the hierarchy information corresponding to the index name based on the target table includes:

determining whether the target table contains a secondary table;

If the secondary table is included, determining a target secondary table in which the index name is located in the secondary table;

And generating hierarchy information according to the target secondary table and the target table.

In some implementations, generating hierarchical information from the target secondary table and the target table includes:

Determining first position information of an index name in a target table, and generating first-level information according to the first position information and a first table type of the target table;

determining second position information of the index name in the target secondary table, and generating second-level information according to the second position information and a second table type of the target table;

generating hierarchy information according to the primary hierarchy information and the secondary hierarchy information.

In some embodiments, after determining whether the target table contains the secondary table, further comprising:

if the secondary table is not included, determining third position information of the index name according to the position of the index name in the target secondary table;

And determining a third table type of the target secondary table, and generating hierarchy information according to the third position information and the third table type.

In some embodiments, the hierarchy nodes include a primary node corresponding to primary hierarchy information and a secondary node corresponding to secondary hierarchy information, and setting the data nodes on the initial map includes:

generating a corresponding first node identifier based on each level one level of level information, and endowing the first node identifier with a first character string obtained by converting the level one level of level information;

generating a corresponding second node identifier based on each second-level hierarchical information, and endowing the second node identifier with a second character string obtained by converting the second-level hierarchical information;

the first node identifier and the second node identifier which are endowed with the character string are arranged on the initial map, and a hierarchical path is arranged between the corresponding first node identifier and second node identifier based on the target secondary table and the target table.

In some embodiments, setting an association path between the index name node, the data node and the conflict detection node, which are associated with each other, obtains a conflict detection map, including:

Setting an associated path between the index name node and the individual node corresponding to the index name node, and

Setting an associated path between the index name node and the service node corresponding to the index name node, and

Setting an associated path between the conflict detection node and the corresponding index name node, and

And setting an association path between the conflict detection node and the corresponding hierarchical node.

In a second aspect, an embodiment of the present application further provides a device for constructing a collision detection map, including:

The data acquisition module is used for acquiring a query statement data set and an operation data set, wherein the query statement data set comprises a plurality of statement samples corresponding to index names, and the operation data set comprises a plurality of operation data tables of target individuals;

The hierarchical analysis module is used for searching a target table associated with the index name in the management data set according to the statement sample and determining hierarchical information corresponding to the index name based on the target table;

The business analysis module is used for determining business related to the index name based on the business data set;

the first node module is used for setting conflict detection nodes corresponding to the index names one by one on the initial map according to the index names and the corresponding level information;

the second node module is used for setting data nodes and index name nodes for representing index names on the initial map, wherein the data nodes comprise level nodes corresponding to the level information, individual nodes corresponding to target individuals and service nodes corresponding to the operation service;

The path generation module is used for setting association paths among the index name nodes, the data nodes and the conflict detection nodes which are associated with each other to obtain a conflict detection map;

In a third aspect, embodiments of the present application further provide a computer device, including a memory and a processor;

A memory for storing a computer program;

And the processor is used for executing the computer program and realizing the conflict detection map construction method when the computer program is executed.

In a fourth aspect, an embodiment of the present application further provides a computer readable storage medium storing a computer program, where the computer program when executed by a processor causes the processor to implement the above-mentioned method for constructing a collision detection map.

The embodiment of the application provides a conflict detection map construction method, a device, computer equipment and a storage medium, wherein the conflict detection map construction method comprises the steps of obtaining a query statement data set and an operation data set, wherein the query statement data set comprises a plurality of statement samples corresponding to index names, the operation data set comprises a plurality of operation data tables of target individuals, searching the target tables associated with the index names in the operation data set according to the statement samples, determining hierarchy information corresponding to the index names based on the target tables, determining operation business associated with the index names based on the operation data set, setting conflict detection nodes corresponding to the index names one by one on an initial map according to the index names and the corresponding hierarchy information, setting data nodes and index name nodes representing the index names on the initial map, wherein the data nodes comprise hierarchy nodes corresponding to the hierarchy information, individual nodes corresponding to the target individuals and service nodes corresponding to the operation business, setting association paths among the index name nodes, the data nodes and the conflict detection nodes which are associated with each other to obtain a conflict detection map, and if different index names contained in a user input query can form connection through the conflict detection nodes, the data nodes and the association paths, and the first index names and the second index names are not in conflict with the first index names or the second index names are formed. According to the embodiment of the application, the conflict detection nodes are obtained by integrating the index names and the level information, and the conflict detection nodes are used for coupling multiple types of operation data into the same conflict detection spectrum, so that a conflict detection spectrum capable of reflecting the correlation relationship between different types of data in the operation data is constructed, so that when a user inputs a query statement, effective conflict analysis can be carried out on multiple words contained in the input query statement according to the conflict detection spectrum, clear and high-accuracy conflict analysis results are provided, and whether the multiple words contained in the search condition conflict or not, and particularly, whether the multiple words conflict are generated can be conveniently determined.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic flow chart of steps of a method for constructing a conflict detection pattern according to an embodiment of the present application;

Fig. 2 is a schematic flowchart of a step of determining hierarchical information in a method for constructing a conflict detection pattern according to an embodiment of the present application;

FIG. 3 is a schematic flowchart of another step of determining hierarchical information in a method for constructing a conflict detection pattern according to an embodiment of the present application;

fig. 4 is a schematic diagram of setting nodes on an initial map in a method for constructing a conflict detection map according to an embodiment of the present application;

Fig. 5 is a schematic diagram of setting nodes on an initial map in a method for constructing a conflict detection map according to an embodiment of the present application;

fig. 6 is a schematic diagram of setting nodes on an initial map in a method for constructing a collision detection map according to an embodiment of the present application;

Fig. 7 is a schematic block diagram of a device for constructing a collision detection spectrum according to an embodiment of the present application;

fig. 8 is a schematic block diagram of a computer device according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

The flow diagrams depicted in the figures are merely illustrative and not necessarily all of the elements and operations/steps are included or performed in the order described. For example, some operations/steps may be further divided, combined, or partially combined, so that the order of actual execution may be changed according to actual situations.

It is to be understood that the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should also be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.

The embodiment of the application provides a conflict detection spectrum construction method, a device, computer equipment and a storage medium, and based on the conflict detection spectrum construction method, a conflict detection spectrum which shows the interrelation relationship between different types of data in operation data can be generated. The conflict detection spectrum construction method can be applied to a management device of the operation analysis platform and is generated based on the conflict detection spectrum construction method, wherein the management device of the operation analysis platform can be a computer, an intelligent robot, an independent server or an electronic device such as a server cluster, and the like, and the method is not limited.

In this embodiment, the case where the method for constructing the collision detection spectrum is applied to an independent server is taken as an example for explanation, but the method is not limited to the case where the method for constructing the collision detection spectrum is only applied to an independent server.

Some embodiments of the present application will be described in detail below with reference to the attached drawings, and the following examples and features of the examples may be combined with each other without conflict.

Referring to fig. 1, fig. 1 is a schematic flowchart illustrating steps of a method for constructing a collision detection map according to an embodiment of the present application, where the method specifically includes the following steps S1 to S6.

Step S1, acquiring a query statement data set and an operation data set, wherein the query statement data set comprises a plurality of statement samples corresponding to index names, and the operation data set comprises a plurality of operation data tables of target individuals.

Specifically, the query statement dataset includes a plurality of statement samples, which are specifically samples obtained by extracting query statements input by a user to the business analysis platform. Specifically, the form of the business analysis platform comprises at least one of a platform website, an application program and a terminal equipment machine carrying the platform, the query sentence input by a user to the business analysis platform can be any number of query sentence segments, one query word or any number of combinations of query words, and the query sentence segments, one query word or any number of query words can be converted into index names corresponding to the query sentence segments, one query word or any number of query words.

The corresponding relation between the sentence sample and the index names is interpreted, namely the sentence sample and the index names form one-to-one correspondence, or one sentence sample corresponds to at least two index names, and correspondingly, at least two different sentence samples also correspond to the same index name.

For example, the query sentence segment is "what the business of company A in 2010 is" what the business of company B in quarter is "the corresponding index name is" business ", the query word" C organizes tax amount ", and the number of C organizes member" corresponds to two index names "tax amount" and "member number".

Specifically, the business data set is data in a database of a business analysis platform, and comprises a plurality of business data tables of target individuals, wherein the target individuals can be at least one of companies, organizations and individuals. And the business data forms of the target individuals include, but are not limited to, business activity form logs that are disclosed when the company, organization are the subject of the business activity, and data forms that record the participation of individuals in the business activity. And it should be noted that the target individual may correspond to a plurality of business data tables to comprehensively reflect the business activity situation of the target individual, and some business data tables may further include any number of sub-data tables.

And S2, searching a target table associated with the index name in the management data set according to the statement sample, and determining the level information corresponding to the index name based on the target table.

Specifically, firstly, determining an index name corresponding to a statement sample, then searching an operation data table associated with the index name in a plurality of operation data tables of an operation data set as a target table, and determining corresponding level information based on the position information of the index name in the target table.

In some embodiments, searching the target table associated with the index name in the business data set according to the statement sample in step S2 includes:

Specifically, the word segmentation processing on the sentence sample can be used for carrying out field decomposition on the inquiry sentence segment or the inquiry word with longer prefix, for example, the word segmentation processing is carried out on the ' business of the A company in 2010 ' to obtain candidate fields of the A company ' in 2010 ' and ' business of the 2010 ' and ' tax of the C organization ' to obtain candidate fields of the C organization ' and ' tax of the C organization '.

Exemplary word segmentation methods for sentence samples include, but are not limited to, by a third party word segmentation tool or word segmentation algorithm, etc. Common third party word segmentation tools include, but are not limited to, a Stanford NLP word segmentation device, ICTClAS word segmentation system, ansj word segmentation tool, hanLP Chinese word segmentation tool and the like. The word segmentation algorithm comprises, but is not limited to, a Maximum forward Matching (MM) algorithm, a reverse Maximum Matching (Reverse Direction Maximum Matching Method RMM) algorithm, a Bi-directional Maximum Matching (Bi-directional Matching method BM) algorithm, a hidden Markov model (Hidden Markov Model HMM) and an N-gram model.

After the candidate fields are obtained through processing, target fields corresponding to index names are screened from the candidate fields, a plurality of management data tables in the management data set are traversed, and management data tables containing the target fields are searched and used as target tables.

The index name and the target field corresponding to the index name are fields for representing the operation index, such as turnover, growth rate, personnel cost and the like. For example, the target field corresponding to the index name may be the same as the index name, or may be a synonym or a paraphrasing of the index name, i.e., in some embodiments, multiple different target fields with the same or similar meaning may correspond to the same index name.

The method comprises the steps of selecting target fields corresponding to index names from candidate fields, namely, carrying out semantic analysis on the candidate fields, extracting fields representing management indexes in the candidate fields as target fields, or screening out fields representing target individuals, time conditions and the like in the candidate fields, so as to keep the remaining fields as target fields.

In some embodiments, the index name and its synonyms and near-meaning words may be built into a dictionary tree in advance, then when the field representing the operation index in the candidate field is extracted as the target field, the candidate field is longest matched by using an AC (Aho-Corasick automaton) automaton algorithm, a prefix combination corresponding to the index name is found, for example (prefix 1, prefix 2, prefix 3..) and then the synonym affix and near-meaning affix corresponding to the index name are found out by each prefix combination, and the synonym affix and near-meaning affix are selected from the candidate field as the target field corresponding to the index name.

Referring to fig. 2, fig. 2 is a schematic flowchart illustrating a step of determining hierarchical information in a method for constructing a collision detection map according to an embodiment of the present application.

As shown in fig. 2, in some embodiments, determining the hierarchy information corresponding to the index name based on the target table in step S2 includes steps S21 to S23:

Step S21, determining whether a target table contains a secondary table;

step S22, if the secondary table is included, determining a target secondary table in which the index name is located in the secondary table;

step S23, generating level information according to the target secondary table and the target table.

Specifically, the partial business data table includes any number of sub-data tables, and the secondary table refers to the sub-data table of the target table. It should be understood that the target secondary table in which the index name is located includes each of the sub-data tables in which the target field corresponding to the index name is located.

For the case that the target table contains secondary tables, the device executing the method searches at least one secondary table for the target secondary table with the corresponding target field therein. And generating the level information according to the target secondary table and the target table.

In some embodiments, generating the hierarchy information in step S23 from the target secondary table and the target table includes:

It should be noted that, the first location information of the target table specifically indicates which target secondary table of the target tables the target name is in, and the first table type of the target table indicates the meaning and the purpose of the record data in the target table, such as a quarter income statistics table, a month expense statistics table, a year tax expense table of company a, and the like.

The second location information of the index name in the target secondary table specifically characterizes the relative location of the index name in the target secondary table, for example, whether the index name is specifically located in a project column or a data column of the table, or specifically located in a row number and/or a column number, and the second table type of the target secondary table characterizes the meaning and the purpose of the record data in the target table, for example, a quarter income statistics table, a month expenditure statistics table, a year tax expenditure table of company a, and the like.

For example, determining the first location information of the index name in the target table and generating the first level information according to the first location information and the first table type of the target table may be that the first location information of the index name in the target table is encoded into a first sub-string, the first table type of the target table is encoded into a second sub-string, and then the first sub-string and the second sub-string are combined to obtain the first string to represent the first level information. Similarly, determining the second position information of the index name in the target secondary table and generating the second-level information according to the second position information and the second table type of the target table may be that the second position information of the index name in the target secondary table is encoded into a third sub-string, the second table type of the target table is encoded into a fourth sub-string, and then the third sub-string and the fourth sub-string are combined to obtain a second string to represent the second-level information.

After that, the target character string obtained by combining the first character string and the second character string may be used as the hierarchical information.

Referring to fig. 3, fig. 3 is a schematic flowchart illustrating another step of determining hierarchical information in a method for constructing a collision detection map according to an embodiment of the present application.

As shown in fig. 3, in some embodiments, after determining whether the target table includes the secondary table in step S21, steps S24 to S25 are further included:

step S24, if the secondary table is not included, determining third position information of the index name according to the position of the index name in the target secondary table;

Step S25, determining a third table type of the target secondary table, and generating hierarchy information according to the third position information and the third table type.

Specifically, under the condition that the secondary table is not included, determining third position information of the index name according to the position of the index name in the target secondary table, determining a third table type of the target secondary table, and generating hierarchy information according to the third position information and the third table type.

The location information of the index name in the target secondary table specifically indicates the relative location of the index name in the target secondary table, for example, whether the index name is specifically located in a project column or a data column of the target secondary table, or specifically located in a row number and/or a column number, and the second table type of the target secondary table indicates the meaning and the purpose of the record data in the target table, for example, a quarter income statistics table, a month expenditure statistics table, a year tax expenditure table of company a, and the like.

And step S3, determining the business associated with the index name based on the business data set.

Based on the business data set including a plurality of business data tables of target individuals, all records of index names and/or target fields corresponding to the index names can be searched in the range of the business data tables, and then business associated with the index names is determined based on record positions corresponding to the records.

For example, when the secondary table is not included in the business data table where the target field corresponding to the index name and/or the index name is located, the record position includes which business data table the target field corresponding to the index name and/or the index name is located in, and the relative position in the business data table, for example, the relative position is located in the project column or the data column of the target table, or the number of rows and/or columns of the target table.

For example, when the secondary table is included in the business data table where the index name and/or the target field corresponding to the index name is located, the record location further includes which secondary table the index name and/or the target field corresponding to the index name is located in, and the relative position in the secondary table, for example, the relative position is located in the item column or the data column of the secondary table, or the number of rows and/or columns in which the index name and/or the target field corresponding to the index name is located.

Specifically, after determining the target field corresponding to the index name, the business dimension is drilled down based on the business data, and at least one business associated with the index name and at least one business associated with the target field corresponding to the index name are listed. For example, when the index name is a planning index, the business dimension of the index name can be divided into a personal business and a group business (including an organization and a company), and the business dimension of the personal business and the group business can be further subdivided into a new business and a renewal business.

And S4, setting conflict detection nodes corresponding to the index names one by one on the initial map according to the index names and the corresponding level information.

In some embodiments, the initial atlas may be atlas-building by specifying an atlas database on the website or in a local device performing the method. In still other embodiments, the initial atlas may also be constructed using a centralized or distributed atlas database.

When the distributed graph database is adopted for construction, the setting of the conflict detection nodes is described by taking NebulaGraph graph database implementation as an example, wherein a command is added in a yam l configuration file, node entities in a graph space are respectively created by using CREATE TAG, and the node entities at least comprise the conflict detection nodes, and further comprise index name nodes for representing index names, hierarchy nodes corresponding to hierarchy information, individual nodes corresponding to target individuals and service nodes corresponding to operation services.

Referring to fig. 5, fig. 5 is a schematic diagram illustrating setting of nodes on an initial map in a method for constructing a collision detection map according to an embodiment of the present application.

As shown in fig. 5, at least one conflict detection node is set on the constructed initial map based on the map database, wherein the conflict detection nodes are in one-to-one correspondence with the index names, and each conflict detection node stores the index names and the level information corresponding to the conflict detection nodes in an associated manner.

For example, the conflict detection node may be set in such a manner that data of the index name and the hierarchy information are stored in { name, label }, and the data are associated and hung to the corresponding conflict detection node, where name is a target field corresponding to the index name, label is the hierarchy information, and specifically, a character string obtained by encoding and combining according to a table type and position information in the target table/the target secondary table, and a specific generation manner of the character string specifically refers to the description in the foregoing step S2.

For example, in the map shown in fig. 5, three collision detection nodes are included { turnover, position code 1×form type 1}, { human cost, position code 2×form type 2}, { field cost, position code 3×form type 3}.

And S5, setting data nodes and index name nodes representing index names on the initial map, wherein the data nodes comprise hierarchy nodes corresponding to the hierarchy information, individual nodes corresponding to target individuals and service nodes corresponding to business services.

Specifically, the data nodes include hierarchical nodes corresponding to hierarchical information, individual nodes corresponding to target individuals, and service nodes corresponding to business services. Setting data nodes and index name nodes is described by taking NebulaGraph diagram database implementation as an example, wherein commands are added in yam l configuration files, and node entities in the diagram space are respectively created by using 'CREATE TAG', wherein the node entities comprise index name nodes, hierarchy nodes, individual nodes and service nodes.

Referring to fig. 6, fig. 6 is a schematic diagram illustrating setting of nodes on an initial map in a method for constructing a collision detection map according to an embodiment of the present application.

As shown in fig. 6, specifically, for the case that the target table includes the secondary table, the apparatus for executing the method generates, on the initial map, a corresponding first node identifier based on each primary level information, generates a corresponding second node identifier based on each secondary level information, assigns a first character string obtained by converting the primary level information to the first node identifier, and assigns a second character string obtained by converting the secondary level information to the second node identifier.

After this, a hierarchical path will be set between the respective first node identity and second node identity based on the target secondary table and the target table.

It should be noted that, the setting sequence of the conflict detection node, the data node and the index name node on the initial map may be set according to the actual requirement.

S6, setting association paths among the index name nodes, the data nodes and the conflict detection nodes which are associated with each other to obtain a conflict detection map;

As shown in fig. 6, in some embodiments, setting an association path between the index name node, the data node, and the collision detection node, which are associated with each other, in step S6, obtains a collision detection map, including:

Specifically, based on the correspondence between the index name node and the individual, the correspondence between the index name node and the service node, the correspondence between the collision detection node and the index name node, and the correspondence between the collision detection node and the hierarchy node, an association path may be set between the nodes associated with each other, that is, it is characterized that no collision is formed between the nodes connected and conducted through the association path.

Setting up the associated path is described by taking NebulaGraph graph database implementation as an example, namely adding a command in the yaml configuration file, and creating a relationship between each node entity in the graph space by using 'CREATE EDGE', thereby completing the construction of the graph space.

The method comprises the following steps of supplementing the explanation, based on the conflict detection spectrum constructed by the conflict detection spectrum construction method, comparing the query sentence input by the user with the conflict detection spectrum to obtain whether a plurality of words contained in the input query sentence are in conflict or not, if different index names can form connection through the conflict detection nodes, the data nodes and the association paths, the first index name and the second index name do not form conflict, otherwise, the first index name and the second index name are in conflict with each other.

For example, the conflict detection map shown in fig. 6 includes { index name node: business amount }, { index name node: personnel cost }, { individual node: company a }, { individual node: organization }, { hierarchical node: position code 1 x 1 of form type }, { hierarchical node: position code 2 x 2 of form type }, { business node: group business }, and { business node: personal business }, and further includes conflict detection node { business amount, position code 1 x 1 of form type }, and { personnel cost, position code 2 x 2 of form type }.

When the user inputs the query sentence comprising the following two words (or elements) of business and form type 2, the comparison of the conflict detection map can obtain { index name node: business and form connection with { hierarchy node: position code 2 x form type 2} can not be formed through the conflict detection node, data node and association path, and the business and form no direct association with form 2 can be judged based on the data in the database of the business analysis platform, so that the two words (or elements) input by the user can be in conflict, and the two words which are in conflict with each other can be further fed back to the user to generate the input query sentence.

In summary, the method obtains the conflict detection node by integrating the index name and the hierarchy information, and couples the multiple types of business data to the same conflict detection spectrum by means of the conflict detection node to construct a conflict detection spectrum capable of reflecting the correlation relationship between the different types of data in the business data, so that when a user inputs a query statement, effective conflict analysis can be performed on multiple words contained in the input query statement according to the conflict detection spectrum, clear and high-accuracy conflict analysis results are provided, and whether conflicts occur among the multiple words contained in the search condition, and particularly, whether conflicts occur among the words are determined.

Referring to fig. 7, fig. 7 is a schematic block diagram of a collision detection map construction apparatus according to an embodiment of the present application.

As shown in fig. 7, the collision detection map construction apparatus 700 includes:

The data acquisition module 701 is configured to acquire a query statement data set and an operation data set, where the query statement data set includes a plurality of statement samples corresponding to index names, and the operation data set includes operation data tables of a plurality of target individuals;

the hierarchy analysis module 702 is configured to search a target table associated with the index name in the management data set according to the statement sample, and determine hierarchy information corresponding to the index name based on the target table;

a business analysis module 703, configured to determine a business associated with the index name based on the business data set;

a first node module 704, configured to set conflict detection nodes corresponding to the index names on the initial map according to the index names and the corresponding level information;

the second node module 705 is configured to set a data node and an index name node for representing an index name on the initial map, where the data node includes a hierarchical node corresponding to the hierarchical information, an individual node corresponding to the target individual, and a service node corresponding to the business;

A path generating module 706, configured to set an association path between the index name node, the data node, and the collision detection node that are associated with each other to obtain a collision detection map;

In some implementations, the hierarchical analysis module 702 searches the business data set for a target table associated with the index name according to the statement sample, specifically including:

In some embodiments, the hierarchy analysis module 702 determines the hierarchy information corresponding to the index name based on the target table, specifically including:

determining whether the target table contains a secondary table;

In some embodiments, the hierarchy analysis module 702 generates hierarchy information from the target secondary table and the target table, specifically including:

In some embodiments, after the hierarchical analysis module 702 determines whether the target table includes the secondary table, the method further specifically includes:

In some embodiments, the hierarchy nodes include a primary node corresponding to primary hierarchy information and a secondary node corresponding to secondary hierarchy information, and the second node module 705 sets data nodes on the initial graph, including:

In some embodiments, the path generation module 706 sets an association path between the index name node, the data node, and the collision detection node that are associated with each other to obtain a collision detection map, including:

setting an association path between the index name node and an individual node corresponding to the index name node;

setting an association path between the index name node and a service node corresponding to the index name node;

setting an association path between the conflict detection node and the corresponding index name node;

Referring to fig. 8, fig. 8 is a schematic block diagram of a computer device according to an embodiment of the present application.

As shown in FIG. 8, computer device 800 includes a processor 801 and a memory 802. The processor 801 and the memory 802 are connected by a bus 803, such as an I2C (Inter-INTEGRATED CIRCUIT) bus.

In particular, the processor 801 is operative to provide computing and control capabilities to support the operation of the overall computer device. The Processor 801 may be a central processing unit (Central Processing Unit, CPU), the Processor 801 may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

Specifically, the Memory 802 may be a Flash chip, a Read-Only Memory (ROM) disk, an optical disk, a U-disk, a removable hard disk, or the like.

It will be appreciated by those skilled in the art that the structure shown in fig. 8 is merely a block diagram of a portion of the structure associated with an embodiment of the present application, and is not intended to limit the application of an embodiment of the present application to a computer device, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or may have a different arrangement of components.

The processor is configured to run a computer program stored in the memory, and implement any one of the conflict detection pattern construction methods provided by the embodiments of the present application when the computer program is executed.

In an embodiment, the processor 801 is configured to run a computer program stored in the memory 802 and when executed implement the following steps:

In some implementations, the processor 801, when looking up a target table associated with an index name in the business data set from a statement sample, includes:

In some embodiments, the processor 801, when determining the hierarchy information corresponding to the index name based on the target table, includes:

determining whether the target table contains a secondary table;

In some implementations, the processor 801, when generating hierarchical information from the target secondary table and the target table, includes:

In some implementations, after determining whether the secondary table is included in the target table, the processor 801 further includes:

In some implementations, the hierarchy nodes include primary nodes corresponding to primary hierarchy information and secondary nodes corresponding to secondary hierarchy information, and the processor 801, when setting the data nodes on the initial graph, includes:

In some embodiments, when setting an association path between the index name node, the data node, and the collision detection node, the processor 801 obtains a collision detection map, including:

It should be noted that, for convenience and brevity of description, specific working processes of the above-described computer device may refer to corresponding processes in the foregoing embodiments of the animal identifying method, which are not described herein again.

Embodiments of the present application also provide a storage medium storing a computer program executable by one or more processors to implement the steps of any of the collision detection map construction methods as provided in the embodiments of the present application.

The storage medium may be an internal storage unit of the computer device according to the foregoing embodiment, for example, a hard disk or a memory of the computer device. The storage medium may also be an external storage device of the computer device, such as a plug-in hard disk provided on the computer device, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD), or the like.

Those of ordinary skill in the art will appreciate that all or some of the steps, systems, functional modules/units in the apparatus, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware embodiment, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components, for example, one physical component may have a plurality of functions, or one function or step may be cooperatively performed by several physical components. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.

It should be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.

The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments. While the application has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions may be made therein without departing from the spirit and scope of the application as defined by the appended claims. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims

1. A collision detection map construction method, characterized in that the method comprises:

Setting conflict detection nodes corresponding to the index names one by one on an initial map according to the index names and the corresponding level information;

setting data nodes and index name nodes representing the index names on the initial map, wherein the data nodes comprise hierarchy nodes corresponding to the hierarchy information, individual nodes corresponding to the target individuals and service nodes corresponding to the business;

And if different index names contained in the query statement input by the user can form connection through the conflict detection node, the data node and the association path, the first index name and the second index name do not form conflict, and otherwise, the first index name and the second index name mutually conflict.

2. The method of claim 1, wherein the looking up a target table associated with the index name in the business data set from the sentence sample comprises:

performing word segmentation processing on the sentence sample to obtain at least one candidate field;

Screening target fields corresponding to index names from the candidate fields;

And traversing the management data set to search the management data table containing the target field as the target table.

3. The method of claim 1, wherein the determining the hierarchy information corresponding to the index name based on the target table comprises:

Determining whether the target table contains a secondary table;

And generating the hierarchy information according to the target secondary table and the target table.

4. The method of claim 3, wherein the generating the hierarchy information from the target secondary table and the target table comprises:

Determining first position information of the index name in the target table, and generating first-level information according to the first position information and a first table type of the target table;

Determining second position information of the index name in the target secondary table, and generating secondary level information according to the second position information and a second table type of the target table;

and generating the hierarchy information according to the primary hierarchy information and the secondary hierarchy information.

5. The method of claim 3, wherein after determining whether the target table contains a secondary table, further comprising:

And determining a third table type of the target secondary table, and generating the hierarchy information according to the third position information and the third table type.

6. The method of claim 4, wherein the hierarchy nodes include primary nodes corresponding to the primary hierarchy information and secondary nodes corresponding to the secondary hierarchy information, the setting data nodes on the initial graph comprising:

Generating a corresponding second node identifier based on each second-level information, and endowing the second node identifier with a second character string obtained by converting the second-level information;

setting the first node identifier and the second node identifier after character string assignment on the initial map, and setting a hierarchical path between the corresponding first node identifier and second node identifier based on the target secondary table and the target table.

7. The method according to any one of claims 1-6, wherein said setting an association path between the index name node, the data node, and the collision detection node, which are associated with each other, to obtain a collision detection map, includes:

Setting the association path between the index name node and the individual node corresponding to the index name node, and,

Setting the association path between the index name node and the service node corresponding to the index name node, and,

Setting the association path between the collision detection node and the corresponding index name node, and,

And setting the association path between the conflict detection node and the corresponding hierarchical node.

8. A collision detection map construction apparatus, comprising:

The data acquisition module is used for acquiring a query statement data set and an operation data set, wherein the query statement data set comprises a plurality of statement samples corresponding to index names, and the operation data set comprises operation data tables of each target individual in a plurality of target individuals;

The hierarchy analysis module is used for searching a target table associated with the index name in the management data set according to the statement sample, and determining hierarchy information corresponding to the index name based on the target table;

The first node module is used for setting conflict detection nodes corresponding to the index names one by one on an initial map according to the index names and the corresponding level information;

The second node module is used for setting data nodes and index name nodes representing the index names on the initial map, wherein the data nodes comprise hierarchical nodes corresponding to the hierarchical information, individual nodes corresponding to the target individuals and service nodes corresponding to the operation service;

The path generation module is used for setting a correlation path among the index name node, the data node and the conflict detection node which are correlated to each other to obtain a conflict detection map;

9. A computer device, the computer device comprising a memory and a processor;

The memory is used for storing a computer program;

the processor is configured to execute the computer program and implement the collision detection map construction method according to any one of claims 1 to 7 when the computer program is executed.

10. A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program which, when executed by a processor, causes the processor to implement the collision detection map construction method according to any one of claims 1 to 7.