Conversational type-based model selection system construction method and device, equipment and medium

Abstract

The embodiment of the invention provides a dialogue-based model selection system construction method and device, equipment and a medium, and relates to the technical field of data management.The method comprises the steps that by means of the dialogue-based model selection system construction method, a user can input parameters in a dialogue mode, and in the input process, the user can input the parameters in the dialogue mode; the system can check the input parameters through the dialogue information between the system and the user, so that on one hand, the user does not need to master complex database operation, the establishment process of the part type selection system is greatly simplified, the type selection system construction efficiency is improved, on the other hand, the type selection system is constructed by the system, and the construction efficiency is improved. The operation accuracy can be improved.

Description

Technical Field

[0001] The present invention relates to the field of data management technology, and in particular to a method for constructing a selection system based on a dialogue, a device for constructing a selection system based on a dialogue, an electronic device, and a computer-readable storage medium. Background Art

[0002] Selection systems are tools or processes used to help users choose the most appropriate solution from multiple options. They can be widely used in various fields, including product selection, supplier selection, and solution evaluation for industrial components. In the product selection of industrial components, industrial component selection systems can effectively help engineers, purchasers, and designers select solutions suitable for their application scenarios from a wide range of industrial components. However, the establishment and maintenance of industrial component selection systems typically rely on manual data entry and form filling. When complex components are involved, multiple parameters need to be defined and configured, which is not only prone to data entry errors but also inefficient and difficult to adapt to frequent updates. Summary of the Invention

[0003] An embodiment of the present invention provides a method, device, electronic device and computer-readable storage medium for constructing a selection system based on a dialogue mode to solve or partially solve the problems that the construction process of the industrial parts selection system is prone to errors, inefficiency and difficulty in adapting to frequent update requirements.

[0004] An embodiment of the present invention discloses a method for constructing a selection system based on a dialogue mode, which is applied to a parameter entry system. The parameter entry system includes at least a natural language processing unit, a database, a selection system management unit, and a feedback unit. The method includes:

[0005] Step 1: In response to detecting a component processing instruction input by a user, the natural language processing unit recognizes the component processing instruction, and the feedback unit outputs part attribute prompt information corresponding to the component processing instruction, wherein the part attribute prompt information is used to prompt the user to input corresponding part attribute content;

[0006] Step 2: In response to first input information input by the user asking about the component attribute information, extracting a first part attribute from the first input information by the natural language processing unit;

[0007] Step 3: If the first part attribute only includes a part name, outputting parameter supplementary prompt information for the part name through the feedback unit, wherein the parameter supplementary prompt information is used to prompt the user to input the corresponding part attribute;

[0008] Step 4: In response to second input information input by the user for the parameter supplement prompt information, extracting, by the natural language processing unit, a second part attribute corresponding to the part name and a first part attribute value corresponding to the second part attribute from the second input information;

[0009] Step 5: Perform a necessity check on the second part attribute and the first part attribute value through the database. If the check is successful, construct a selection system based on the second part attribute and the first part attribute value through the selection management unit to obtain the selection system corresponding to the part name.

[0010] In some feasible implementations, performing a necessity check on the second part attribute and the first part attribute value through the database, and if the check succeeds, constructing a selection system based on the second part attribute and the first part attribute value through the selection management unit to obtain a selection system corresponding to the part name includes:

[0011] extracting a target unit corresponding to the second part attribute;

[0012] Extracting unit mapping information and a standard value series list corresponding to the part name from the database, wherein the unit mapping information includes a mapping relationship between part parameters and units;

[0013] If a mapping relationship between the second part attribute and the target unit exists in the unit mapping information, confirming that the units between the second part attribute and the target unit are accurate;

[0014] If the first part attribute value exists in the standard value list, confirming that the attribute of the first part attribute value is reasonable;

[0015] When the units between the second part attribute and the target unit are accurate and the first part attribute value exists in the standard value series table, the selection management unit constructs a selection system based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name.

[0016] In some feasible implementations, when the second part attribute and the target unit are accurate and the first part attribute value exists in the standard value series table, constructing a selection system according to the second part attribute and the first part attribute value by the selection management unit to obtain the selection system corresponding to the part name includes:

[0017] Obtain necessary part attributes corresponding to the part name;

[0018] When the units of the second part attribute and the target unit are accurate, the value of the first part attribute exists in the standard value series table, and the second part attribute is exactly the same as the required part attribute, the selection management unit constructs a selection system based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name.

[0019] Some possible implementations also include:

[0020] If there is no mapping relationship between the second part attribute and the target unit in the unit mapping information, parameter correction prompt information for the second part attribute and / or the target unit is output through the feedback unit, and the parameter correction prompt information is used to prompt the user to perform parameter correction on the second part attribute and / or the target unit.

[0021] Some possible implementations also include:

[0022] If the first part attribute value does not exist in the standard value series table, value correction prompt information for the first part attribute value is output through the feedback unit, and the value correction prompt information is used to prompt the user to correct the parameter value of the first part attribute value.

[0023] Some possible implementations also include:

[0024] Step 7: In response to the parameter adjustment instruction input by the user, the natural language processing unit recognizes the parameter adjustment instruction, and the feedback unit outputs product confirmation information for the parameter adjustment instruction, wherein the product confirmation information is used to prompt the user to input the part attributes that need to be updated;

[0025] Step 8: In response to the product confirmation information input by the user, extracting at least one of a corresponding third part attribute and a second part attribute value from the third input information by the natural language processing unit;

[0026] Step 9: Execute parameter adjustment operations corresponding to the third part attribute and / or the second part attribute value.

[0027] In some feasible implementations, the database includes a parameter dictionary library, the second part attribute includes a part type, and constructing a selection system based on the second part attribute and the first part attribute value to obtain a selection system corresponding to the part name includes:

[0028] Mapping the second part attribute to a corresponding standard term through the parameter dictionary library;

[0029] Unifying the units of the first part attribute values ​​and simultaneously parsing the value range, constructing standardized parameter key-value pairs corresponding to the first part attribute values, and using the standard term and the standardized parameter key-value pairs as corresponding standardized parameters;

[0030] Loading a selection rule library corresponding to the part type, and extracting a selection rule set matching the standardized parameters from the selection rule library;

[0031] Establishing a mapping relationship table between the standardized parameters and the selection rule set;

[0032] The mapping relationship table is used to construct a selection system corresponding to the part name.

[0033] The embodiment of the present invention further discloses a dialog-based selection system construction device, which is applied to a parameter entry system. The parameter entry system includes at least a natural language processing unit, a database, a selection system management unit, and a feedback unit. The device includes:

[0034] a first instruction recognition module, configured to, in response to detecting a component processing instruction input by a user, recognize the component processing instruction through the natural language processing unit, and output part attribute prompt information corresponding to the component processing instruction through the feedback unit, wherein the part attribute prompt information is used to prompt the user to input corresponding part attribute content;

[0035] an information extraction module, configured to extract a first part attribute from the first input information input by the user inquiring about the part attribute information through the natural language processing unit;

[0036] a prompt output module, configured to output parameter supplementary prompt information for the part name through the feedback unit if the first part attribute only includes the part name, wherein the parameter supplementary prompt information is used to prompt the user to input the corresponding part attribute;

[0037] an attribute extraction module, configured to extract, in response to second input information input by the user for the parameter supplementary prompt information, a second part attribute corresponding to the part name and a first part attribute value corresponding to the second part attribute from the second input information through the natural language processing unit;

[0038] A system construction module is used to perform a necessity check on the second part attribute and the first part attribute value through the database. If the second part attribute and the first part attribute value are successfully checked, a selection system is constructed according to the second part attribute and the first part attribute value through the selection management unit to obtain a selection system corresponding to the part name.

[0039] In some feasible implementations, the system building module is specifically used to:

[0040] extracting a target unit corresponding to the second part attribute;

[0041] Extracting unit mapping information and a standard value series list corresponding to the part name from the database, wherein the unit mapping information includes a mapping relationship between part parameters and units;

[0042] If a mapping relationship between the second part attribute and the target unit exists in the unit mapping information, confirming that the units between the second part attribute and the target unit are accurate;

[0043] If the first part attribute value exists in the standard value list, confirming that the attribute of the first part attribute value is reasonable;

[0044] When the units between the second part attribute and the target unit are accurate and the first part attribute value exists in the standard value series table, the selection management unit constructs a selection system based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name.

[0045] In some feasible implementations, the system building module is specifically used to:

[0046] Obtain necessary part attributes corresponding to the part name;

[0047] When the units of the second part attribute and the target unit are accurate, the value of the first part attribute exists in the standard value series table, and the second part attribute is exactly the same as the required part attribute, the selection management unit constructs a selection system based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name.

[0048] Some possible implementations also include:

[0049] A parameter correction prompt module is used to output parameter correction prompt information for the second part attribute and / or the target unit through the feedback unit if there is no mapping relationship between the second part attribute and the target unit in the unit mapping information. The parameter correction prompt information is used to prompt the user to perform parameter correction on the second part attribute and / or the target unit.

[0050] Some possible implementations also include:

[0051] The attribute value correction prompt module is used to output value correction prompt information for the first part attribute value through the feedback unit if the first part attribute value does not exist in the standard value series list, and the value correction prompt information is used to prompt the user to correct the parameter value of the first part attribute value.

[0052] Some possible implementations also include:

[0053] a second instruction recognition module, configured to respond to a parameter adjustment instruction input by the user, recognize the parameter adjustment instruction through the natural language processing unit, and output product confirmation information for the parameter adjustment instruction through the feedback unit, wherein the product confirmation information is used to prompt the user to input part attributes that need to be updated;

[0054] a confirmation module, configured to extract at least one of a third part attribute and a second part attribute value corresponding to the third input information through the natural language processing unit in response to the confirmation information input by the user for the product;

[0055] An adjustment module is used to perform parameter adjustment operations corresponding to the third part attribute and / or the second part attribute value.

[0056] In some feasible implementations, the database includes a parameter dictionary library, the second part attribute includes a part type, and the system construction module is specifically configured to:

[0057] Mapping the second part attribute to a corresponding standard term through the parameter dictionary library;

[0058] Unifying the units of the first part attribute values ​​and simultaneously parsing the value range, constructing standardized parameter key-value pairs corresponding to the first part attribute values, and using the standard term and the standardized parameter key-value pairs as corresponding standardized parameters;

[0059] Loading a selection rule library corresponding to the part type, and extracting a selection rule set matching the standardized parameters from the selection rule library;

[0060] Establishing a mapping relationship table between the standardized parameters and the selection rule set;

[0061] The mapping relationship table is used to construct a selection system corresponding to the part name.

[0062] An embodiment of the present invention further discloses an electronic device, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0063] The memory is used to store computer programs;

[0064] The processor is configured to implement the method described in the embodiment of the present invention when executing the program stored in the memory.

[0065] An embodiment of the present invention further discloses a computer-readable storage medium having instructions stored thereon. When executed by one or more processors, the processors are enabled to execute the method according to the embodiment of the present invention.

[0066] The embodiments of the present invention include the following advantages:

[0067] In an embodiment of the present invention, in the process of the user constructing a selection system for the corresponding parts, a parameter entry system can be constructed first. The parameter entry system at least includes a natural language processing unit, a database, a selection system management unit and a feedback unit. The construction of the selection system can be quickly realized through the parameter entry system. In response to detecting the part processing instruction input by the user, the natural language processing unit identifies the part processing instruction, and the feedback unit outputs part attribute prompt information for the part processing instruction. The part attribute prompt information is used to prompt the user to input the corresponding part attribute content. Then, in response to the first input information input by the user for questioning information about the part attribute, the natural language processing unit extracts the first part attribute from the first input information. If the first part attribute only contains the part name, the feedback unit outputs parameter supplement prompt information for the part name. The parameter supplement prompt information is used to prompt the user to input the corresponding part attribute, and then the system can respond. In response to the second input information input by the user for the parameter supplement prompt information, the natural language processing unit extracts the second part attribute corresponding to the part name and the first part attribute value corresponding to the second part attribute from the second input information, and performs a necessity check on the second part attribute and the first part attribute value through the database. If the second part attribute and the first part attribute value are successfully checked, the selection management unit constructs a selection system according to the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name, so that the user can enter the parameters through dialogue through the conversational selection system construction method. During the entry process, the system can verify the entered parameters through the conversation information between the user and the user. On the one hand, the user does not need to master complex database operations, which greatly simplifies the establishment process of the part selection system and improves the efficiency of the selection system construction. On the other hand, the construction of the selection system by the system can improve the accuracy of the operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 This is a flowchart of the steps of a method for constructing a selection system based on a dialogue mode provided in an embodiment of the present invention;

[0069] Figure 2 This is a structural block diagram of a dialog-based selection system construction device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0071] As an example, the establishment and maintenance of industrial parts selection systems usually rely on manual entry and form filling. When complex parts are involved, multiple parameters need to be defined and configured, which is not only prone to entry errors but also inefficient and difficult to adapt to frequent update needs.

[0072] In this regard, in the present invention, in the process of the user constructing a selection system for the corresponding parts, a parameter entry system can be first constructed, and the construction process of the selection system can be simplified through the parameter entry system, wherein the parameter entry system at least includes a natural language processing unit, a database, a selection system management unit and a feedback unit. The construction of the selection system can be quickly realized through the parameter entry system. In response to detecting the part processing instruction input by the user, the part processing instruction is identified by the natural language processing unit, and the part attribute prompt information for the part processing instruction is output through the feedback unit. The part attribute prompt information is used to prompt the user to input the corresponding part attribute content. Then, in response to the first input information input by the user for the question information about the part attribute, the first part attribute is extracted from the first input information through the natural language processing unit. If the first part attribute only contains the part name, the parameter supplement prompt information for the part name is output through the feedback unit. The parameter supplement prompt information is used to prompt the user to input the correct part attribute. The corresponding part attributes can then respond to the second input information input by the user for the parameter supplement prompt information, and the natural language processing unit can extract the second part attribute corresponding to the part name and the first part attribute value corresponding to the second part attribute from the second input information, and perform a necessity check on the second part attribute and the first part attribute value through the database. If the second part attribute and the first part attribute value are successfully checked, the selection management unit constructs a selection system according to the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name, so that the user can enter the parameters through dialogue through the dialogue method. During the entry process, the system can verify the entered parameters through the dialogue information between the user, and then on the one hand, the user does not need to master complex database operations, which greatly simplifies the establishment process of the part selection system and improves the efficiency of the selection system construction. On the other hand, the construction of the selection system by the system can improve the accuracy of the operation.

[0073] Reference Figure 1 , shows a flowchart of the steps of a method for constructing a selection system based on a dialogue mode provided in an embodiment of the present invention, which is applied to a parameter entry system. The parameter entry system includes at least a natural language processing unit, a database, a selection system management unit, and a feedback unit. Specifically, the following steps may be included:

[0074] Step 1: In response to detecting a component processing instruction input by a user, the natural language processing unit recognizes the component processing instruction, and the feedback unit outputs part attribute prompt information corresponding to the component processing instruction, wherein the part attribute prompt information is used to prompt the user to input corresponding part attribute content;

[0075] Step 2: In response to first input information input by the user asking about the component attribute information, extracting a first part attribute from the first input information by the natural language processing unit;

[0076] Step 3: If the first part attribute only includes a part name, outputting parameter supplementary prompt information for the part name through the feedback unit, wherein the parameter supplementary prompt information is used to prompt the user to input the corresponding part attribute;

[0077] Step 4: In response to second input information input by the user for the parameter supplement prompt information, extracting, by the natural language processing unit, a second part attribute corresponding to the part name and a first part attribute value corresponding to the second part attribute from the second input information;

[0078] Step 5: Perform a necessity check on the second part attribute and the first part attribute value through the database. If the check is successful, construct a selection system based on the second part attribute and the first part attribute value through the selection management unit to obtain the selection system corresponding to the part name.

[0079] The parameter entry system (hereinafter referred to as the system) is a software system that assists users in entering part-related parameters and subsequently constructing a selection system. It primarily consists of several core components: a natural language processing unit, a database, a selection system management unit, and a feedback unit. Through the collaboration of these components, it can complete a series of operations from receiving user instructions to ultimately constructing the selection system.

[0080] Among them, the natural language processing unit can have the ability to recognize, analyze and extract the natural language instructions and information input by the user, and can understand the component processing instructions input by the user and the subsequent input component attribute content and parameter information, and accurately extract the required key information, such as part name, part parameters and parameter values.

[0081] The database is primarily used to store relevant information about various parts and components, as well as necessary inspection rules. During system operation, it performs the crucial task of verifying the user-entered part parameters and values, determining whether the input information complies with system requirements and business rules.

[0082] For the selection system management unit, when the part parameters and parameter values ​​entered by the user pass the database verification, the unit can build the selection system based on these valid parameter information, and finally generate a selection system corresponding to the specific part name.

[0083] The feedback unit is primarily responsible for interacting with the user, outputting prompts based on the system's processing status to the user, guiding the user through the process of entering part attributes and parameters. Optionally, the prompts include at least part attribute prompts for component processing instructions and supplementary parameter prompts for the part name, though this is not a limitation of the present invention.

[0084] In one example, for the parameter entry system, the functions of the modules included therein are as follows:

[0085] Dialogue unit: A multi-round dialogue system that supports natural language and imperative input. Users can interact with the system through text, voice, and other means.

[0086] Natural language processing unit: used to parse text or voice input by the user, understand semantics and extract key information such as component names, attributes, specifications, etc.

[0087] Dialogue management unit: responsible for maintaining the dialogue status, managing the multi-round dialogue process, and ensuring that user input is effectively fed back and processed.

[0088] Knowledge base and rules engine: Contains standard properties and specifications of components for verification and guidance during the conversation process.

[0089] Selection system management unit: automatically establishes or updates the parts database based on user dialogue input, and supports structured storage and association of data.

[0090] Feedback unit: Provides real-time feedback based on user input to help users correct input errors or supplement missing information to ensure the integrity of the selection system.

[0091] In addition, the dialogue design between the user and the system can be as follows:

[0092] 1. Dialogue initiation: Users can initiate a dialogue through voice assistants, text chat boxes, etc., and send a request to the system to create or update the selection system.

[0093] 2. Information collection: The system asks users for basic information about parts through dialogue, such as part name, type, specifications, materials, etc. Users can provide information through short answers or detailed descriptions.

[0094] 3. Information Parsing and Confirmation: The system uses NLP technology to parse user input, identify key information, and format and store it according to predefined rules. If the input is incomplete or ambiguous, the system will further prompt the user to supplement or confirm the information.

[0095] 4. Multi-round dialogue guidance: The system guides the user to gradually enter more details of the parts, such as dimensions, functions, scope of application, etc., until all necessary data are entered.

[0096] 5. Data verification and feedback: The system verifies the information entered by the user, such as unit conversion, attribute rationality check, etc. If there are errors or unreasonable places, the system will prompt the user to make corrections.

[0097] 6. Selection system update: After the user confirms that all information is correct, the system will automatically update the selection system, create or modify the corresponding component entries, and generate the data structure.

[0098] During the construction of the selection system, when the system detects a user-entered component processing instruction, the natural language processing unit identifies the instruction and, based on the identification result, outputs a part attribute prompt through the feedback unit, guiding the user to enter the corresponding part attribute content and helping the user clarify the information required for the next step. Next, when the user enters the first input information in response to the part attribute prompt information, the natural language processing unit analyzes it and extracts the first part attribute from it. If the extracted first part attribute only contains the part name, the feedback unit outputs a parameter supplement prompt, prompting the user to enter the specific parameters corresponding to the part. The user then enters the second input information in response to the parameter supplement prompt information, and the natural language processing unit again functions to extract the second part attribute corresponding to the part name and the first part attribute values ​​corresponding to these parameters from this input information. The second part attribute and the first part attribute values ​​can then be subjected to necessity checks (such as completeness checks, unit accuracy checks, and attribute rationality checks) based on database verification rules to check whether they comply with the system's pre-set rules and requirements. If the inspection is successful, the selection system management unit will construct the selection system based on these valid parameter information, and finally obtain the selection system corresponding to the part name to provide support for subsequent parts selection work.

[0099] Among them, for component processing instructions, it can be information input by the user in the system in a corresponding manner. Specifically, the user can input corresponding text information or voice information in the system. Based on the information input by the user, the system recognizes the user's intention, so that the system recognizes the content input by the user through the natural language processing unit, and outputs corresponding prompt information through the feedback unit based on the recognition result. For example, the user can input "I want to enter a new gear model and set its optional parameter range" in the system through text or voice, and then the system can recognize through the natural language processing unit that the user's intention is to "create a gear selection system", and then the system can output corresponding prompt information through the feedback unit, such as "OK, please tell me the name or model of the gear".

[0100] In the process of users entering part attributes through dialogue to build a selection system, part parameters can be part attributes corresponding to parts, and part parameter values ​​can be values ​​or value ranges of part parameters, etc. For example, part parameters can include part name, part model, module, tooth number range, material, etc., and part parameter values ​​can be "gear xxx", "G34 (part model)", "2.0 (module)", "optional range 16-24", etc. During the dialogue process, the system can guide the user to enter corresponding part attributes through at least one round of dialogue based on the information input by the user, so as to build a corresponding selection system based on the part attributes input by the user. The present invention does not limit this.

[0101] In one example, assuming that after a user triggers the construction of a selection system, the system, through a natural language processing unit, extracts a first part attribute containing only the part name from the first input information initially entered by the user. The system can then output corresponding parameter supplementary prompt information to prompt the user to enter the corresponding part attribute. Subsequently, based on the parameter supplementary prompt information output by the system, the user can choose to enter multiple part attributes at once, or enter different part attributes separately through multiple rounds of dialogue. Regardless of the method used, the system can extract the corresponding part attributes and / or part attribute values ​​from the information entered by the user, so as to further verify the part attributes and part attribute values ​​entered by the user to determine whether the conditions for constructing a selection system are met. If the conditions are met, the corresponding selection system can then be constructed.

[0102] For example, the dialogue content of building a selection system through dialogue can be as follows:

[0103] 1. Start a conversation

[0104] User: I want to enter a new gear model and set its optional parameter range.

[0105] System: OK, please tell me the name or model of the gear.

[0106] 2. Enter the gear name

[0107] User: The gear model is G34.

[0108] System: Gear model G34 has been recorded. Next, please enter the module of the gear.

[0109] 3. Input modulus

[0110] User: The modulus is 2.0.

[0111] System: Module 2.0 has been recorded. Please tell me the range of teeth corresponding to this module.

[0112] 4. Define the range of teeth

[0113] User: For module 2.0, the number of teeth can be selected from 16 to 24.

[0114] System: The recorded range of teeth corresponding to module 2.0 is 16 to 24. Do I need to set other correspondences between modules and the number of teeth?

[0115] 5. Set more module and tooth number ranges

[0116] User: Yes, the number of teeth corresponding to module 3.0 ranges from 20 to 30.

[0117] System: The recorded number of teeth for module 3.0 ranges from 20 to 30. Do I need to set the material selection next?

[0118] 6. Define material selection

[0119] User: For each module, the material can be selected as 45 steel and 20CrMnTi.

[0120] System: The material selection has been recorded. Next, what is the correspondence between the module and the material model?

[0121] 7. Define the model

[0122] User: When the module 2.0 is made of 45# steel, the standard model is G34-2.0-45. When 20CrMnTi is used, the standard model is G34-2.0-20CrMnTi.

[0123] System: Model number has been recorded. Is the material and model relationship the same for Modulus 3.0?

[0124] 8. Confirm other models

[0125] User: Yes, the model rules are the same for module 3.0.

[0126] System: The model relationship of Modulus 3.0 has been confirmed. Please confirm the information:

[0127] Model: G34

[0128] Module 2.0: Number of teeth range 16-24, material optional 45 steel, 20CrMnTi, corresponding models are G34-2.0-45 and G34-2.0-20CrMnTi

[0129] Module 3.0: number of teeth range 20-30, same material, same model rules

[0130] 9. User confirmation and completion

[0131] User: Confirmed.

[0132] System: All information has been confirmed to be correct. The parameters and optional range of gear G34 have been successfully entered. Do you need to add more rules or data?

[0133] It should be noted that during the conversation, the system can make contextual connections based on the component category and the content input by the user, and ask corresponding question information, such as "Please enter the name of the component", "What is the material of the component?", etc., so that the user can supplement the corresponding part attributes, part attribute values, etc. based on the question information output by the system.

[0134] The system dynamically generates questions based on the parameter template of the component type and the metadata definition in the knowledge base. The corresponding processing process can be:

[0135] In the system, a list of required parameters and parameter attributes (type, unit, value range, etc.) can be predefined in the knowledge base for each type of component (such as gears, bearings).

[0136] For example, the parameter template for a gear:

[0137]

[0138]

[0139] It should be understood that embodiments of the present invention include but are not limited to the above examples.

[0140] In the above process, the conversational selection system construction method allows users to enter parameters through dialogue. During the entry process, the system can verify the entered parameters through dialogue information with the user. On the one hand, users do not need to master complex database operations, which greatly simplifies the establishment process of the parts selection system and improves the efficiency of the selection system construction. On the other hand, the construction of the selection system by the system can improve the accuracy of the operation.

[0141] It should be noted that in the process of constructing the above-mentioned selection system, when the information input by the user fully meets the conditions for constructing the selection system, the system can construct the corresponding selection system based on the information input by the user. When the information input by the user does not meet the conditions, the system can guide the user to adjust the input information through the feedback unit to conduct verification and guidance during the dialogue process, thereby reducing the difficulty of constructing the selection system.

[0142] In an embodiment of the present invention, in addition to outputting parameter supplementary prompt information when the first input information only contains the part name in the above embodiment, the system can also verify the part attributes and part attribute values ​​that the user has entered to determine whether the part attributes and part attribute values ​​meet the corresponding verification conditions.

[0143] Optionally, during the inspection process, the system can first extract the target unit corresponding to the second part attribute, and then extract the unit mapping information and the standard value series table corresponding to the part name from the database. The unit mapping information includes the mapping relationship between the part parameters and the units. Then, the system searches the unit mapping table to find out whether there is a mapping relationship between the second part attribute and the target unit. If there is a mapping relationship between the second part attribute and the target unit in the unit mapping information, it is confirmed that the unit between the second part attribute and the target unit is accurate. At the same time, it can also search whether the first part attribute value exists in the standard value series table. If the first part attribute value exists in the standard value series table, it is confirmed that the attribute of the first part attribute value is reasonable. When the unit between the second part attribute and the target unit is accurate and the first part attribute value exists in the standard value series table, the selection management unit constructs a selection system based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name. In this way, the part attributes, part attribute values, etc. input by the user are inspected during the dialogue process to verify the rationality of the user input, and the data is corrected according to the standards in the database, thereby effectively ensuring the accuracy and effectiveness of the selection parameters and ensuring the success rate of the selection system construction.

[0144] In addition, in addition to checking the rationality of units and attribute values, it is also possible to determine whether the part attributes and part attribute values ​​entered by the user meet all the parameters required to build a complete selection system. By obtaining the necessary part attributes corresponding to the part name, and then comparing each second part with the necessary part attributes, it is determined whether all second part attributes correspond to the necessary part attributes one by one. When the units between the second part attributes and the target units are accurate, and the first part attribute values ​​exist in the standard value series table, and the second part attributes are exactly the same as the necessary part attributes, the selection management unit constructs the selection system according to the second part attributes and the first part attribute values ​​to obtain the selection system corresponding to the part name. Therefore, during the dialogue process, the part attributes, part attribute values, etc. entered by the user are checked for unit accuracy, attribute rationality and completeness, the rationality of the user input is verified, and the data is corrected according to the standards in the database, effectively ensuring the accuracy and effectiveness of the selection parameters and ensuring the success rate of the selection system construction.

[0145] In the above process, if the mapping relationship between the second part attribute and the target unit does not exist in the unit mapping information, parameter correction prompt information for the second part attribute and / or the target unit is output through the feedback unit, and the parameter correction prompt information is used to prompt the user to perform parameter correction on the second part attribute and / or the target unit. Correspondingly, if the first part attribute value does not exist in the standard value series table, value correction prompt information for the first part attribute value is output through the feedback unit, and the value correction prompt information is used to prompt the user to perform parameter value correction on the first part attribute value. Optionally, when the mapping relationship between the part attribute and the unit does not exist in the mapping relationship table, and the attribute value does not exist in the standard value series table, the system can also simultaneously output prompt information for prompting errors in the part attribute and attribute value, so as to prompt the user to adjust the part attribute and part attribute value, etc. The present invention is not limited to this.

[0146] In some examples, for the verification process of unit accuracy, assuming that when the user inputs hardness, the system verifies whether the hardness unit entered by the user is accurate based on the system knowledge base. For example, the Rockwell hardness unit of the gear is HRC, but the user writes HQC, the system can feedback that the hardness unit is wrong. For the verification process of attribute rationality, assuming that the gear module is a standardized parameter and must comply with the national standard series value (such as the first and second series in GB / T 1357), for example: the first series (preferred): 1, 1.25, 1.5, 2, 2.5, 3, 4, 5, 6... The second series (allowed for use): 1.125, 1.375, 1.75, 2.25, 2.75, 3.5... etc., then the corresponding verification process and example can be as follows:

[0147] User input:

[0148] Modulus input: "Modulo is 2.2" (non-standard value)

[0149] Modulus input: "The modulus is 3.5" (second series value)

[0150] Verification process:

[0151] Standard value matching:

[0152] The system loads the modular standard series list from the knowledge base.

[0153] Check if the input value matches the first or second series:

[0154] If the input is 2.2 → does not match the standard value, an error message is triggered: "The module must comply with the national standard series value. It is recommended to use the first series 2.0 or the second series 2.25."

[0155] If the input is 3.5 → it matches the second series and the verification passes.

[0156] In addition, for integrity inspection, assuming that the gear selection parameters include at least necessary part attributes such as part model, part name, module, tooth number range, material, etc., when the part attributes input by the user lack corresponding necessary part attributes, the system can output corresponding prompt information to prompt the user to supplement the corresponding part attributes, part attribute values, etc. The present invention does not impose any restrictions on this.

[0157] Through the above process, the part attributes and part attribute values ​​input by the user can be checked for unit accuracy, attribute rationality and completeness during the dialogue, verifying the rationality of the user input and correcting the data according to the standards in the database, effectively ensuring the accuracy and effectiveness of the selection parameters and ensuring the success rate of the selection system construction.

[0158] After the user completes the input of selection parameters such as part attributes and part attribute values ​​through the above process, the user can enter corresponding confirmation information to instruct the system to build a selection system corresponding to the component based on the input part attributes, part attribute values, etc. Among them, the database includes a parameter dictionary library, and the second part attribute includes the part type. In the process of constructing the selection system, the system can first map the second part attribute to the corresponding standard term through the parameter dictionary library, then unify the unit of the first part attribute value, and at the same time parse the value range, construct the standardized parameter key-value pair corresponding to the first part attribute value, and use the standard term and the standardized parameter key-value pair as the corresponding standardized parameter. Then, the selection rule library corresponding to the part type is loaded, and the selection rule set matching the standardized parameter is extracted from the selection rule library, and a mapping relationship table between the standardized parameter and the selection rule set is established. Finally, the mapping relationship table is used to construct the selection system corresponding to the part name, so that the user can enter the parameters through dialogue through the dialogue method. During the entry process, the system can verify the entered parameters through the dialogue information between the user and the user. On the one hand, the user does not need to master complex database operations, which greatly simplifies the establishment process of the part selection system and improves the efficiency of the selection system construction. On the other hand, the system constructs the selection system, which can improve the accuracy of the operation.

[0159] Among them, the parameter dictionary library can be a database that stores and manages the mapping relationship between various attributes and standard terms in the data. It can convert various different expressions that may appear in the system into standard and standardized ones to ensure the consistency and accuracy of the data and facilitate the construction of the subsequent selection system. For example, for parts such as "bolts", there may be different names such as "ordinary bolts", "hexagonal head bolts", and "screws" in the system, but the parameter dictionary library will map them all to a standard term, such as "standard bolts", etc. Each mapping relationship usually consists of the original attribute value and the corresponding standard term. In addition, in addition to the basic mapping relationship, the parameter dictionary library may also contain some auxiliary information, such as the attribute category, data source, instructions for use, etc. For example, for the "color" attribute, it may be marked which types of parts the attribute applies to, as well as the actual colors corresponding to different color codes.

[0160] Furthermore, the selection rule library can be a database that stores various selection rules for different objects (such as different parts). This serves as a screening criterion, used to select objects that meet the requirements from a large selection pool based on the object's attributes and specific needs. For example, each rule typically consists of two parts: a condition and a conclusion. The condition describes the attribute requirements that the object must meet, while the conclusion describes the selection result if the condition is met.

[0161] For example, regarding the conditions in the gear selection rules, gears play an important role in transmitting power and changing speed in mechanical transmissions. For a machine tool transmission system, the gear selection conditions can be set as follows: If the gear module is 3, the number of teeth is between 20-30, the tooth surface hardness reaches HRC50-55 (Rockwell hardness), and the gear helix angle is 20°, then this gear may be suitable for the machine tool transmission system. The module, number of teeth, tooth surface hardness, and helix angle are the attribute requirements of the gear, and the conclusion part can be: When the gear meets these conditions, the selection result is: This gear can be used for the machine tool spindle drive, can achieve a precise transmission ratio, ensure the machine tool processing accuracy, and at the same time have sufficient wear resistance and strength.

[0162] Optionally, in the selection rule library, different components may correspond to different selection rules.

[0163] In one example, when the system is building a selection system, the second part attribute is the part type, and the first part attribute value is other attributes related to the part, such as size, weight, etc. The corresponding specific implementation steps can be as follows:

[0164] 1. Attribute mapping to standard terminology

[0165] First, for the second part attribute (i.e., part type), for example, the system may have different types of part records, such as "ordinary bolt" and "high-strength bolt," but the parameter dictionary library specifies the use of standard terms such as "standard bolt" and "high-performance bolt." When the system receives the part type "ordinary bolt," it can map it to "standard bolt" and "high-strength bolt" to "high-performance bolt" through the parameter dictionary library, completing the conversion from part type to standard terminology.

[0166] 2. First part attribute value processing

[0167] Since the first part attribute value can contain the values ​​or value ranges corresponding to various specific attributes of the part, different units may exist. For example, some part length attributes are recorded as "10 cm" and some are recorded as "0.1 m". The system will identify these different units and convert them into a standard unit, such as "m". In this way, "10 cm" will be converted to "0.1 m", which is convenient for subsequent calculations and comparisons. In addition to unit unification, the system will also parse the value range of the attribute value. For example, the weight attribute of a part may be recorded as "5-10 kg". The system will parse this value range and construct a standardized parameter key-value pair. In this example, the key is "weight" and the value is "5-10 kg". After unit unification and value range parsing, a series of standardized parameter key-value pairs are obtained.

[0168] 3. Generate standardized parameters

[0169] Combine the standard terms (part type mapping results) obtained in the previous step with the standardized parameter key-value pairs to form a complete standardized parameter. For example, the part type is "standard bolt", the length is "0.1 meter", and the weight is "5-10 kg". This information is combined to form the standardized parameters of the part.

[0170] 4. Load the selection rule library

[0171] Different part types correspond to different selection rule libraries. Just as different products have different quality standards and screening criteria, once a part type is determined (e.g., "standard bolt"), the system loads the corresponding selection rule library from the database. This selection rule library contains a series of selection rules specific to that part type, such as bolt length ranges and tensile strength requirements.

[0172] 5. Extract the matching selection rule set

[0173] The system can compare the previously obtained standardized parameters with the loaded selection rule library. For example, for a "standard bolt," if the standardized parameters specify a bolt length of "0.1 meter" and a weight of "5-10 kilograms," the system will search the selection rule library for a rule that matches these parameters. For example, if the rule library contains the rule "Bolts with a length between 0.08-0.12 meters and a weight between 3-12 kilograms meet the requirements," this rule will be extracted, forming a set of selection rules that match the standardized parameters.

[0174] 6. Establish a mapping relationship table

[0175] A mapping table is created between standardized parameters and matching selection rule sets. The mapping table acts as a "bridge" to connect the specific properties of a part with the applicable selection rules.

[0176] For example, for a "standard bolt", its standardized parameters (length "0.1 meter", weight "5-10 kilograms") correspond to one or more selection rules. These correspondences are recorded in a mapping relationship table to facilitate subsequent query and use.

[0177] 7. Build a selection system

[0178] Finally, the established mapping table is used to build a selection system corresponding to part names. When a user enters part attribute information, the system searches the mapping table for applicable selection rules to filter out parts that meet the requirements. For example, if a user enters "standard bolt, length 0.1 meter, weight 7 kg," the system will use the mapping table to find the corresponding selection rule, determine whether the bolt meets the requirements, and provide the screening results.

[0179] Through the above process, the conversational selection system construction method allows users to enter parameters through dialogue. During the entry process, the system can verify the entered parameters through dialogue information with the user. On the one hand, users do not need to master complex database operations, which greatly simplifies the establishment process of the parts selection system and improves the efficiency of the selection system construction. On the other hand, the construction of the selection system by the system can improve the accuracy of the operation.

[0180] In addition, during the construction of the selection system, or when the user wants to modify the target part attributes, target part attribute values, etc. in the corresponding selection system, the user can also adjust the parameters through dialogue. The specific process may include:

[0181] Step 7: In response to the parameter adjustment instruction input by the user, the natural language processing unit recognizes the parameter adjustment instruction, and the feedback unit outputs product confirmation information for the parameter adjustment instruction, the product confirmation information being used to prompt the user to input the part attributes that need to be updated;

[0182] Step 8: In response to the product confirmation information input by the user, extracting at least one of a corresponding third part attribute and a second part attribute value from the third input information through the natural language processing unit;

[0183] Step 9: Execute parameter adjustment operations corresponding to the third part attribute and / or the second part attribute value.

[0184] In one example, during the parameter adjustment process, the dialogue between the user and the system may be as follows:

[0185] User: "I think the torque transmission capacity of the current gear is insufficient, and I need to adjust the parameters to enhance it."

[0186] System: "We understand your needs. Please tell me the gear properties you want to update. Properties like module and number of teeth have a significant impact on torque transmission capacity."

[0187] User: "Increase the module to 3 and adjust the number of teeth to 35."

[0188] System: The third part attribute is "gear", and the second part attribute values ​​are "module 3" and "number of teeth 35".

[0189] System: Filters gears with a module of 3 and a number of teeth of 35 in the database, updates the selection results, and provides analysis of the improvement in the torque transmission capacity of the adjusted gears and the impact on other parameters such as the transmission ratio.

[0190] Through the above process, users can adjust the relevant parameters of the selection system according to their needs, so that the selection system can be flexibly expanded according to different rules, further improving the construction flexibility of the selection system.

[0191] In another example, the processing flow of the system may include:

[0192] 1. Parameter definition and input: Users gradually define basic parameters of the gear, such as module, number of teeth, and material, through dialogue, and provide optional ranges and corresponding relationship rules for these parameters (such as the module and number of teeth range, the relationship between material and model, etc.).

[0193] 2. Rule verification and storage: The system automatically verifies whether the scope and relationship provided by the user are reasonable, and stores these data in the selection system after confirmation.

[0194] 3. Flexibility and scalability: Users can continue to add or modify optional ranges and relationships according to their needs, so that the selection system can be flexibly expanded according to different specifications.

[0195] It should be noted that the embodiments of the present invention include but are not limited to the above examples. It is understandable that those skilled in the art can also make settings according to actual needs under the guidance of the ideas of the embodiments of the present invention, and the present invention does not limit this.

[0196] In an embodiment of the present invention, in the process of the user constructing a selection system for the corresponding parts, a parameter entry system can be constructed first. The parameter entry system at least includes a natural language processing unit, a database, a selection system management unit and a feedback unit. The construction of the selection system can be quickly realized through the parameter entry system. In response to detecting the part processing instruction input by the user, the natural language processing unit identifies the part processing instruction, and the feedback unit outputs part attribute prompt information for the part processing instruction. The part attribute prompt information is used to prompt the user to input the corresponding part attribute content. Then, in response to the first input information input by the user for questioning information about the part attribute, the natural language processing unit extracts the first part attribute from the first input information. If the first part attribute only contains the part name, the feedback unit outputs parameter supplement prompt information for the part name. The parameter supplement prompt information is used to prompt the user to input the corresponding part attribute, and then the system can respond. In response to the second input information input by the user for the parameter supplement prompt information, the natural language processing unit extracts the second part attribute corresponding to the part name and the first part attribute value corresponding to the second part attribute from the second input information, and performs a necessity check on the second part attribute and the first part attribute value through the database. If the second part attribute and the first part attribute value are successfully checked, the selection management unit constructs a selection system according to the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name, so that the user can enter the parameters through dialogue through the conversational selection system construction method. During the entry process, the system can verify the entered parameters through the conversation information between the user and the user. On the one hand, the user does not need to master complex database operations, which greatly simplifies the establishment process of the part selection system and improves the efficiency of the selection system construction. On the other hand, the construction of the selection system by the system can improve the accuracy of the operation.

[0197] It should be noted that for the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0198] Reference Figure 2 , shows a structural block diagram of a dialog-based selection system construction device provided in an embodiment of the present invention, which is applied to a parameter entry system. The parameter entry system includes at least a natural language processing unit, a database, a selection system management unit, and a feedback unit; specifically, the following modules may be included:

[0199] A first instruction recognition module 201 is configured to, in response to detecting a component processing instruction input by a user, recognize the component processing instruction through the natural language processing unit, and output part attribute prompt information corresponding to the component processing instruction through the feedback unit, wherein the part attribute prompt information is used to prompt the user to input corresponding part attribute content;

[0200] An information extraction module 202 is configured to extract a first part attribute from the first input information input by the user inquiring about the part attribute by using the natural language processing unit;

[0201] a prompt output module 203 configured to output parameter supplementary prompt information for the part name through the feedback unit if the first part attribute only includes the part name, the parameter supplementary prompt information being used to prompt the user to input the corresponding part attribute;

[0202] an attribute extraction module 204 for extracting, in response to second input information input by the user for the parameter supplementary prompt information, a second part attribute corresponding to the part name and a first part attribute value corresponding to the second part attribute from the second input information through the natural language processing unit;

[0203] The system construction module 205 is used to perform a necessity check on the second part attribute and the first part attribute value through the database. If the second part attribute and the first part attribute value are successfully checked, the selection management unit constructs a selection system based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name.

[0204] In some feasible implementations, the system construction module 205 is specifically configured to:

[0205] extracting a target unit corresponding to the second part attribute;

[0206] Extracting unit mapping information and a standard value series list corresponding to the part name from the database, wherein the unit mapping information includes a mapping relationship between part parameters and units;

[0207] If a mapping relationship between the second part attribute and the target unit exists in the unit mapping information, confirming that the units between the second part attribute and the target unit are accurate;

[0208] If the first part attribute value exists in the standard value list, confirming that the attribute of the first part attribute value is reasonable;

[0209] When the units between the second part attribute and the target unit are accurate and the first part attribute value exists in the standard value series table, the selection management unit constructs a selection system based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name.

[0210] In some feasible implementations, the system construction module 205 is specifically configured to:

[0211] Obtain necessary part attributes corresponding to the part name;

[0212] When the units of the second part attribute and the target unit are accurate, the value of the first part attribute exists in the standard value series table, and the second part attribute is exactly the same as the required part attribute, the selection management unit constructs a selection system based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name.

[0213] Some possible implementations also include:

[0214] A parameter correction prompt module is used to output parameter correction prompt information for the second part attribute and / or the target unit through the feedback unit if there is no mapping relationship between the second part attribute and the target unit in the unit mapping information. The parameter correction prompt information is used to prompt the user to perform parameter correction on the second part attribute and / or the target unit.

[0215] Some possible implementations also include:

[0216] The attribute value correction prompt module is used to output value correction prompt information for the first part attribute value through the feedback unit if the first part attribute value does not exist in the standard value series list, and the value correction prompt information is used to prompt the user to correct the parameter value of the first part attribute value.

[0217] Some possible implementations also include:

[0218] a second instruction recognition module, configured to respond to a parameter adjustment instruction input by the user, recognize the parameter adjustment instruction through the natural language processing unit, and output product confirmation information for the parameter adjustment instruction through the feedback unit, wherein the product confirmation information is used to prompt the user to input part attributes that need to be updated;

[0219] a confirmation module, configured to extract at least one of a third part attribute and a second part attribute value corresponding to the third input information through the natural language processing unit in response to the confirmation information input by the user for the product;

[0220] An adjustment module is used to perform parameter adjustment operations corresponding to the third part attribute and / or the second part attribute value.

[0221] In some feasible implementations, the database includes a parameter dictionary library, the second part attribute includes a part type, and the system construction module 205 is specifically configured to:

[0222] Mapping the second part attribute to a corresponding standard term through the parameter dictionary library;

[0223] Unifying the units of the first part attribute values ​​and simultaneously parsing the value range, constructing standardized parameter key-value pairs corresponding to the first part attribute values, and using the standard term and the standardized parameter key-value pairs as corresponding standardized parameters;

[0224] Loading a selection rule library corresponding to the part type, and extracting a selection rule set matching the standardized parameters from the selection rule library;

[0225] Establishing a mapping relationship table between the standardized parameters and the selection rule set;

[0226] The mapping relationship table is used to construct a selection system corresponding to the part name.

[0227] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0228] In addition, an embodiment of the present invention also provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and runnable on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned dialogue-based selection system construction method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0229] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program implements the various processes of the embodiment of the above-mentioned method for constructing a dialog-based selection system and achieves the same technical effect. To avoid repetition, the details are not described here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0230] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0231] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, apparatuses, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, EEPROM, Flash, and eMMC, etc.) containing computer-usable program code.

[0232] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the process in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0233] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0234] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0235] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0236] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0237] The above is a detailed introduction to a method for constructing a selection system based on a dialogue and a device for constructing a selection system based on a dialogue provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for constructing a selection system based on a dialogue, characterized in that: Applied to a parameter entry system, the parameter entry system includes at least a natural language processing unit, a database, a selection system management unit, and a feedback unit; wherein the method includes: Step 1: In response to detecting a component processing instruction input by a user, the natural language processing unit recognizes the component processing instruction, and the feedback unit outputs part attribute prompt information corresponding to the component processing instruction, wherein the part attribute prompt information is used to prompt the user to input corresponding part attribute content; Step 2: In response to first input information input by the user asking about the component attribute information, extracting a first part attribute from the first input information by the natural language processing unit; Step 3: If the first part attribute only includes a part name, outputting parameter supplementary prompt information for the part name through the feedback unit, wherein the parameter supplementary prompt information is used to prompt the user to input the corresponding part attribute; Step 4: In response to second input information input by the user for the parameter supplement prompt information, extracting, by the natural language processing unit, a second part attribute corresponding to the part name and a first part attribute value corresponding to the second part attribute from the second input information; Step 5: Perform a necessity check on the second part attribute and the first part attribute value through the database. If the check is successful, construct a selection system based on the second part attribute and the first part attribute value through the selection management unit to obtain the selection system corresponding to the part name.

2. The method according to claim 1, characterized in that The necessity check is performed on the second part attribute and the first part attribute value by the database. If the check succeeds, the selection management unit constructs a selection system according to the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name, including: extracting a target unit corresponding to the second part attribute; Extracting unit mapping information and a standard value series list corresponding to the part name from the database, wherein the unit mapping information includes a mapping relationship between part parameters and units; If a mapping relationship between the second part attribute and the target unit exists in the unit mapping information, confirming that the units between the second part attribute and the target unit are accurate; If the first part attribute value exists in the standard value list, confirming that the attribute of the first part attribute value is reasonable; When the units between the second part attribute and the target unit are accurate and the first part attribute value exists in the standard value series table, the selection management unit constructs a selection system based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name.

3. The method according to claim 2, characterized in that When the second part attribute and the target unit are accurate and the first part attribute value exists in the standard value series table, the selection management unit constructs a selection system according to the second part attribute and the first part attribute value to obtain a selection system corresponding to the part name, including: Obtain necessary part attributes corresponding to the part name; When the units of the second part attribute and the target unit are accurate, the value of the first part attribute exists in the standard value series table, and the second part attribute is exactly the same as the required part attribute, the selection management unit constructs a selection system based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name.

4. The method according to claim 2, characterized in that Also includes: If there is no mapping relationship between the second part attribute and the target unit in the unit mapping information, parameter correction prompt information for the second part attribute and / or the target unit is output through the feedback unit, and the parameter correction prompt information is used to prompt the user to perform parameter correction on the second part attribute and / or the target unit.

5. The method according to claim 2 or 3, characterized in that Also includes: If the first part attribute value does not exist in the standard value series table, value correction prompt information for the first part attribute value is output through the feedback unit, and the value correction prompt information is used to prompt the user to correct the parameter value of the first part attribute value.

6. The method according to claim 1, characterized in that Also includes: Step 7: In response to the parameter adjustment instruction input by the user, the natural language processing unit recognizes the parameter adjustment instruction, and the feedback unit outputs product confirmation information for the parameter adjustment instruction, wherein the product confirmation information is used to prompt the user to input the part attributes that need to be updated; Step 8: In response to the product confirmation information input by the user, extracting at least one of a corresponding third part attribute and a second part attribute value from the third input information by the natural language processing unit; Step 9: Execute parameter adjustment operations corresponding to the third part attribute and / or the second part attribute value.

7. The method according to claim 1, characterized in that The database includes a parameter dictionary library, the second part attribute includes a part type, and the selection system is constructed based on the second part attribute and the first part attribute value to obtain the selection system corresponding to the part name, including: Mapping the second part attribute to a corresponding standard term through the parameter dictionary library; Unifying the units of the first part attribute values ​​and simultaneously parsing the value range, constructing standardized parameter key-value pairs corresponding to the first part attribute values, and using the standard term and the standardized parameter key-value pairs as corresponding standardized parameters; Loading a selection rule library corresponding to the part type, and extracting a selection rule set matching the standardized parameters from the selection rule library; Establishing a mapping relationship table between the standardized parameters and the selection rule set; The mapping relationship table is used to construct a selection system corresponding to the part name.

8. A device for constructing a selection system based on a dialogue, characterized in that: Applied to a parameter entry system, the parameter entry system includes at least a natural language processing unit, a database, a selection system management unit, and a feedback unit; wherein the device includes: a first instruction recognition module, configured to, in response to detecting a component processing instruction input by a user, recognize the component processing instruction through the natural language processing unit, and output part attribute prompt information corresponding to the component processing instruction through the feedback unit, wherein the part attribute prompt information is used to prompt the user to input corresponding part attribute content; an information extraction module, configured to extract a first part attribute from the first input information input by the user inquiring about the part attribute information through the natural language processing unit; a prompt output module, configured to output parameter supplementary prompt information for the part name through the feedback unit if the first part attribute only includes the part name, wherein the parameter supplementary prompt information is used to prompt the user to input the corresponding part attribute; an attribute extraction module, configured to extract, in response to second input information input by the user for the parameter supplementary prompt information, a second part attribute corresponding to the part name and a first part attribute value corresponding to the second part attribute from the second input information through the natural language processing unit; A system construction module is used to perform a necessity check on the second part attribute and the first part attribute value through the database. If the second part attribute and the first part attribute value are successfully checked, a selection system is constructed according to the second part attribute and the first part attribute value through the selection management unit to obtain a selection system corresponding to the part name.

9. An electronic device, characterized in that: comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; The memory is used to store computer programs; The processor is configured to implement the method according to any one of claims 1 to 7 when executing a program stored in the memory.

10. A computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform the method according to any one of claims 1 to 7.

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