Electronic component automatic recommendation method and system based on parameter weight

Abstract

The invention provides an electronic component automatic recommendation method and system based on parameter weight, and relates to the technical field, and the method comprises the steps: dividing a parameter set into numeric type, character type and Boolean type parameters through obtaining a retrieval condition and parameter weight configuration information input by a user; numerical value comparison, vector cosine similarity calculation and Boolean value comparison are carried out on the candidate electronic components, matching results of various parameters are multiplied by weight values and accumulated to obtain matching degree scores, and finally the candidate electronic components are sorted according to the matching degree scores and displayed in a classified mode according to attributes of manufacturers. According to the method, weight configuration can be carried out on the parameters according to personalized requirements of users, the accuracy and efficiency of electronic component retrieval are improved, and differentiated retrieval requirements of different users are met.

Description

Technical Field

[0001] The present invention relates to electronic component technology, and in particular to a method and system for automatically recommending electronic components based on parameter weights. Background Art

[0002] In the process of electronic product design and development, the selection of electronic components is a key link, which directly affects the performance, cost and market competitiveness of the product. With the rapid development of the electronics industry, the types of electronic components are becoming more and more diverse, and there are tens of thousands of product models launched by different manufacturers. Engineers need to screen from a large number of electronic components when selecting products. At present, the mainstream way to select electronic components is through a multi-parameter retrieval system, which is based on the various technical parameters of the product;

[0003] However, the existing electronic component retrieval system has the following shortcomings: first, the retrieval system cannot configure personalized parameter weights according to the differentiated needs of different users, resulting in a deviation between the retrieval results and the actual needs of users; second, the retrieval system lacks an intelligent processing mechanism for different types of parameters, especially the fuzzy matching ability of character-type parameters is weak, which reduces the accuracy of retrieval; third, the retrieval results are displayed in a single way and fail to be classified and presented according to manufacturer attributes, which is not conducive to users quickly identifying and comparing products from different sources;

[0004] In view of this, the present invention aims to provide an automatic recommendation method for electronic components based on parameter weights, by introducing a parameter weight configuration mechanism, combining intelligent processing solutions for numerical, character and Boolean parameters, and adopting a multi-dimensional result display method, so as to solve the technical problems existing in the prior art such as low retrieval efficiency, poor matching accuracy and unreasonable result display. Summary of the invention

[0005] The embodiments of the present invention provide methods and systems that can solve the problems in the prior art.

[0006] According to a first aspect of the embodiments of the present invention,

[0007] Provides an automatic recommendation method for electronic components based on parameter weights, including:

[0008] Receive the target electronic component model input by the user, and display the electronic component information corresponding to the target electronic component model, the electronic component information including picture information, model information, packaging information, description information, category information and manufacturer information; respond to the user's confirmation operation on the electronic component information, and obtain the parameter set corresponding to the target electronic component model.

[0009] Convert the parameter value of the character parameter into a corresponding parameter vector; calculate the cosine similarity between the parameter vector and the vector of the corresponding parameter of the candidate electronic component; determine whether the cosine similarity is greater than a preset similarity threshold; when the cosine similarity is greater than the preset similarity threshold, set the second matching result of the character parameter to the corresponding weight value; when the cosine similarity is less than or equal to the preset similarity threshold, set the second matching result of the character parameter to zero.

[0010] The preset similarity threshold is 0.7.

[0011] The entire parameter set includes a material classification parameter set, and the material classification parameter set includes a model parameter set.

[0012] In the display area corresponding to each of the manufacturer attributes, the candidate electronic components are arranged in descending order according to the matching scores; and the picture information, model information, packaging information, description information, category information and manufacturer information of each of the candidate electronic components are displayed.

[0013] According to a second aspect of the embodiments of the present invention,

[0014] Provides an automatic recommendation system for electronic components based on parameter weights, including:

[0015] The first unit is used to obtain an electronic component search condition input by a user, wherein the search condition includes a corresponding parameter set; determine an associated parameter set according to the electronic component search condition, wherein the parameter set is divided into a numerical parameter, a character parameter, and a Boolean parameter according to the parameter type; receive a weight value set by the user for each parameter in the parameter set, and generate parameter weight configuration information;

[0016] The second unit is used to calculate the matching score of the candidate electronic component based on the parameter weight configuration information, including: performing numerical comparison on the numerical parameter to obtain a first matching result, converting the parameter value into a vector for the character parameter and calculating the cosine similarity to obtain a second matching result, performing Boolean value comparison on the Boolean parameter to obtain a third matching result, and multiplying the first matching result, the second matching result, and the third matching result by the corresponding weight value respectively and accumulating them to obtain the matching score of the candidate electronic component;

[0017] The third unit is used to sort the candidate electronic components according to the matching scores and display them by categories, wherein the category display includes dividing the candidate electronic components into domestic manufacturer products, foreign manufacturer products and same manufacturer products according to manufacturer attributes for display.

[0018] According to a third aspect of the embodiments of the present invention,

[0019] An electronic device is provided, comprising:

[0020] processor;

[0021] a memory for storing processor-executable instructions;

[0022] The processor is configured to call the instructions stored in the memory to execute the aforementioned method.

[0023] A fourth aspect of the embodiments of the present invention is:

[0024] A computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the aforementioned method is implemented.

[0025] The beneficial effects of this application are as follows:

[0026] The present invention introduces a parameter weight configuration mechanism, allowing users to set weight values ​​for different parameters according to actual needs, thereby realizing personalized customization of the retrieval process. Users can focus on the importance of specific parameters and reduce the influence of secondary parameters, so that the retrieval results are closer to the actual needs of users, effectively improving the accuracy of electronic component selection.

[0027] The present invention adopts intelligent processing schemes for different parameter types. Numerical parameters are processed by numerical comparison, character parameters are processed by vector cosine similarity algorithm, Boolean parameters are processed by Boolean comparison, and the comprehensive matching score is calculated in combination with the weight value. This multi-dimensional parameter processing method significantly improves the intelligence level of the retrieval system, especially when processing character parameters, through vectorization conversion and similarity calculation, the fuzzy matching ability is greatly enhanced.

[0028] The present invention innovatively displays search results by manufacturer attributes, and divides candidate electronic components into three categories: domestic manufacturer products, foreign manufacturer products, and same manufacturer products. This multi-dimensional display method facilitates users to quickly compare parameter characteristics of products from different sources, facilitates users to make horizontal comparisons and selection decisions, and significantly improves the efficiency of electronic component selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A schematic diagram of a flow chart of a method for automatically recommending electronic components based on parameter weights according to an embodiment of the present invention;

[0030] Figure 2 A schematic diagram of a process of sorting the embodiments of the present invention from high to low scores;

[0031] Figure 3 Schematic diagram of the structure of an automatic electronic component recommendation system based on parameter weights according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0034] Figure 1 Schematic diagram of the process of the method for automatically recommending electronic components based on parameter weights according to an embodiment of the present invention. Figure 2 FIG. 1 is a flowchart of an embodiment of the present invention sorted by scores from high to low, such as Figure 1-2 As shown, the method includes:

[0035] S11. The electronic component automatic recommendation system provides two search modes: query based on known device models and query based on material classification. The system supports the search and recommendation of various types of electronic components including microcontrollers, operational amplifiers, resistors and capacitors.

[0036] S12. For the query mode based on known device models, when the user enters a model such as "LPC824", the system first displays the detailed information of the model. Taking the microcontroller as an example, the displayed information includes chip physical pictures, package specifications (such as LQFP48), core description (such as 32-bit ARM Cortex-M0+ core), operating voltage (such as 1.8V-3.6V) and other parameter information. After the user confirms the target model, the system automatically extracts the complete parameter set of the model.

[0037] S13. In the parameter weight configuration interface, the system displays the parameters by category: numerical parameters include operating voltage, operating temperature, clock frequency, etc.; character parameters include peripheral configuration (such as "2×SPI, 4×I 2C"), package type, etc.; Boolean parameters include whether online debugging is supported, whether DMA is supported, etc. Users can assign a weight value of 0-100 to each parameter through the slider to reflect the importance of different parameters.

[0038] The matching degree calculation adopts a classification processing strategy. For numerical parameters, the system determines whether the candidate product parameters are within the target range, such as whether the operating voltage of 2.7V-5.5V covers the target requirement of 3.3V±10%. For character parameters, the system converts the text into a feature vector and calculates the similarity. For example, the interface configuration similarity of "3×UART,2×SPI" and "2×UART,2×SPI" is 0.8. For Boolean parameters, the truth value is directly compared.

[0039] In the query mode based on material classification, the system adopts a hierarchical parameter system. The user selects a material category (such as analog chips), and the system automatically loads the parameter template of that type (such as input offset, gain bandwidth, etc.). After the user fills in the parameter value and sets the weight, the system uses the same matching calculation method to recommend products.

[0040] In terms of interface display, the system divides the search results into three areas: products from domestic manufacturers, products from foreign manufacturers, and products from the same manufacturer. Each candidate product displays complete parameter information and physical pictures, supporting multi-dimensional comparison.

[0041] Beneficial effects:

[0042] 1. By introducing the parameter weight mechanism, personalized customization of the retrieval process is achieved. Users can flexibly adjust the importance of parameters according to actual application requirements, which improves the accuracy and efficiency of component selection and effectively solves the problem that traditional retrieval methods cannot reflect the differences in parameter importance.

[0043] 2. A classification parameter processing strategy is adopted, and special matching algorithms are used for numerical, character and Boolean parameters respectively. In particular, the fuzzy matching of character parameters is processed by vectorization method, which significantly improves the intelligence level and retrieval accuracy of the system.

[0044] 3. Innovatively introduce a multi-dimensional result display mechanism, classify and display candidate products by manufacturer attributes, and provide complete parameter comparison information, so that users can comprehensively evaluate the performance characteristics and supply status of different products, and optimize the selection decision-making process.

[0045] Through the browser plug-in, a convenient user operation interface is provided. The homepage contains a model query area, where users can enter basic information such as the model, package, manufacturer, etc. of the component to be replaced. The system associates this information with the component classification information to determine the only target component.

[0046] In the parameter query interface, the detailed parameter information of the target components is displayed. Each parameter item contains the parameter name, parameter value, unit information, and a switch button to configure whether to participate in the comparison. The position of the parameter is adjusted by moving up and down. The closer the position is, the higher the weight. The system converts the parameter position information into a basic weight value, and the parameters in the front position obtain a higher basic weight. For specific parameters, users can fine-tune the weight using the +1% and -1% buttons, and the system automatically makes proportional and balanced adjustments to the weights of other parameters to ensure that the total weight value is constant.

[0047] Taking a certain type of resistor as an example, the system first displays its rated power, resistance value, temperature coefficient, size and other parameters. The user moves the temperature coefficient parameter to the first place, and increases its weight from the original 0.1 to 0.3, while adding an additional weight of 5%. The system automatically reduces the weights of other parameters in proportion to keep the total weight at 1.

[0048] According to the set parameter weights, the system searches the component library and calculates the parameter matching degree between the candidate replacement components and the target components. The matching degree calculation comprehensively considers the similarity of the parameter values ​​and the corresponding weights to generate a score from 0 to 100. The system sorts the candidate components in descending order by score and displays them by manufacturer and package type.

[0049] In the query result interface, users can adjust the parameter weight configuration, and the system will update the matching results in real time. By canceling the comparison of some non-critical parameters, adjusting the parameter position, setting additional weights, etc., the matching results will change dynamically to meet the replacement needs of different application scenarios. The system records the parameter weight adjustment process and intuitively displays the impact of weight changes on matching results.

[0050] The solution of this application can:

[0051] Through the combined mechanism of parameter position adjustment and additional weight setting, the importance of parameters is accurately quantified, which improves the matching accuracy of component alternatives. The dynamic weight balancing mechanism is adopted to automatically maintain the total weight constant when adjusting the weight of a single parameter, ensuring the comparability and rationality of the alternative scoring. It provides an intuitive visual operation interface and real-time response mechanism, supports flexible adjustment of parameter weight configuration, and quickly obtains updated matching results, which improves the ease of use and work efficiency of the system. Figure 3 FIG. 1 is a schematic diagram of the structure of an automatic electronic component recommendation system based on parameter weights according to an embodiment of the present invention. Figure 3 As shown, the system comprises:

[0052] The first unit is used to obtain an electronic component search condition input by a user, wherein the search condition includes a corresponding parameter set; determine an associated parameter set according to the electronic component search condition, wherein the parameter set is divided into a numerical parameter, a character parameter, and a Boolean parameter according to the parameter type; receive a weight value set by the user for each parameter in the parameter set, and generate parameter weight configuration information;

[0053] The second unit is used to calculate the matching score of the candidate electronic component based on the parameter weight configuration information, including: performing numerical comparison on the numerical parameter to obtain a first matching result, converting the parameter value into a vector for the character parameter and calculating the cosine similarity to obtain a second matching result, performing Boolean value comparison on the Boolean parameter to obtain a third matching result, and multiplying the first matching result, the second matching result, and the third matching result by the corresponding weight value respectively and accumulating them to obtain the matching score of the candidate electronic component;

[0054] The third unit is used to sort the candidate electronic components according to the matching scores and display them by categories, wherein the category display includes dividing the candidate electronic components into domestic manufacturer products, foreign manufacturer products and same manufacturer products according to manufacturer attributes for display.

[0055] According to a third aspect of the embodiments of the present invention,

[0056] An electronic device is provided, comprising:

[0057] processor;

[0058] a memory for storing processor-executable instructions;

[0059] The processor is configured to call the instructions stored in the memory to execute the aforementioned method.

[0060] A fourth aspect of the embodiments of the present invention is:

[0061] A computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the aforementioned method is implemented.

[0062] The present invention may be a method, an apparatus, a system and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present invention.

[0063] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An automatic recommendation method for electronic components based on parameter weights, characterized in that: include: Acquire electronic component search conditions input by a user, wherein the search conditions include corresponding parameter sets; determine associated parameter sets according to the electronic component search conditions, wherein the parameter sets are divided into numerical parameters, character parameters, and Boolean parameters according to parameter types; receiving a weight value set by a user for each parameter in the parameter set, and generating parameter weight configuration information; Calculating the matching scores of candidate electronic components based on the parameter weight configuration information, including: performing numerical comparison on the numerical parameters to obtain a first matching result, converting the parameter values ​​of the character parameters into vectors and calculating the cosine similarity to obtain a second matching result, performing Boolean value comparison on the Boolean parameters to obtain a third matching result, and multiplying the first matching result, the second matching result, and the third matching result by the corresponding weight values ​​respectively and accumulating them to obtain the matching scores of the candidate electronic components; The candidate electronic components are sorted according to the matching scores and displayed in categories. The category display includes dividing the candidate electronic components into domestic manufacturer products, foreign manufacturer products and same manufacturer products according to manufacturer attributes for display.

2. The method according to claim 1, characterized in that The method for obtaining the electronic component search condition includes: Receive the target electronic component model input by the user, and display the electronic component information corresponding to the target electronic component model, the electronic component information including picture information, model information, packaging information, description information, category information and manufacturer information; respond to the user's confirmation operation on the electronic component information, and obtain the parameter set corresponding to the target electronic component model.

3. The method according to claim 1, characterized in that The process of obtaining the second matching result includes: Convert the parameter value of the character parameter into a corresponding parameter vector; calculate the cosine similarity between the parameter vector and the vector of the corresponding parameter of the candidate electronic component; determine whether the cosine similarity is greater than a preset similarity threshold; when the cosine similarity is greater than the preset similarity threshold, set the second matching result of the character parameter to the corresponding weight value; when the cosine similarity is less than or equal to the preset similarity threshold, set the second matching result of the character parameter to zero.

4. The method according to claim 4, characterized in that: The preset similarity threshold is 0.

7.

5. The method according to claim 1, characterized in that: An electronic component retrieval system is established through a hierarchical inclusion relationship of parameter sets, wherein the hierarchical inclusion relationship is: all parameter sets include material classification parameter sets, and the material classification parameter sets include model parameter sets.

6. The method according to claim 1, characterized in that The classification display includes: In the display area corresponding to each of the manufacturer attributes, the candidate electronic components are arranged in descending order according to the matching scores; and the picture information, model information, packaging information, description information, category information and manufacturer information of each of the candidate electronic components are displayed.

7. An automatic electronic component recommendation system based on parameter weights, used to implement the method according to any one of claims 1 to 6, characterized in that: include: The first unit is used to obtain an electronic component search condition input by a user, wherein the search condition includes a corresponding parameter set; determine an associated parameter set according to the electronic component search condition, wherein the parameter set is divided into a numerical parameter, a character parameter, and a Boolean parameter according to a parameter type; receiving a weight value set by a user for each parameter in the parameter set, and generating parameter weight configuration information; The second unit is used to calculate the matching score of the candidate electronic component based on the parameter weight configuration information, including: performing numerical comparison on the numerical parameter to obtain a first matching result, converting the parameter value into a vector for the character parameter and calculating the cosine similarity to obtain a second matching result, performing Boolean value comparison on the Boolean parameter to obtain a third matching result, and multiplying the first matching result, the second matching result, and the third matching result by the corresponding weight value respectively and accumulating them to obtain the matching score of the candidate electronic component; The third unit is used to sort the candidate electronic components according to the matching scores and display them by categories, wherein the category display includes dividing the candidate electronic components into domestic manufacturer products, foreign manufacturer products and same manufacturer products according to manufacturer attributes for display.

8. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to call the instructions stored in the memory to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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