A method for integrated design and processing of whole-house woodworking customization based on big data

Abstract

The present invention provides a whole-house wood customization integrated design processing method based on big data, which belongs to the field of big data technology, and specifically includes: determining the user's demand keywords based on the user's description data, and determining the user matching degree between the user and different historical users and the matching user through the user's demand keywords, house type data and the region where the user is located, obtaining the user's demand keywords and house type data, and determining the user's demand complexity in combination with the similarity of design schemes of different matching users and the user matching degree between matching users, determining the number of the user's alternative design schemes based on the user's demand complexity, and determining the user's alternative design schemes in combination with the design schemes of different matching users, thereby ensuring the efficiency of design processing.

Description

Technical Field

[0001] The present invention belongs to the technical field of big data, and in particular relates to a whole-house woodworking customization integrated design processing method based on big data. Background Art

[0002] In recent years, with the gradual improvement of living standards, decorative furniture has gradually changed from ready-made furniture to customized furniture designed according to the actual situation of the room, which has greatly improved the space utilization and aesthetics of the room. However, at the same time, due to the large difference between the actual effect and the design effect of customized furniture, it is difficult to guarantee the user experience.

[0003] In order to solve the above technical problems, the invention patent CN201811639651.X "A furniture customization method and customization device" can realize data interaction with the professional design process through the rich types of human-computer interaction interfaces provided by the interactive user interface through the feedback and experience of customers at different customization stages, thereby greatly improving the user experience. However, at the same time, there are the following technical problems:

[0004] Since customers cannot express their needs accurately and completely, multiple revisions or even redesigns are inevitable during the actual design process. This not only makes it difficult to meet the requirements for the design efficiency of the whole house woodwork, but also increases the workload of designers.

[0005] In response to the above technical problems, the present invention provides an integrated design and processing method for whole-house wood customization based on big data. Summary of the invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, a method for integrated design and processing of whole-house woodworking customization based on big data is provided.

[0008] A method for integrated design and processing of whole-house woodworking customization based on big data, characterized by specifically including:

[0009] S1 determines the user's demand keywords based on the user's description data, and determines the user matching degree between the user and different historical users and the matching user through the user's demand keywords, apartment data and location;

[0010] S2 determines the similarity of the design schemes of different matching users based on the similarity of the design schemes of different matching users, and determines the matching design scheme and the matching degree between the matching design scheme and the user's scheme according to the similarity of the design schemes of different matching users, and when the scheme matching degree does not meet the requirement, proceeds to the next step;

[0011] S3: obtaining the user's demand keywords and apartment data, and determining the complexity of the user's demand by combining the similarities of design solutions of different matching users and the user matching degree between the matching users and the user;

[0012] S4 determines the number of alternative design solutions for the user based on the complexity of the user's needs, and determines the number of alternative design solutions for the user in combination with different design solutions that match the user.

[0013] The beneficial effects of the present invention are:

[0014] 1. The user's matching degree with different historical users and the determination of matching users are carried out through the user's demand keywords, apartment data and the region where the user is located. Not only is the difference in user matching degree between the user and historical users due to the difference in demand keywords considered alone, but also the difference in lighting caused by the difference in the user's apartment data and the difference in the region is further considered, thereby achieving an accurate assessment of the user's matching users and laying the foundation for further combining historical data to output alternative design solutions.

[0015] 2. Determine the number of alternative design schemes for the user based on the complexity of the user's needs, and determine the user's alternative design schemes in combination with different design schemes that match the user, thereby achieving the determination of multiple alternative design schemes from the perspective of the complexity of the user's needs, improving the probability of satisfaction with the user's design scheme, and avoiding the occurrence of time-consuming technical problems due to repeated design.

[0016] A further technical solution is that the user's demand keywords are determined based on the user's description data and a matching result of a preset keyword library.

[0017] A further technical solution is that when the user matching degree between the historical user and the user is greater than a preset matching degree, the historical user is determined to be a matching user.

[0018] A further technical solution is to use the design solution of the matching user that has the greatest matching degree as the matching design solution.

[0019] A further technical solution is that the value range of the complexity of the user's demand is between 0 and 1, wherein the higher the complexity of the user's demand is, the higher the complexity of the user's demand is determined to be.

[0020] A further technical solution is that the method for determining the number of the user's alternative design solutions is:

[0021] The number of preset design solutions corresponding to the complexity of the user's needs is determined based on the complexity of the user's needs, and the number of alternative design solutions for the user is determined according to the number of preset design solutions.

[0022] A further technical solution is to determine the user's alternative design solutions, specifically including:

[0023] Determining the comprehensive deviation amounts of different matching users by the similarities between different matching users and the design solutions of the user, the similarities between the design solutions of the matching users and other matching users, and the user matching between the matching users and the user;

[0024] The user's alternative design solutions are determined based on the comprehensive deviation amount and the number of alternative design solutions.

[0025] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0027] Figure 1 It is a flowchart of a whole-house woodworking customization integrated design processing method based on big data;

[0028] Figure 2 is a flow chart of a method for determining user matching degree;

[0029] Figure 3 It is a flow chart of a method for determining a matching design solution. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0031] Example 1

[0032] To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, a method for integrated design and processing of whole-house woodworking customization based on big data is provided, which is characterized by specifically including:

[0033] S1 determines the user's demand keywords based on the user's description data, and determines the user matching degree between the user and different historical users and the matching user through the user's demand keywords, apartment data and location;

[0034] Specifically, the user's demand keywords are determined based on the user's description data and the matching results of a preset keyword library.

[0035] In one embodiment, Figure 2 As shown, the method for determining the user matching degree is:

[0036] Determining the degree of matching between the needs of the user and the historical users based on the matching results of the needs keywords of the user and the needs keywords of the historical users;

[0037] Determine the user's floor plan according to the user's floor plan data, and determine the degree of matching between the user's floor plan and the floor plans of historical users based on the similarity between the user's floor plan and the floor plans of historical users;

[0038] Determine the location matching degree between the user and the historical user based on the location of the user and the location of the historical user;

[0039] The user matching degree between the user and the historical users is determined through the location matching degree, the apartment type matching degree and the demand matching degree.

[0040] Further, when the user matching degree between the historical user and the user is greater than a preset matching degree, the historical user is determined to be a matching user.

[0041] In another embodiment, the method for determining the user matching degree is:

[0042] Determine the degree of matching between the user's demand keywords and the historical user's demand keywords based on the matching result of the user's demand keywords and the historical user's demand keywords, and judge whether the degree of matching between the user's demand and the historical user meets the requirement. If so, proceed to the next step; if not, determine that the historical user does not belong to the matching user;

[0043] Determine the matching degree interval of the user's demand matching degree with the historical user through the demand matching degree, and determine the preset apartment type matching degree threshold and the preset location matching degree threshold between the user and the historical user according to the matching degree interval;

[0044] Determine the user's floor plan according to the user's floor plan data, and determine the degree of matching between the user's floor plan and the floor plans of historical users based on the similarity between the user's floor plan and the floor plans of historical users, and judge whether the floor plan matching degree is greater than a preset floor plan matching degree threshold. If so, proceed to the next step; if not, determine that the historical user is not a matching user;

[0045] Determine the location matching degree between the user and the historical user by the location of the user and the location of the historical user, and judge whether the location matching degree is greater than a preset location matching degree threshold, if so, proceed to the next step, if not, determine that the historical user is not a matching user;

[0046] The user matching degree between the user and the historical users is determined through the location matching degree, the apartment type matching degree and the demand matching degree.

[0047] In another embodiment, the method for determining the user matching degree is:

[0048] S11 determines whether the user and the historical user have matching demand keywords based on the matching results of the user's demand keywords and the historical user's demand keywords. If yes, proceed to the next step. If no, determine that the historical user is not a matching user.

[0049] S12 determines whether the number of the required keywords is greater than the preset number of keywords, if so, proceeds to the next step, if not, proceeds to step S14;

[0050] S13 determines the user's floor plan according to the user's floor plan data, and determines the floor plan matching degree between the user and the historical user based on the similarity between the user's floor plan and the floor plan of the historical user, determines the location matching degree between the user and the historical user according to the user's location and the location of the historical user, and determines the basic condition matching degree between the user and the historical user in combination with the floor plan matching degree, and determines whether the basic condition matching degree meets the requirements. If so, it is determined that the historical user is a matching user, and if not, proceeds to the next step;

[0051] S14 determines the demand matching degree between the user and the historical users based on the matching result of the demand keywords of the user and the demand keywords of the historical users, and determines the user matching degree between the user and the historical users through the basic condition matching degree and the demand matching degree.

[0052] S2 determines the similarity of the design schemes of different matching users based on the similarity of the design schemes of different matching users, and determines the matching design scheme and the matching degree between the matching design scheme and the user's scheme according to the similarity of the design schemes of different matching users, and when the scheme matching degree does not meet the requirement, proceeds to the next step;

[0053] Specifically, the similarity of the design scheme of the matching user is determined according to the image similarity of the custom-made furniture of the design scheme of the matching user.

[0054] In one embodiment, Figure 3 As shown, the method for determining the matching design solution is:

[0055] Determining similar solution users and different solution users of the matching user based on the similarity between the design solutions of the matching user and other matching users;

[0056] Determine the comprehensive similarity of the solutions of the matching users according to the number of the users with similar solutions and the user matching degree between different users with similar solutions and the matching users;

[0057] Determining the comprehensive deviation degree of the schemes of the matched users based on the number of the differentiated scheme users and the user matching degrees between different differentiated scheme users and the matched users;

[0058] The matching degree between the design schemes of different matching users and the schemes of the users is determined by using the comprehensive similarities and comprehensive deviations of the schemes of different matching users, and the matching design scheme is determined based on the scheme matching degree.

[0059] Furthermore, the design scheme of the matching user corresponding to the scheme with the greatest matching degree is taken as the matching design scheme.

[0060] In another embodiment, the method for determining the matching design solution is:

[0061] Determine similar solution users and different solution users of the matching user based on the similarity between the design solutions of the matching user and other matching users, and judge whether the number of similar solution users of the matching user meets the requirement, if yes, proceed to the next step, if no, determine that the design solution of the matching user does not belong to the matching design solution;

[0062] Determine whether the proportion of the number of users with similar solutions to the matching user to the number of all matching users meets the requirement, if so, proceed to the next step, if not, determine that the design solution of the matching user does not belong to the matching design solution;

[0063] Determine the comprehensive similarity of the solutions of the matching users according to the number of the users with similar solutions and the user matching degree between different users with similar solutions and the matching user, and judge whether the comprehensive similarity of the solutions of the matching users meets the requirements, if yes, proceed to the next step, if not, determine that the design solution of the matching user does not belong to the matching design solution;

[0064] Determining the comprehensive deviation degree of the schemes of the matched users based on the number of the differentiated scheme users and the user matching degrees between different differentiated scheme users and the matched users;

[0065] The matching degree between the design schemes of different matching users and the schemes of the users is determined by using the comprehensive similarities and comprehensive deviations of the schemes of different matching users, and the matching design scheme is determined based on the scheme matching degree.

[0066] In another embodiment, the method for determining the matching design solution is:

[0067] Determine similar solution users and different solution users of the matching user based on the similarity between the design solutions of the matching user and other matching users, and judge whether there is a similar solution user of the matching user. If so, proceed to the next step; if not, determine that the design solution of the matching user does not belong to the matching design solution;

[0068] Obtain the number of users with different schemes of the matched user, and determine whether the proportion of the number of users with different schemes of the matched user to the number of all matched users meets the requirement, if so, proceed to the next step, if not, determine that the design scheme of the matched user does not belong to the matching design scheme;

[0069] Obtaining the number of users with different schemes of the matched user and the user matching degree between different users with different schemes and the matched user, and determining the comprehensive deviation degree of the scheme of the matched user in combination with the proportion of the matched user in the number of all matched users, and judging whether the comprehensive deviation degree of the scheme of the matched user meets the requirement, if yes, proceeding to the next step, if no, determining that the design scheme of the matched user does not belong to the matching design scheme;

[0070] The comprehensive similarity of the solutions of the matching users is determined according to the number of users with similar solutions and the user matching degrees between different users with similar solutions and the matching users. The matching degrees of the design solutions of different matching users and the solutions of the users are determined through the comprehensive similarities of the solutions of different matching users and the comprehensive deviations of the solutions, and the matching design solution is determined based on the solution matching degrees.

[0071] S3: obtaining the user's demand keywords and apartment data, and determining the complexity of the user's demand by combining the similarities of design solutions of different matching users and the user matching degree between the matching users and the user;

[0072] In one embodiment, the method for determining the complexity of the user's requirements is:

[0073] Determine the number of rooms and the number of customized furniture for the user based on the user's apartment data, and determine the complexity of the user's basic needs based on the number of the user's demand keywords;

[0074] Determining the comprehensive deviation amounts of different matching users by the similarities between different matching users and the design solutions of the user, the similarities between the design solutions of the matching users and other matching users, and the user matching between the matching users and the user;

[0075] The demand complexity of the user is determined based on the number of matched users, the comprehensive deviations of different matched users, and the basic demand complexity of the user.

[0076] Furthermore, the value range of the complexity of the user's demand is between 0 and 1, wherein the higher the complexity of the user's demand is, the higher the complexity of the user's demand is determined to be.

[0077] In another embodiment, the method for determining the complexity of the user's requirements is:

[0078] Determine the number of rooms and the number of customized furniture for the user based on the apartment data of the user, and judge whether the number of rooms and the number of customized furniture for the user are both within a preset number range. If so, proceed to the next step; if not, determine the complexity of the user's needs based on the preset complexity of needs;

[0079] Obtain the number of the user's demand keywords, and determine whether the number of the user's demand keywords is less than the preset number of keywords. If so, proceed to the next step; if not, determine the user's demand complexity based on the preset demand complexity;

[0080] Obtaining the number of the matched users, determining whether the number of the matched users is greater than a preset number of matched users, if so, proceeding to the next step, if not, determining the user's demand complexity based on a preset demand complexity;

[0081] Determine the comprehensive deviations of different matching users by the similarities between the design solutions of different matching users and the user, the similarities between the design solutions of the matching users and other matching users, and the user matching between the matching users and the user, and judge whether the number of matching users whose comprehensive deviations meet the requirements meets the requirements, if so, proceed to the next step, if not, determine the demand complexity of the user based on the preset demand complexity;

[0082] The demand complexity of the user is determined based on the number of matched users, the comprehensive deviations of different matched users, and the basic demand complexity of the user.

[0083] S4 determines the number of alternative design solutions for the user based on the complexity of the user's needs, and determines the number of alternative design solutions for the user in combination with different design solutions that match the user.

[0084] Specifically, the method for determining the number of the user's alternative design solutions is:

[0085] The number of preset design solutions corresponding to the complexity of the user's needs is determined based on the complexity of the user's needs, and the number of alternative design solutions for the user is determined according to the number of preset design solutions.

[0086] It should be noted that determining the user's alternative design scheme specifically includes:

[0087] Determining the comprehensive deviation amounts of different matching users by the similarities between different matching users and the design solutions of the user, the similarities between the design solutions of the matching users and other matching users, and the user matching between the matching users and the user;

[0088] The user's alternative design solutions are determined based on the comprehensive deviation amount and the number of alternative design solutions.

[0089] Through the above embodiments, the present invention achieves the following beneficial effects:

[0090] 1. The user's matching degree with different historical users and the determination of matching users are carried out through the user's demand keywords, apartment data and the region where the user is located. Not only is the difference in user matching degree between the user and historical users due to the difference in demand keywords considered alone, but also the difference in lighting caused by the difference in the user's apartment data and the difference in the region is further considered, thereby achieving an accurate assessment of the user's matching users and laying the foundation for further combining historical data to output alternative design solutions.

[0091] 2. Determine the number of alternative design schemes for the user based on the complexity of the user's needs, and determine the user's alternative design schemes in combination with different design schemes that match the user, thereby achieving the determination of multiple alternative design schemes from the perspective of the complexity of the user's needs, improving the probability of satisfaction with the user's design scheme, and avoiding the occurrence of time-consuming technical problems due to repeated design.

[0092] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0093] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0094] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A method for integrated design and processing of whole-house woodworking customization based on big data, characterized in that: Specifically include: Determine the user's demand keywords based on the user's description data, and determine the user matching degree between the user and different historical users and the matching user through the user's demand keywords, apartment data and location; Determine the similarity of the design schemes of different matching users by the similarity of the design schemes of different matching users, and determine the matching design scheme and the matching degree between the matching design scheme and the user's scheme according to the similarity of the design schemes of different matching users, and when the scheme matching degree does not meet the requirement, proceed to the next step; Obtain the user's demand keywords and apartment data, and determine the complexity of the user's demand by combining the similarities of design solutions of different matching users and the user matching degree between the matching users and the user; Determine the number of alternative design solutions for the user based on the complexity of the user's needs, and determine the alternative design solutions for the user in combination with different design solutions that match the user; The method for determining the user matching degree is: Determining the degree of matching between the needs of the user and the historical users based on the matching results of the needs keywords of the user and the needs keywords of the historical users; Determine the user's floor plan according to the user's floor plan data, and determine the degree of matching between the user's floor plan and the floor plans of historical users based on the similarity between the user's floor plan and the floor plans of historical users; Determine the location matching degree between the user and the historical user based on the location of the user and the location of the historical user; Determining the user matching degree between the user and the historical users through the location matching degree, the apartment type matching degree and the demand matching degree; When the user matching degree between the historical user and the user is greater than a preset matching degree, the historical user is determined to be a matching user; The method for determining the matching design solution is: Determining similar solution users and different solution users of the matching user based on the similarity between the design solutions of the matching user and other matching users; Determine the comprehensive similarity of the solutions of the matching users according to the number of the users with similar solutions and the user matching degree between different users with similar solutions and the matching users; Determining the comprehensive deviation degree of the schemes of the matched users based on the number of the differentiated scheme users and the user matching degrees between different differentiated scheme users and the matched users; Determine the matching degree between the design solutions of different matching users and the solutions of the users through the comprehensive similarity and comprehensive deviation of the solutions of different matching users, and determine the matching design solution based on the solution matching degree; The design scheme of the matching user with the greatest matching degree is taken as the matching design scheme; Determining the user's alternative design solutions specifically includes: Determine the comprehensive deviations of different matching users by the similarities between different matching users and the design solutions of the user, the similarities between the design solutions of the matching users and other matching users, and the user matching between the matching users and the user; The user's alternative design solutions are determined based on the comprehensive deviation amount and the number of alternative design solutions.

2. The whole-house woodworking customization integrated design processing method based on big data as claimed in claim 1 is characterized in that: The user's demand keywords are determined based on the user's description data and the matching results of the preset keyword library.

3. The whole-house woodworking customization integrated design processing method based on big data as claimed in claim 1 is characterized in that: The similarity of the design scheme of the matching user is determined based on the image similarity of the custom-made furniture of the design scheme of the matching user.

4. The whole-house woodworking customization integrated design processing method based on big data as claimed in claim 1 is characterized in that: The method for determining the number of the user's alternative design solutions is: The number of preset design solutions corresponding to the complexity of the user's needs is determined based on the complexity of the user's needs, and the number of alternative design solutions for the user is determined according to the number of preset design solutions.

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