CN109816489A - Recommend and dispense the algorithm of finishing material by process intelligent accurate - Google Patents
Recommend and dispense the algorithm of finishing material by process intelligent accurate Download PDFInfo
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- CN109816489A CN109816489A CN201910078059.5A CN201910078059A CN109816489A CN 109816489 A CN109816489 A CN 109816489A CN 201910078059 A CN201910078059 A CN 201910078059A CN 109816489 A CN109816489 A CN 109816489A
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Abstract
The present invention relates to Computer Applied Technology algorithmic technique fields, and disclose the algorithm for recommending and dispensing finishing material by process intelligent accurate, the following steps are included: owner issues the primary demand that oneself needs to fit up in systems, the elements such as the regional location of oneself, finishing anticipated price, decoration style, expected house type and finishing area are carried out publicity and wait designer to be its Decoration Design scheme.The invention proposes the algorithms for recommending and dispensing finishing material by process intelligent accurate, three aspects such as situations such as material production of the demand of owner, the design conditions of designer and businessman is with inventory and dispatching can be merged, finishing material progress considering in all directions is screened and pick out most suitable finishing material and is distributed to owner, the selection situation of owner can be merged, the behavioral data of selection, the behavior of the ripe data of the behavior of automatic tracing user and current change recommendation results, learns and analyzes preference and requirement of the owner to finishing material.
Description
Technical field
The present invention relates to Computer Applied Technology algorithmic technique field, specially recommends by process intelligent accurate and dispense dress
Repair the algorithm of material.
Background technique
Recommender system is the information or a kind of system in kind for recommending user referred to user may like, now such as
The epoch of modern Internet technology rapid development targetedly recommend its interested and meet the product of demand, for enterprise to user
Industry and the value of user are self-evident, are that find oneself by the recommendation of system interested more than 60% Netflix user
Video and film, and QQ watching focus is then to like, do not like and shield to obtain the emerging of user by providing the user with feedback system
Interesting model checks behavior and recommends relevant watching focus content to user, makes every effort to the thing recommended more in conjunction with the history of user
Add and meets user preference.
Recommender system relies primarily on proposed algorithm to user's progress recommendation to realize, proposed algorithm is entire recommendation system
Most crucial and most critical part in system, performance determines the quality of recommender system, it is presently recommended that method mainly includes being based on
Commending contents, collaborative filtering recommending are recommended based on correlation rule, based on effectiveness recommendation, knowledge based recommendation and combined recommendation, though
So above-mentioned recommended method has been widely applied, but is still faced with many problems, such as in the selection and dispatching of finishing material
On, there is very big problem in accuracy and personalized remain unchanged, owner remains by designer or gone according to the wish of oneself
Selection purchase material, existing algorithm is low with dispatching personalized recommendation degree to the purchase of finishing material and recommends flexibility difference right
Owner recommends and how to recommend new material to owner etc., still to be improved in the accuracy of recommendation.
Summary of the invention
(1) the technical issues of solving
In view of the deficiencies of the prior art, recommend by process intelligent accurate the present invention provides a kind of and dispense finishing material
Algorithm, have recommend accuracy height and flexibility it is high the advantages that, solve recommend accuracy it is low and recommend flexibility difference ask
Topic.
(2) technical solution
To realize above-mentioned recommendation accuracy height and the high purpose of flexibility, the invention provides the following technical scheme: pressing process
Intelligent accurate is recommended and dispenses the algorithm of finishing material, comprising the following steps:
1) owner issues the primary demand that oneself needs to fit up in systems, by the regional location of oneself, the pre- forward price of finishing
The elements such as lattice, decoration style, expected house type and finishing area carry out publicity and wait designer to be its Decoration Design scheme.
2) design designs decorating scheme according to the decoration requirements of owner for its amount of visiting room and according to requirements of the owner, considers room
The finishing feasibility in room, then carry out simply fitting up layout, consider to fit up existing multiple problems, one for determining finishing is big
Cause direction, and the decoration style in house selected, in the way of requirements of the owner, fit up the house of oneself, owner with set
The meter abundant ditch of teacher have friendly relations finishing feasibility after, provide oneself for the finishing opinion in house, the habit of requirement, inhabitation to house
Used and personal interest etc. carries out considering and starting design scheme for synthesis.
3) after designer designs decorating scheme, by with owner to determining final finishing side after being discussed in detail of details
Case, and determine the working hour technique in final house.
4) decorating scheme that system gets designer's upload automatically first includes working hour process program, then obtains owner
Behavior use habit data, according to big data sort out come and the external third party's data relevant to business of joint do it is qualitative
Quantitative management is analyzed and carried out, the selection of design style in finishing, and purchased material quantity, demand are mainly included in
With the data such as gender, age, occupation, income and the city at place of owner, the data of socialization relationship can be by introducing
The relevant third party's data of business obtain, and the third party's data that can be introduced mainly include the consumption preferences of finishing material, material life
Data, Unionpay's data and credit data etc. are produced, then according to the proprietor's behavior use habit data got, determines each material
Using temperature score value, and original material is picked out from active material, be finally with the first recommendation dimension and the second recommendation dimension
Basic reference, suggesting material is to owner.
A) determine that finishing material first recommends dimension according to working hour technique: after the pre- suggesting material of screening, throughput
Change technology difficulty present in material and actual life, working hour requires, and determines finishing material for the sequence of material installation
The first of material recommends dimension, to further choose the material for being most suitable for recommending owner, it is ensured that the accuracy of recommendation increases and uses
Family viscosity.
B) the second recommendation dimension that the behavioral data according to owner in internet determines: the second recommendation latitude is specially owner
Internet behavioral data, quantifiable normalization operation is converted into the internet behavioral data of owner, to obtain pre- recommend
Second fractional value of product.
5) by the recommendation of algorithm, the material of owner's finishing is arranged in working hour technique and is aggregated to form a material
Material inventory simultaneously be pushed to owner, owner after receiving recommendation results, can by the bill of materials carry out finishing material adjustment from
And form oneself most perfectly contented finishing material inventory.
6) after determining the finishing material inventory recommended by algorithm in owner, the material that algorithm is determined automatically according to owner is clear
It is single, and the order dispatching to material order is carried out according to each element, selected bill of materials result is automatically formed into order, intelligence
It is sent to producer and directly orders production, then got home by direct deal dispatching.
(3) beneficial effect
Compared with prior art, the present invention provides a kind of calculations recommended by process intelligent accurate and dispense finishing material
Method, have it is following the utility model has the advantages that
This is recommended by process intelligent accurate and dispenses the algorithm of finishing material, compared with prior art, has the advantage that
Situations such as merging the production of demand, the design conditions of designer and the material of businessman, inventory and the dispatching of owner etc.
Three aspects carry out considering and screen and pick out most suitable finishing material and be distributed to owner in all directions to finishing material, melt
The selection situation of owner is closed, the behavioral data of selection and currently changes recommendation results at the ripe data of the behavior of automatic tracing user
Behavior, deep learning and automatically according to working hour and material market data analysis owner the preference to finishing material with
And require, so as to according to the preference real-time update recommendation results of owner, while algorithm of the invention considers consumer products
Order and product inventory factor, while so that recommendation results is enabled client satisfaction, it is ensured that owner can order material in time, this
Inventive embodiments can go out desired product according to the behavioral data preliminary screening in working hour of owner's house decoration and selection material, and from
Different evaluation dimensions and different businessman's dimensions carry out comprehensive normalization scoring to pre- recommended products and recommend, and will comment
The valence score highest and Products Show for meeting construction working hour and requirements of the owner is to owner, guarantees that recommended product meets owner and wants
It asks, to improve business profession degree and owner's satisfaction.
Specific embodiment
Below in conjunction with the embodiment of the present invention, technical solution in the embodiment of the present invention is clearly and completely retouched
It states, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Based on the present invention
In embodiment, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
Recommend and dispense the algorithm of finishing material by process intelligent accurate, the algorithm the following steps are included:
1) owner issues the primary demand that oneself needs to fit up in systems, by the regional location of oneself, the pre- forward price of finishing
The elements such as lattice, decoration style, expected house type and finishing area carry out publicity and wait designer to be its Decoration Design scheme.
2) design designs decorating scheme according to the decoration requirements of owner for its amount of visiting room and according to requirements of the owner, considers room
The finishing feasibility in room, then carry out simply fitting up layout, consider to fit up existing multiple problems, one for determining finishing is big
Cause direction, and the decoration style in house selected, in the way of requirements of the owner, fit up the house of oneself, owner with set
The meter abundant ditch of teacher have friendly relations finishing feasibility after, provide oneself for the finishing opinion in house, the habit of requirement, inhabitation to house
Used and personal interest etc. carries out considering and starting design scheme for synthesis.
3) after designer designs decorating scheme, by with owner to determining final finishing side after being discussed in detail of details
Case, and determine the working hour technique in final house, by the temperature situation of material can the rough Behavior preference for understanding owner,
Consumption habit and producer's condition of production carry out quantitative analysis scoring according to these essential informations come the material to magnanimity, with certain
Temperature fractional value do screening conditions, the product of limited quantity is filtered out from the product of magnanimity as pre- recommended products, thus
Ensure that pre- recommended products substantially conforms to user interest and preference.
4) decorating scheme that system gets designer's upload automatically first includes working hour process program, then obtains owner
Behavior use habit data, according to big data sort out come and the external third party's data relevant to business of joint do it is qualitative
Quantitative management is analyzed and carried out, the selection of design style in finishing, and purchased material quantity, demand are mainly included in
With the data such as gender, age, occupation, income and the city at place of owner, the data of socialization relationship can be by introducing
The relevant third party's data of business obtain, and the third party's data that can be introduced mainly include the consumption preferences of finishing material, material life
Data, Unionpay's data and credit data etc. are produced, then according to the proprietor's behavior use habit data got, determines each material
Using temperature score value, and original material is picked out from active material, be finally with the first recommendation dimension and the second recommendation dimension
Basic reference, suggesting material in specific implementation, carry out arrangement recommendation to the first recommendation dimension and second point of recommendation dimension to owner
To determine the finishing material recommended in advance, and the preference of owner is surrounded, further considers factor when material and upfitter, thus
User is precisely recommended in realization.
A) determine that finishing material first recommends dimension according to working hour technique: after the pre- suggesting material of screening, throughput
Change technology difficulty present in material and actual life, working hour requires, and determines finishing material for the sequence of material installation
The first of material recommends dimension, to further choose the material for being most suitable for recommending owner, it is ensured that the accuracy of recommendation increases and uses
Family viscosity, technology difficulty refer to decoration construction in the process for the construction is simple of material to a complicated degree, in constructor
Under member's rank and class, including construction level and the identical situation of production technique, for certain materials during installation
Technology difficulty degree, working hour requires to refer to construction time of a certain procedure in the construction process, and it includes for material
, there is highly important influence in the case where service condition, construction technology for the first recommendation dimension fractional value, can promote material recommendation
Accuracy, material erection sequence refers to fixed working hour process program in decorating scheme, and the material in finishing is carried out
The sequence of installation.
B) the second recommendation dimension that the behavioral data according to owner in internet determines: the second recommendation latitude is specially owner
Internet behavioral data, quantifiable normalization operation is converted into the internet behavioral data of owner, to obtain pre- recommend
Second fractional value of product, it should be noted that the behavior of the internet each time event of user all can be considered an internet row
For data, the essential requirement of user's heart is reflected invariably, including page browsing, click, collection, shopping, search, give a mark and comment
By etc., therefore the internet behavioral data for tracking owner can react user to the preference of product, it is easier to meet owner instantly
Demand the row recommended or ordered furthermore was carried out to product in view of user thus more accurately to owner's recommended products
For this can more react the selection preference of owner than the behavioral datas such as clicking and browsing, and push away in carry out pre- recommended products second
When recommending dimension, number and the preset weighted value of product subscription history is recommended to want higher to owner is assigned.
5) by the recommendation of algorithm, the material of owner's finishing is arranged in working hour technique and is aggregated to form a material
Material inventory simultaneously be pushed to owner, owner after receiving recommendation results, can by the bill of materials carry out finishing material adjustment from
And form oneself most perfectly contented finishing material inventory.
6) after determining the finishing material inventory recommended by algorithm in owner, the material that algorithm is determined automatically according to owner is clear
It is single, and the order dispatching to material order is carried out according to each element, selected bill of materials result is automatically formed into order, intelligence
It is sent to producer and directly orders production, then got home by direct deal dispatching.
In conclusion the present invention is recommended by process intelligent accurate and dispensed the algorithm of finishing material, the need of owner can be merged
Ask, the production of the material of the design conditions of designer and businessman, inventory and three aspects such as situations such as dispatching, to finishing material into
Row considering in all directions screens and picks out most suitable finishing material and be distributed to owner, can merge the selection situation of owner, select
The behavioral data selected, the behavior of the ripe data of the behavior of automatic tracing user and current change recommendation results, deep learning and from
Dynamic preference and requirement according to working hour and material market data analysis owner to finishing material, so as to basis
The preference real-time update recommendation results of owner, while algorithm of the invention considers the order and product inventory of consumer products
Factor, while making recommendation results enable client satisfaction, it is ensured that owner can order material in time, and the embodiment of the present invention can be according to owner
The working hour of house decoration and the behavioral data preliminary screening of selection material go out desired product, and from different evaluation dimensions and not
Same businessman's dimension carries out comprehensive normalization scoring to pre- recommended products and recommends, and by evaluation score highest and meets construction
The Products Show of working hour and requirements of the owner guarantees that recommended product meets owner's requirement to owner, to improve business profession
Degree and owner's satisfaction.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (1)
1. recommending and dispensing the algorithm of finishing material by process intelligent accurate, which comprises the following steps:
1) owner issues the primary demand that oneself needs to fit up in systems, by the regional location of oneself, finishing anticipated price, dress
The elements such as style, expected house type and finishing area are repaired to carry out publicity and wait designer to be its Decoration Design scheme.
2) design designs decorating scheme according to the decoration requirements of owner for its amount of visiting room and according to requirements of the owner, considers house
Feasibility is fitted up, then carries out simply fitting up layout, considers to fit up existing multiple problems, one for determining finishing is substantially square
To, and the decoration style in house is selected, in the way of requirements of the owner, fit up the house of oneself, owner and designer
Abundant ditch have friendly relations finishing feasibility after, provide oneself for the finishing opinion in house, the habit of requirement, inhabitation to house with
And personal interest etc. carries out considering and starting design scheme for synthesis.
3) after designer designs decorating scheme, by with owner to determining final decorating scheme after being discussed in detail of details,
And determine the working hour technique in final house.
4) decorating scheme that system gets designer's upload automatically first includes working hour process program, then obtains the row of owner
For use habit data, is sorted out come according to big data and combine external third party's data relevant to business and do qualitative analysis
And quantitative management is carried out, it is mainly included in the selection of design style in finishing, and purchased material quantity, demand and industry
The data such as main gender, age, occupation, income and the city at place, the data of socialization relationship can be by the business that introduce
Relevant third party's data obtain, and the third party's data that can be introduced mainly include the consumption preferences of finishing material, material production number
According to, Unionpay's data and credit data etc., then according to the proprietor's behavior use habit data got, the use of each material is determined
Temperature score value, and original material is picked out from active material, it is basic for finally recommending dimension and the second recommendation dimension with first
With reference to suggesting material is to owner.
A) determine that finishing material first recommends dimension according to working hour technique: after the pre- suggesting material of screening, by quantifying material
Technology difficulty present in material and actual life and working hour require, and determine finishing material for the sequence of material installation
First recommends dimension, to further choose the material for being most suitable for recommending owner, it is ensured that it is glutinous to increase user for the accuracy of recommendation
Degree.
B) the second recommendation dimension that the behavioral data according to owner in internet determines: the second recommendation latitude is specially the mutual of owner
Networking behavioral data, is converted into quantifiable normalization operation to the internet behavioral data of owner, to obtain pre- recommended products
The second fractional value.
5) by the recommendation of algorithm, the material of owner's finishing is arranged in working hour technique and to be aggregated to form a material clear
List is simultaneously pushed to owner, and owner, can be by carrying out the adjustment of finishing material to the bill of materials to shape after receiving recommendation results
At oneself most perfectly contented finishing material inventory.
6) after determining the finishing material inventory recommended by algorithm in owner, the bill of materials that algorithm is determined automatically according to owner, and
The order dispatching to material order is carried out according to each element, selected bill of materials result is automatically formed into order, intelligence is sent
Production is directly ordered to producer, is then got home by direct deal dispatching.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201910078059.5A CN109816489A (en) | 2019-01-28 | 2019-01-28 | Recommend and dispense the algorithm of finishing material by process intelligent accurate |
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| CN201910078059.5A CN109816489A (en) | 2019-01-28 | 2019-01-28 | Recommend and dispense the algorithm of finishing material by process intelligent accurate |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110490691A (en) * | 2019-07-24 | 2019-11-22 | 深圳市梦想家联盟科技有限公司 | Information recommendation method, device, computer equipment and storage medium |
| CN112631187A (en) * | 2020-12-28 | 2021-04-09 | 江苏金迪木业股份有限公司 | Customized home decoration monitoring and management system based on Internet of things and artificial intelligence |
| CN117371100A (en) * | 2023-10-19 | 2024-01-09 | 深圳市伊派室内设计有限公司 | Intelligent generation method and system for indoor decoration scheme based on model structure |
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| CN1950823A (en) * | 2004-03-09 | 2007-04-18 | 罗尔公司 | Systems, methods and computer program products for implementing processes relating to retail sales |
| CN106651678A (en) * | 2016-12-16 | 2017-05-10 | 北京家装云网络科技有限公司 | Novel home decoration supervision process management method and system |
| US20170277778A1 (en) * | 2016-03-25 | 2017-09-28 | Maruthi Siva P Cherukuri | Personalized guidance and recommendation based on multi-variable user attributes and multi-dimensional schema |
| CN109213771A (en) * | 2018-06-28 | 2019-01-15 | 深圳市彬讯科技有限公司 | Update the method and apparatus of portrait label |
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN1950823A (en) * | 2004-03-09 | 2007-04-18 | 罗尔公司 | Systems, methods and computer program products for implementing processes relating to retail sales |
| US20170277778A1 (en) * | 2016-03-25 | 2017-09-28 | Maruthi Siva P Cherukuri | Personalized guidance and recommendation based on multi-variable user attributes and multi-dimensional schema |
| CN106651678A (en) * | 2016-12-16 | 2017-05-10 | 北京家装云网络科技有限公司 | Novel home decoration supervision process management method and system |
| CN109213771A (en) * | 2018-06-28 | 2019-01-15 | 深圳市彬讯科技有限公司 | Update the method and apparatus of portrait label |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110490691A (en) * | 2019-07-24 | 2019-11-22 | 深圳市梦想家联盟科技有限公司 | Information recommendation method, device, computer equipment and storage medium |
| CN112631187A (en) * | 2020-12-28 | 2021-04-09 | 江苏金迪木业股份有限公司 | Customized home decoration monitoring and management system based on Internet of things and artificial intelligence |
| CN117371100A (en) * | 2023-10-19 | 2024-01-09 | 深圳市伊派室内设计有限公司 | Intelligent generation method and system for indoor decoration scheme based on model structure |
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Application publication date: 20190528 |