CN113450190A - Intelligent decoration requirement matching and order pushing system and method based on big data - Google Patents
Intelligent decoration requirement matching and order pushing system and method based on big data Download PDFInfo
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Abstract
The invention discloses an intelligent decoration requirement matching and order pushing system and method based on big data, and relates to the technical field of big data intelligent application. The system comprises an intelligent matching list pushing system and a server side; the intelligent matching and bill pushing system comprises a demand entry module, a dynamic dimension integral marking control module, an intelligent matching and bill pushing strategy control module and a bill pushing control module; the service end comprises a user demand preference dimension library, an industry process dimension library and a provider service and quality dimension library; the method comprises a server industry standard data dimension library mechanism and a dynamic dimension library integral marking control mechanism. The system and the method construct a standard data dimension library based on a process, users and service providers, provide a dynamic integral marking algorithm matched with the standard data dimension library, realize the optimal matching of the requirements and the services through an intelligent requirement matching scheduling strategy, and greatly improve the matching efficiency of the effective requirements and the services and the user experience.
Description
Technical Field
The invention belongs to the technical field of big data intelligent application, and particularly relates to an intelligent decoration demand matching and order pushing system and method based on big data.
Background
At present, the mainstream decoration industry in the market mainly adopts a manual mode to solve the matching deduction between the user decoration requirements and the service providers, namely, a user with decoration requirements submits decoration requirement information and a contact mode, a customer service manually contacts the user to communicate the core decoration appeal of the user, after recording, the service providers nearby are selected in a manual screening mode, and relevant information is fed back to the user and the service providers through two lines, so that the matching between the user decoration requirements and the service providers is formed. The method only solves the problem of primary information difference matching, and has the matching limitation of a single service provider.
In the traditional mode, from the matching mode of demand and service, only manual communication information of customer service can be relied on, so that the efficiency is low, and the communication cost is high. Due to the fact that the complexity of the process and the flow of the decoration industry is high, knowledge of the user on relevant information is generally insufficient, and a large amount of information difference exists between the user and a service provider. The user cannot accurately express the core decoration appeal of the user, high-probability demand supplement and change can occur in the service execution process of the service provider, the experience between the user and the service provider is reduced, and the communication cost of the two parties is also improved.
From the aspect of operation cost, the matching strategy needs a large number of customer service personnel to perform information processing, and the customer service personnel perform matching and recommendation of service providers through subjective personal judgment, so that certain matching errors can be caused, the operation cost is high, the quality is uneven, and the user experience and the service quality cannot be guaranteed.
In addition, the user may repeatedly submit decoration requirements, and the duplication elimination operation of related information is difficult to be performed by a traditional manual processing mode, so that multiple service providers repeatedly contact the user, and troubles are caused to the user.
Disclosure of Invention
The invention provides an intelligent decoration requirement matching and order pushing system and method based on big data, and solves the problems.
In order to solve the technical problems, the invention is realized by the following technical scheme:
the invention discloses an intelligent decoration requirement matching and bill pushing system based on big data, which comprises an intelligent matching and bill pushing system and a server side;
the intelligent matching and bill pushing system comprises a demand entry module, a dynamic dimension integral marking control module, an intelligent matching and bill pushing strategy control module and a bill pushing control module;
the service end comprises a user demand preference dimension library, an industry process dimension library and a provider service and quality dimension library;
the demand entry module acquires demand information of a decoration user through interface interaction and enters the demand information into the system; the dynamic dimension integral marking control module is used for interacting the requirement information of the decoration user acquired by the requirement information inlet module with a user requirement preference dimension library, and performing data analysis and classification according to the requirement information and preference information submitted by the decoration user; the bill pushing control module is used for pushing a bill and receiving the bill by a service provider; the intelligent matching and order pushing strategy control module is used for realizing the interaction between the order pushing module and a user demand preference dimension library, an industry process dimension library and a provider service and quality dimension library;
the user demand preference dimension library is internally provided with a user demand basic information dimension and a user preference information dimension; industry process dimension information is stored in the industry process dimension library; the service and quality dimension library of the provider is internally provided with service providing basic dimension and service quality dimension information.
Further, the user demand basic information dimensionality comprises information of a city, a position, a house area, a house type, a space structure and a family structure; the user preference information dimensionality comprises decoration style preference, budget preference, building material brand preference, user process preference, designer preference and case preference.
Further, the industry process dimension information comprises plane layout design process, wall dismantling and modifying process, hydropower modification process, woodworking process, muddy water paint process, ceramic tile floor process, kitchen and bathroom ceiling wall process, cabinet process, door and window process, hardware lamp process and soft-mounting process dimension information.
Further, the service providing basic dimension and service quality dimension information comprises store information, store position information, service information, activity information, store comment information, service quality information, store popularity information, service range and process information.
A big data-based method for matching a bill pushing system with intelligent decoration requirements comprises a server industry standard data dimension library mechanism, a dynamic dimension library integral marking control mechanism, an intelligent matching and bill pushing strategy control mechanism and a matching bill pushing strategy failure and service provider refused bill retry recovery mechanism;
the server industry standard data dimension library mechanism is used for interacting a dynamic dimension integral marking control module in the intelligent matching and order-pushing system with an intelligent matching and order-pushing strategy control module;
the dynamic dimension library integral marking control mechanism is used for interacting a decoration user demand information inlet module and a user demand preference dimension library, and performing data analysis and classification according to demand information and preference information submitted by a user, and comprises a basic dimension library integral mechanism and a preference clustering completion strategy; after a basic dimension library integral mechanism and a preference clustering completion strategy mechanism, storing an obtained user core demand dimension result table and an associated integral result table for an intelligent matching and order pushing strategy control mechanism;
the intelligent matching and pushing strategy control mechanism relates to the interaction between a pushing control module and a user demand preference dimension library, an industry process flow dimension library and a provider service and quality dimension library, and matches process processes and service providers according to a user core demand dimension result table and an associated integral result table, wherein the used data comprises all dimensions of the process dimension library and the provider service and quality dimension library, and the contained intelligent scheduling strategies comprise a core demand priority strategy, a high service quality priority strategy and a comprehensive balance matching degree priority strategy; when a decoration user submits decoration requirements, a single strategy or a comprehensive strategy mechanism is selected independently; if the decoration user does not select the strategy, selecting one of the three single strategies to carry out monotonicity pushing;
the matching push policy failure and service provider refusal list retry recovery mechanism is specifically that after the service provider solves the problem of receiving push information, the intelligent scheduling module can automatically recover the mechanism, recalculate according to the original matching policy, perform storage and update operation on a new policy matching result, and execute push operation; when the matching strategy pushing strategy is invalid and the service provider sets strict limits on the service range and style, the user requirement cannot be normally matched with the proper service provider, if the situation occurs, an automatic informing mechanism is triggered, the user service personnel is informed through a short message and platform message mechanism, and the user requirement and the service provider information are verified and processed by the service personnel;
and the interaction between the dynamic dimension library integral marking control module and the intelligent matching and list pushing strategy control module and the interaction between each dimension library and the list pushing control module in the server side are unified by adopting a user-defined message format.
Further, the base dimension library integration mechanism: matching the information of a user demand dimension library according to the basic information of the user, marking the scores, and calculating the scores according to the number of the subdivision dimensions and the matching priority; the single-dimensional complete matching records the basic demand weight proportion of 1 point, the single-dimensional partial matching records the basic demand weight proportion of 0.5 point, and the single-dimensional partial matching records the basic demand weight proportion of 0 point; wherein the weight proportion of the basic demand is the average value of similar type houses in the same city in the latest month;
the preference clustering completion strategy is as follows: matching information of a user preference dimension library according to the user preference dimension information, performing integral marking, and performing score calculation according to the number of subdivided dimensions and the matching priority; the single-dimensional complete matching records are divided into 1 mark and preference weight proportion, the single-dimensional part matching records are divided into 0.5 mark and preference weight proportion, and the single-dimensional part can not be matched with the records of 0 mark; according to the preference cases of the user, identifying the style and decoration process of the cases through case clustering analysis, and performing score accumulation according to the matching degree percentage x 1; and for dimension information which cannot be provided by the user, performing score dimension calculation according to preference settings of users of the same type in the platform database, and labeling.
Further, the core requirement prioritization policy: according to core requirement indexes and preferences of users, preferentially ensuring the service provider with the highest core requirement degree to be matched, wherein the core requirements are core requirements of the users and the process range; specifically, the intelligent matching and list pushing strategy control module automatically receives a dynamic dimension library integral mark control result, analyzes an instruction, and executes the following processes:
s01, acquiring user demand dimensions and dimension integrals in the instruction;
s02, loading a process standard library and providing a standard library by a service provider;
s03, excluding the service merchant provider who suspends the order receiving;
s04, eliminating relevant service providers with unmatched user preferences; the method comprises the steps of mismatch of decoration style, mismatch of budget, match of service and brand part and the like;
s05, matching scores of the main demand dimensions, and calculating scores of the rest service providers;
s06, circularly executing the steps through the S05 to realize the point value accumulation calculation of the service provider;
and S07, storing and recording the service provider list with the highest score, and pushing the first three digits to perform a list pushing module.
Further, the high quality of service prioritization policy: according to the core requirement index and preference of the user, the service provider with the highest service quality is preferentially ensured to be matched, the intelligent matching and list pushing strategy control module automatically receives the control result of the integral mark of the dynamic dimension library, analyzes the instruction and executes the following processes:
p01, acquiring user demand dimensions and dimension integrals in the instruction;
p02, loading a process standard library and providing a standard library by a service provider;
p03, service merchant provider excluding pickup suspension;
p04, excluding service providers with service provider quality score values which do not meet the user requirements; the method comprises the steps that the service provider comprehensive score does not reach the standard, the same city ranking does not reach the standard, the service heat score does not reach the standard and the like, and score calculation is carried out on the rest service providers;
p05, matching scores of the main matching demand dimensions, and calculating scores of the rest service providers;
p06, the score of the service provider is calculated in a circulating way through the P05 step;
and P07, storing and recording the service provider list with the highest score, and pushing the first three digits to perform a list pushing module.
Further, the comprehensive balanced matching priority strategy is as follows: according to the core requirement index and preference of the user, preferentially ensuring the service provider with the highest core requirement degree to be matched, wherein the core requirement degree is the core requirement of the user and the process range; the intelligent matching and list pushing strategy control module automatically receives the integral marking control result of the dynamic dimension library, analyzes the instruction and executes the following procedures:
t01, acquiring user demand dimensions and dimension integrals in the instruction;
t02, loading a process standard library and providing a standard library by a service provider;
t03, service merchant provider for excluding suspension of order pickup;
t04, matching scores of the matching demand dimensions, and calculating scores of the rest service providers;
t05, circularly executing through a T04 step mode, and realizing the score accumulation calculation of a service provider;
and T06, storing and recording the service provider list with the highest score, and pushing the first three digits to perform a list pushing module.
Further, the customized message format is specifically as follows:
the method comprises the following fields: id; type; params; status; the id represents the number of the data transmission instruction and is used for interaction among the tracing modules, and the id information comprises a user number, a user demand number and sectional information, so that the fault tolerance of the demand dimension is provided; the Type represents the Type of a data transmission instruction, supports three types of a heartbeat instruction, a system interaction instruction and a list pushing execution instruction; the Params represents specific data information of the instruction and is a set stored in a key value pair mode, the key attribute is a dimension number, and the value attribute comprises a score, a weight, a reason, time, a sequence, a strategy and the like; the Status indicates instruction information and has the modes of immediate effect, delayed effect, timed effect and the like;
the field names corresponding to the fields are respectively: numbering ID; a dimension type; instruction parameters, stored by using a key value pair mode; an instruction state;
the formats corresponding to the fields are: a character string; a character string; gathering; a number;
the descriptions corresponding to the fields are: an instruction number; a system interaction instruction, a heartbeat instruction and a list pushing execution instruction are carried out; bond: dimension, value: scores, weights, reasons, time, order, policies, etc.; immediate effect, delayed effect and timed effect.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention mainly aims to solve the problems of low matching rate and low conversion rate of user requirements and service providers in the decoration industry; matching the user requirements, the services provided by the service providers and the decoration processes and technologies based on a dimension standard library of three aspects of decoration processes and technologies, user requirements and preferences and service and quality of the service providers to form a multi-dimensional point marking result table, configuring the table through a dynamic intelligent algorithm, and performing order pushing operation on the service providers after optimal planning is performed; the algorithm strategy can provide recommendation of multiple service providers for the user according to various user preferences, so that the low-efficiency limitation of manual matching of traditional customer service is avoided, the user can freely select favorite service providers, and the user experience is improved;
2. meanwhile, the intelligent scoring and marking meeting end user performs multi-maintenance information completion, so that a service provider can more accurately understand the user requirements and provide higher-quality service pertinently; from the aspect of operation cost, the system realizes automation, reduces the flow links needing manual intervention, reduces the operation cost and the flow complexity, can provide 24-hour timely matching service, and avoids the time limitation of the conventional mode;
3. the system and the method construct a standard data dimension library based on a process, users and service providers, provide a dynamic integral marking algorithm matched with the standard data dimension library, realize the optimal matching of the requirements and the services through an intelligent requirement matching scheduling strategy, and greatly improve the matching efficiency of the effective requirements and the services and the user experience.
Of course, it is not necessary for any product in which the invention is practiced to achieve all of the above-described advantages at the same time.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic structural diagram of an intelligent decoration requirement matching and order pushing system based on big data according to the present invention;
FIG. 2 is a flow chart of a core requirement priority policy resolution instruction and execution steps in the present invention;
FIG. 3 is a flow chart of the high QoS priority policy resolution instruction and execution steps of the present invention;
FIG. 4 is a flowchart of the steps for parsing and executing the comprehensive balanced matching priority policy of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
On the premise that online matching in the decoration industry is gradually approved by the market, decoration requirements of users are more and more, and services provided by service providers are more and more diversified. And the complexity of the flow and the process related to the decoration industry is high, so that a large information difference exists between the user and the service provider. The traditional customer service manual matching cannot eliminate the information difference, and efficient matching between the customer service manual matching and the customer service manual matching is realized.
The method and the system construct a standard data dimension base based on a process, users and service providers, provide a dynamic integral marking algorithm matched with the standard data dimension base, realize the optimal matching of the requirements and the services through an intelligent requirement matching scheduling strategy, and greatly improve the matching efficiency and the user experience of the effective requirements and the services, and the specific implementation process of the method comprises the following steps:
referring to fig. 1, the intelligent decoration requirement matching and order pushing system based on big data of the present invention includes an intelligent matching and order pushing system and a server;
the intelligent matching and bill pushing system comprises a demand entry module, a dynamic dimension integral marking control module, an intelligent matching and bill pushing strategy control module and a bill pushing control module;
the service end comprises a user demand preference dimension library, an industry process dimension library and a provider service and quality dimension library;
the demand input module acquires demand information of a decoration user through interface interaction and inputs the demand information into the system; the dynamic dimension integral marking control module is used for interacting the requirement information of the decoration user acquired by the requirement information inlet module with a user requirement preference dimension library, and performing data analysis and classification according to the requirement information and preference information submitted by the decoration user; the bill pushing control module is used for pushing a bill and receiving the bill by a service provider; the intelligent matching and order pushing strategy control module is used for realizing the interaction between the order pushing module and a user demand preference dimension library, an industry process dimension library and a provider service and quality dimension library;
the user demand preference dimension library is internally provided with a user demand basic information dimension and a user preference information dimension; industry process dimension information is put in the industry process dimension library; the service and quality dimension library of the provider is internally provided with service providing basic dimension and service quality dimension information.
The user demand basic information dimensionality comprises information of a city, a position, a house area, a house type, a space structure and a family structure; the user preference information dimensionality comprises decoration style preference, budget preference, building material brand preference, user process preference, designer preference and case preference.
The industry process dimension information comprises a plane layout design process, a wall body dismantling and modifying process, a hydropower modification process, a woodworking process, a muddy water paint process, a ceramic tile floor process, a kitchen and bathroom ceiling wall body process, a cabinet process, a door and window process, a hardware lamp process and a soft mounting process dimension information.
The service providing basic dimension and service quality dimension information comprises store information, store position information, service information, activity information, store comment information, service quality information, store popularity information, service range and process information.
As shown in fig. 2-4, a method for matching a waybill system based on intelligent decoration requirements of big data includes a technical design system scheme integrating a server industry standard data dimension library mechanism, a dynamic dimension library integral mark control mechanism, an intelligent matching and waybill strategy control mechanism, and a matching waybill strategy failure and service provider refused waybill recovery mechanism;
the server industry standard data dimension library mechanism is used for interacting a dynamic dimension integral mark control module in the intelligent matching and order-pushing system with an intelligent matching and order-pushing strategy control module;
the dynamic dimension library integral marking control mechanism is used for interacting a decoration user demand information inlet module and a user demand preference dimension library, and performing data analysis and classification according to demand information and preference information submitted by a user, and comprises a basic dimension library integral mechanism and a preference clustering completion strategy; after a basic dimension library integral mechanism and a preference clustering completion strategy mechanism, storing an obtained user core demand dimension result table and an associated integral result table for an intelligent matching and order pushing strategy control mechanism;
the intelligent matching and pushing strategy control mechanism relates to the interaction between a pushing control module and a user demand preference dimension library, an industry process flow dimension library and a provider service and quality dimension library, and matches a process and a service provider according to a user core demand dimension result table and an associated integral result table, wherein the used data comprises all dimensions of the process dimension library and the provider service and quality dimension library, and the contained intelligent scheduling strategy comprises a core demand priority strategy, a high service quality priority strategy and a comprehensive balance matching degree priority strategy; when a decoration user submits decoration requirements, a single strategy or a comprehensive strategy mechanism is selected independently; if the decoration user does not select the strategy, selecting one of the three single strategies to carry out monotonicity pushing;
the matching push policy failure and service provider refusal list retry recovery mechanism is specifically that after the service provider solves the problem of receiving push information, the intelligent scheduling module can automatically recover the mechanism, recalculate according to the original matching policy, perform storage and update operation on a new policy matching result, and execute the push operation; when the matching strategy pushing strategy is invalid and the service provider sets strict limits on the service range and style, the user requirement cannot be normally matched with the proper service provider, if the situation occurs, an automatic informing mechanism is triggered, the user service personnel is informed through a short message and platform message mechanism, and the user requirement and the service provider information are verified and processed by the service personnel;
the interaction between the dynamic dimension library integral mark control module and the intelligent matching and list pushing strategy control module and the interaction between each dimension library and the list pushing control module in the server side are unified by adopting a self-defined message format.
Wherein, the basic dimension library integration mechanism: matching the information of a user demand dimension library according to the basic information of the user, marking the scores, and calculating the scores according to the number of the subdivision dimensions and the matching priority; the single-dimensional complete matching records the basic demand weight proportion of 1 point, the single-dimensional partial matching records the basic demand weight proportion of 0.5 point, and the single-dimensional partial matching records the basic demand weight proportion of 0 point; wherein the weight proportion of the basic demand is the average value of similar type houses in the same city in the latest month;
partial users [ typically utility demand users ]): the functional design is more emphasized, and the specific type is not very concerned. In the strategy mechanism, the matching weight of the basic information of the user is higher in score. )
The base user dimension matching priority order is as follows: city, position, house type, space structure and family structure
The user preference dimension matching priority order is as follows: decoration style preference, designer preference, building material brand preference, process flow preference | case preference
The single dimension refers to each specific index in an index library, for example (indexes such as cities, positions, house areas, house types, space structures, family structure information and the like in a user basic dimension library are calculated as single dimensions.)
How to calculate a match, including partial match, full match, and failure to match:
partial matching:
example 1: the decoration requirement style of the user is preferred to be European decoration style, and the dimension library comprises simple Europe, Western Europe, Spanish style and the like. And judging the styles (simple Europe, Western Europe and Spanish styles) of the European class which is not precisely matched and is similar to the European class by the keywords, recording scores (0.5 score according to the above rule), and marking the European class decoration style which is interested by the user according to the weight distribution.
Example 2: the user house type is 'big flat layer 200 m', the dimension library is provided with 'big flat layer 5 chamber', 'big flat layer 6 chamber', 'big flat layer 7 chamber', etc., the similar 'big flat layer 6 chamber', 'big flat layer 7 chamber' is judged according to the area and the structural characteristics, and the scoring is carried out according to the rule.
And (3) complete matching:
example 1: the style preference of the user decoration requirement is 'simple Europe style', the keyword judgment is not exactly matched with 'simple Europe', and the scores are recorded, as the rule 1, respectively;
example 2: the house type of the user is '100 m for 3 rooms, 2 layers and 2 guards', the dimension library comprises '3 rooms, 2 layers and 2 guards', and the like, complete matching is judged according to keywords, and the scoring is carried out according to rules.
Failure to match:
example 1: the user decoration needs style preference, self-defines the millet style or is not set, and if the keyword is judged not to be accurately matched or similar, the score is not recorded.
Example 2: if the house type of the user is 'self-building house 50 m' or not set, the keyword is judged to be incapable of being accurately matched and partially matched, the score is not recorded, and the condition can be only identified manually;
preference clustering completion strategy: matching information of a user preference dimension library according to the user preference dimension information, performing integral marking, and performing score calculation according to the number of subdivided dimensions and the matching priority; the single-dimensional complete matching records are divided into 1 mark and preference weight proportion, the single-dimensional part matching records are divided into 0.5 mark and preference weight proportion, and the single-dimensional part can not be matched with the records of 0 mark; according to the preference cases of the user, identifying the style and decoration process of the cases through case clustering analysis, and performing score accumulation according to the matching degree percentage x 1; and for dimension information which cannot be provided by the user, performing score dimension calculation according to preference settings of users of the same type in the platform database, and labeling.
And (3) partial users: the general open type users do not pay much attention to practical requirements of specific functions, pay more attention to decoration color values, and have higher requirements on styles, designers, brands and the like. In the policy mechanism, the user preference information matching weight is given a higher score.
The base user dimension matching priority order is as follows: city > location > house type > space structure > family structure;
the user preference dimension matching priority order is as follows: decoration style preference > designer preference > building material brand preference > process flow preference | case preference;
the single dimension means that each specific index in the index library, such as indexes of a city, a position, a house area, a house type, a space structure, family structure information and the like in the user basic dimension library, is calculated as a single dimension.
How to calculate a match, including partial match, full match, and failure to match:
partial matching:
examples are: the decoration requirement style of a user is preferred to be 'European decoration style', and a dimension library has 'simple Europe', 'Western Europe', 'Spanish style' and the like; and judging the styles (simple Europe, Western Europe and Spanish styles) of the European class which is not precisely matched and is similar to the European class by the keywords, recording scores (0.5 score according to the above rule), and marking the European class decoration style which is interested by the user according to the weight distribution.
And (3) complete matching:
examples are: the style preference of the user decoration requirement is 'simple Europe style', the keyword judgment is not exactly matched with 'simple Europe', and scores are recorded (1 score according to the above rule);
failure to match:
examples are: the user decoration needs style preference, self-defines the millet style or is not set, and if the keyword is judged not to be accurately matched or similar, the score is not recorded.
The percent match is obtained and calculated as follows:
due to the fact that cases are decorated in a large number of ways and dimensions in case style and decoration technology, and continuous updating is increased. The mark which is not suitable for the fixed score scoring is calculated by matching the dimension. The platform can be regularly clustered and updated in a fixed period. Typically 2 weeks to 4 weeks.
Examples are: for example, the user house source is located in a villa area and prefers 'Chinese style' of decoration style, 'house customization home' and 'integral bathroom' in decoration process, 'simple marble tile' and 'polylith emulsion paint' in brand, etc. The method can be corresponding to the technical field of plane layout design flow process \ [ carpentry flow process ] \ [ ceramic tile floor flow process \ [ slurry paint flow process ] by adopting a keyword matching mode.
The percentage is recorded according to the keyword matching rate and is divided into [ complete matching is 100% ] [ partial matching is hit dimension/total dimension ] [ unmatched is 0% ], and the weight is calculated according to [ 1/total environment dimension ].
[ Users of the same kind ]
Clustering the matched users into similar users according to the following sequence: similar user preference > similar user base dimension > same region;
if the user does not specifically mark the preference requirement or the keyword selection of the preference requirement is wrong, which causes the failure of matching, the preferences of the users of the same type are used. Because the mechanism is the conjecture of the users of the same type, the deviation exists between the non-user direct marking and the real requirement of the user, and the weight value is 50 percent of the weight value of the user marking. And has special identification [ system automatic marking ].
Wherein, the core requirement priority strategy is as follows: according to core requirement indexes and preferences of users, preferentially ensuring the service provider with the highest core requirement degree to be matched, wherein the core requirements are core requirements of the users and the process range; specifically, the intelligent matching and list pushing strategy control module automatically receives a dynamic dimension library integral mark control result, analyzes an instruction, and executes the following processes:
s01, acquiring user demand dimensions and dimension integrals in the instruction;
s02, loading a process standard library and providing a standard library by a service provider;
s03, excluding the service merchant provider who suspends the order receiving;
s04, eliminating relevant service providers with unmatched user preferences; the method comprises the steps of mismatch of decoration style, mismatch of budget, match of service and brand part and the like;
s05, matching scores of the main demand dimensions, and calculating scores of the rest service providers;
s06, circularly executing the steps through the S05 to realize the point value accumulation calculation of the service provider;
and S07, storing and recording the service provider list with the highest score, and pushing the first three digits to perform a list pushing module.
Wherein, the high service quality priority strategy is as follows: according to the core requirement index and preference of the user, the service provider with the highest service quality is preferentially ensured to be matched, the intelligent matching and list pushing strategy control module automatically receives the control result of the integral mark of the dynamic dimension library, analyzes the instruction and executes the following procedures:
p01, acquiring user demand dimensions and dimension integrals in the instruction;
p02, loading a process standard library and providing a standard library by a service provider;
p03, service merchant provider excluding pickup suspension;
p04, excluding service providers with service provider quality score values which do not meet the user requirements; the method comprises the steps that the service provider comprehensive score does not reach the standard, the same city ranking does not reach the standard, the service heat score does not reach the standard and the like, and score calculation is carried out on the rest service providers;
p05, matching scores of the main matching demand dimensions, and calculating scores of the rest service providers;
p06, the score of the service provider is calculated in a circulating way through the P05 step;
and P07, storing and recording the service provider list with the highest score, and pushing the first three digits to perform a list pushing module.
Wherein, the comprehensive balance matching priority strategy is as follows: according to the core requirement index and preference of the user, preferentially ensuring the service provider with the highest core requirement degree to be matched, wherein the core requirement degree is the core requirement of the user and the process range; the intelligent matching and list pushing strategy control module automatically receives the integral marking control result of the dynamic dimension library, analyzes the instruction and executes the following procedures:
t01, acquiring user demand dimensions and dimension integrals in the instruction;
t02, loading a process standard library and providing a standard library by a service provider;
t03, service merchant provider for excluding suspension of order pickup;
t04, matching scores of the matching demand dimensions, and calculating scores of the rest service providers;
t05, circularly executing through a T04 step mode, and realizing the score accumulation calculation of a service provider;
and T06, storing and recording the service provider list with the highest score, and pushing the first three digits to perform a list pushing module. The user-defined message format is as follows:
table 1: custom message format table
The method comprises the following fields: id; type; params; status; the id represents the number of the data transmission instruction and is used for interaction among the tracing modules, and the id information comprises a user number, a user demand number and sectional information, so that the fault tolerance of the demand dimension is provided; the Type represents the Type of a data transmission instruction, and supports three types of a heartbeat instruction, a system interaction instruction and a list pushing execution instruction; the Params represents specific data information of the instruction and is a set stored in a key value pair mode, the key attribute is a dimension number, and the value attribute comprises a score, a weight, a reason, time, a sequence, a strategy and the like; status indicates instruction information, and has modes of immediate effect, delayed effect, timed effect and the like;
the field names corresponding to the fields are respectively: numbering ID; a dimension type; instruction parameters, stored by using a key value pair mode; an instruction state;
the formats corresponding to the fields are: a character string; a character string; gathering; a number;
the descriptions corresponding to the fields are: an instruction number; a system interaction instruction, a heartbeat instruction and a list pushing execution instruction are carried out; bond: dimension, value: scores, weights, reasons, time, order, policies, etc.; immediate effect, delayed effect and timed effect.
From the technical point of view, due to the adoption of various intelligent scheduling planning and bill pushing matching mechanisms, the bill receiving rate of a service provider is improved, the service docking time is shortened, the matching efficiency of 3 service providers is matched according to 1 user, and compared with 2 to 3 working days in the traditional mode, the matching efficiency is shortened to 10 minutes to 30 minutes. The butt joint conversion rate of the demand and the service is greatly improved.
Has the advantages that:
1. the invention mainly aims to solve the problems of low matching rate and low conversion rate of user requirements and service providers in the decoration industry; matching the user requirements, the services provided by the service providers and the decoration processes and technologies based on a dimension standard library of three aspects of decoration processes and technologies, user requirements and preferences and service and quality of the service providers to form a multi-dimensional point marking result table, configuring the table through a dynamic intelligent algorithm, and performing order pushing operation on the service providers after optimal planning is performed; the algorithm strategy can provide recommendation of multiple service providers for the user according to various user preferences, so that the low-efficiency limitation of manual matching of traditional customer service is avoided, the user can freely select favorite service providers, and the user experience is improved;
2. meanwhile, the intelligent scoring and marking meeting end user performs multi-maintenance information completion, so that a service provider can more accurately understand the user requirements and provide higher-quality service pertinently; from the aspect of operation cost, the system realizes automation, reduces the flow links needing manual intervention, reduces the operation cost and the flow complexity, can provide 24-hour timely matching service, and avoids the time limitation of the conventional mode;
3. the system and the method construct a standard data dimension library based on a process, users and service providers, provide a dynamic integral marking algorithm matched with the standard data dimension library, realize the optimal matching of the requirements and the services through an intelligent requirement matching scheduling strategy, and greatly improve the matching efficiency of the effective requirements and the services and the user experience.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (10)
1. An intelligent decoration requirement matching and bill pushing system based on big data is characterized by comprising an intelligent matching and bill pushing system and a server side;
the intelligent matching and bill pushing system comprises a demand entry module, a dynamic dimension integral marking control module, an intelligent matching and bill pushing strategy control module and a bill pushing control module;
the service end comprises a user demand preference dimension library, an industry process dimension library and a provider service and quality dimension library;
the demand entry module acquires demand information of a decoration user through interface interaction and enters the demand information into the system; the dynamic dimension integral marking control module is used for interacting the requirement information of the decoration user acquired by the requirement information inlet module with a user requirement preference dimension library, and performing data analysis and classification according to the requirement information and preference information submitted by the decoration user; the bill pushing control module is used for pushing a bill and receiving the bill by a service provider; the intelligent matching and order pushing strategy control module is used for realizing the interaction between the order pushing module and a user demand preference dimension library, an industry process dimension library and a provider service and quality dimension library;
the user demand preference dimension library is internally provided with a user demand basic information dimension and a user preference information dimension; industry process dimension information is stored in the industry process dimension library; the service and quality dimension library of the provider is internally provided with service providing basic dimension and service quality dimension information.
2. The big data-based intelligent decoration requirement matching and order pushing system of claim 1, wherein the user requirement basic information dimension comprises information of a city, a position, a house area, a house type, a space structure and a family structure; the user preference information dimensionality comprises decoration style preference, budget preference, building material brand preference, user process preference, designer preference and case preference.
3. The intelligent decoration requirement matching and order-pushing system based on big data as claimed in claim 1, wherein the industry process dimension information comprises a planar layout design process, a wall dismantling and modifying process, a hydroelectric reconstruction process, a woodworking process, a muddy water paint process, a tile floor process, a kitchen and bathroom ceiling wall process, a cabinet process, a door and window process, a hardware lamp process, and a soft-mounting process dimension information.
4. The intelligent decoration requirement matching and order pushing system based on big data as claimed in claim 1, wherein the service providing basic dimension and service quality dimension information includes store information, store position information, service information, activity information, store comment information, service quality information, store popularity information, service scope and process information.
5. The method for matching a waybill system based on the intelligent decoration requirement of big data as claimed in any one of claims 1-4, comprising a server industry standard data dimension base mechanism, a dynamic dimension base integral mark control mechanism, an intelligent matching and waybill strategy control mechanism, and a matching waybill strategy failure and waybill retry recovery mechanism of a service provider;
the server industry standard data dimension library mechanism is used for interacting a dynamic dimension integral marking control module in the intelligent matching and order-pushing system with an intelligent matching and order-pushing strategy control module;
the dynamic dimension library integral marking control mechanism is used for interacting a decoration user demand information inlet module and a user demand preference dimension library, and performing data analysis and classification according to demand information and preference information submitted by a user, and comprises a basic dimension library integral mechanism and a preference clustering completion strategy; after a basic dimension library integral mechanism and a preference clustering completion strategy mechanism, storing an obtained user core demand dimension result table and an associated integral result table for an intelligent matching and order pushing strategy control mechanism;
the intelligent matching and pushing strategy control mechanism relates to the interaction between a pushing control module and a user demand preference dimension library, an industry process flow dimension library and a provider service and quality dimension library, and matches process processes and service providers according to a user core demand dimension result table and an associated integral result table, wherein the used data comprises all dimensions of the process dimension library and the provider service and quality dimension library, and the contained intelligent scheduling strategies comprise a core demand priority strategy, a high service quality priority strategy and a comprehensive balance matching degree priority strategy; when a decoration user submits decoration requirements, a single strategy or a comprehensive strategy mechanism is selected independently; if the decoration user does not select the strategy, selecting one of the three single strategies to carry out monotonicity pushing;
the matching push policy failure and service provider refusal list retry recovery mechanism is specifically that after the service provider solves the problem of receiving push information, the intelligent scheduling module can automatically recover the mechanism, recalculate according to the original matching policy, perform storage and update operation on a new policy matching result, and execute push operation; when the matching strategy pushing strategy is invalid and the service provider sets strict limits on the service range and style, the user requirement cannot be normally matched with the proper service provider, if the situation occurs, an automatic informing mechanism is triggered, the user service personnel is informed through a short message and platform message mechanism, and the user requirement and the service provider information are verified and processed by the service personnel;
and the interaction between the dynamic dimension library integral marking control module and the intelligent matching and list pushing strategy control module and the interaction between each dimension library and the list pushing control module in the server side are unified by adopting a user-defined message format.
6. The method for intelligent decoration requirement matching of bill pushing system based on big data as claimed in claim 5, wherein:
the base dimension library integration mechanism: matching the information of a user demand dimension library according to the basic information of the user, marking the scores, and calculating the scores according to the number of the subdivision dimensions and the matching priority; the single-dimensional complete matching records the basic demand weight proportion of 1 point, the single-dimensional partial matching records the basic demand weight proportion of 0.5 point, and the single-dimensional partial matching records the basic demand weight proportion of 0 point; wherein the weight proportion of the basic demand is the average value of similar type houses in the same city in the latest month;
the preference clustering completion strategy is as follows: matching information of a user preference dimension library according to the user preference dimension information, performing integral marking, and performing score calculation according to the number of subdivided dimensions and the matching priority; the single-dimensional complete matching records are divided into 1 mark and preference weight proportion, the single-dimensional part matching records are divided into 0.5 mark and preference weight proportion, and the single-dimensional part can not be matched with the records of 0 mark; according to the preference cases of the user, identifying the style and decoration process of the cases through case clustering analysis, and performing score accumulation according to the matching degree percentage x 1; and for dimension information which cannot be provided by the user, performing score dimension calculation according to preference settings of users of the same type in the platform database, and labeling.
7. The method for intelligent decoration requirement matching of bill pushing system based on big data as claimed in claim 5, wherein:
the core requirement priority strategy is as follows: according to core requirement indexes and preferences of users, preferentially ensuring the service provider with the highest core requirement degree to be matched, wherein the core requirements are core requirements of the users and the process range; specifically, the intelligent matching and list pushing strategy control module automatically receives a dynamic dimension library integral mark control result, analyzes an instruction, and executes the following processes:
s01, acquiring user demand dimensions and dimension integrals in the instruction;
s02, loading a process standard library and providing a standard library by a service provider;
s03, excluding the service merchant provider who suspends the order receiving;
s04, eliminating relevant service providers with unmatched user preferences; the method comprises the steps of mismatch of decoration style, mismatch of budget, match of service and brand part and the like;
s05, matching scores of the main demand dimensions, and calculating scores of the rest service providers;
s06, circularly executing the steps through the S05 to realize the point value accumulation calculation of the service provider;
and S07, storing and recording the service provider list with the highest score, and pushing the first three digits to perform a list pushing module.
8. The method for intelligent decoration requirement matching of bill pushing system based on big data as claimed in claim 5, wherein:
the high quality of service priority policy: according to the core requirement index and preference of the user, the service provider with the highest service quality is preferentially ensured to be matched, the intelligent matching and list pushing strategy control module automatically receives the control result of the integral mark of the dynamic dimension library, analyzes the instruction and executes the following processes:
p01, acquiring user demand dimensions and dimension integrals in the instruction;
p02, loading a process standard library and providing a standard library by a service provider;
p03, service merchant provider excluding pickup suspension;
p04, excluding service providers with service provider quality score values which do not meet the user requirements; the method comprises the steps that the service provider comprehensive score does not reach the standard, the same city ranking does not reach the standard, the service heat score does not reach the standard and the like, and score calculation is carried out on the rest service providers;
p05, matching scores of the main matching demand dimensions, and calculating scores of the rest service providers;
p06, the score of the service provider is calculated in a circulating way through the P05 step;
and P07, storing and recording the service provider list with the highest score, and pushing the first three digits to perform a list pushing module.
9. The method for intelligent decoration requirement matching of bill pushing system based on big data as claimed in claim 5, wherein:
the comprehensive balance matching priority strategy is as follows: according to the core requirement index and preference of the user, preferentially ensuring the service provider with the highest core requirement degree to be matched, wherein the core requirement degree is the core requirement of the user and the process range; the intelligent matching and list pushing strategy control module automatically receives the integral marking control result of the dynamic dimension library, analyzes the instruction and executes the following procedures:
t01, acquiring user demand dimensions and dimension integrals in the instruction;
t02, loading a process standard library and providing a standard library by a service provider;
t03, service merchant provider for excluding suspension of order pickup;
t04, matching scores of the matching demand dimensions, and calculating scores of the rest service providers;
t05, circularly executing through a T04 step mode, and realizing the score accumulation calculation of a service provider;
and T06, storing and recording the service provider list with the highest score, and pushing the first three digits to perform a list pushing module.
10. The method for matching the manifest system for the intelligent decoration requirement based on the big data as claimed in claim 5, wherein the custom message format is as follows:
the method comprises the following fields: id; type; params; status; the id represents the number of the data transmission instruction and is used for interaction among the tracing modules, and the id information comprises a user number, a user demand number and sectional information, so that the fault tolerance of the demand dimension is provided; the Type represents the Type of a data transmission instruction, supports three types of a heartbeat instruction, a system interaction instruction and a list pushing execution instruction; the Params represents specific data information of the instruction and is a set stored in a key value pair mode, the key attribute is a dimension number, and the value attribute comprises a score, a weight, a reason, time, a sequence, a strategy and the like; the Status indicates instruction information and has the modes of immediate effect, delayed effect, timed effect and the like;
the field names corresponding to the fields are respectively: numbering ID; a dimension type; instruction parameters, stored by using a key value pair mode; an instruction state;
the formats corresponding to the fields are: a character string; a character string; gathering; a number;
the descriptions corresponding to the fields are: an instruction number; a system interaction instruction, a heartbeat instruction and a list pushing execution instruction are carried out; bond: dimension, value: scores, weights, reasons, time, order, policies, etc.; immediate effect, delayed effect and timed effect.
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