CN113112173A - Intelligent matching method and system for housekeeping service personnel and computer equipment - Google Patents
Intelligent matching method and system for housekeeping service personnel and computer equipment Download PDFInfo
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Abstract
The invention belongs to the field of housekeeping services, and provides a method, a system and computer equipment for intelligently matching housekeeping service personnel, wherein the method comprises the following steps: establishing an housekeeping staff database to store the characteristic parameters of the waiters of the housekeeping staff; acquiring text data of a user about the requirement of the housekeeping service through a client; extracting the user characteristic parameters of the user from the text data; matching the user characteristic parameters with characteristic parameters of each service person in the database to calculate the matching degree of each housekeeping service person and the user; and transmitting the information of the service personnel to the client according to the matching degree and a preset push strategy. The method can accurately match the housekeeping service personnel and improve the ordering rate of the user.
Description
Technical Field
The invention belongs to the technical field of internet, is particularly suitable for the field of housekeeping services, and more particularly relates to an intelligent matching method and system for housekeeping service personnel and computer equipment.
Background
The home services include the sisters-in-law services, the nurse services and the like, and the sisters-in-law services in the traditional home services are favored by consumers: and the month sister to the home of the user to provide the child care service for the user. However, the traditional sisters-in-law services mainly serve users by means of experiences summarized by the users, and the content and quality of the services of the sisters-in-law are not clear to the users.
In particular, traditional housekeeping services have several major drawbacks: the quality and the content of the home-based service cannot be guaranteed, and the content of the home-based service cannot be supervised and checked. In the existing home services, most of the services in the month-sisters-in-law are introduced by intermediaries or introduced by friends, the content and quality of the services are opaque, and the services in the month-sisters-in-law have no unified standard, for example, the month-sisters-in-law is also served by experience, so that scientific child care cannot be achieved, and adaptive services aiming at user requirements cannot be effectively realized.
The existing household service system can provide on-line reservation household service items for consumers, other requirements can only depend on telephone communication of brokers or promoters or social tools for communication, the system is not convenient enough, the requirements of users for appointing service personnel according to the requirements cannot be met, the system can only listen to household companies or household service platforms to randomly arrange household personnel for home service, and the problems that the distribution of household service personnel is unreasonable, the matching accuracy of the household service personnel and the users is low, the user customization requirements cannot be effectively met, and the like exist.
Therefore, there is a need to provide a more efficient intelligent matching method for housekeeping service personnel.
Disclosure of Invention
Technical problem to be solved
The invention aims to solve the problems of unreasonable distribution of the housekeeping service personnel, low matching accuracy of the housekeeping service personnel and the user, incapability of effectively realizing the adaptive service of the user customization requirement and the like.
(II) technical scheme
In order to solve the above technical problems, an aspect of the present invention provides an intelligent matching method for housekeeping service personnel, including the following steps: establishing an housekeeping staff database to store the characteristic parameters of the waiters of the housekeeping staff; acquiring text data of a user about the requirement of the housekeeping service through a client; extracting the user characteristic parameters of the user from the text data; matching the user characteristic parameters with characteristic parameters of each service person in the database to calculate the matching degree of each housekeeping service person and the user; and transmitting the information of the service personnel to the client according to the matching degree and a preset push strategy.
According to a preferred embodiment of the present invention, acquiring text data of a user about needs of a home service through a client comprises: the method comprises the steps of providing a text and/or voice chat tool on a client, and acquiring text data of a user about needs of the home services through the chat tool.
According to the preferred embodiment of the invention, the chat tool is integrated in the mobile device APP or PC side application software for home services.
According to the preferred embodiment of the present invention, the information of the service person pushed to the client is transmitted through the APP or PC application software of the mobile device.
According to a preferred embodiment of the present invention, the method further comprises calculating a user intention degree according to the user characteristic parameter of the user; and only when the user intention meets a preset condition, matching the user characteristic parameters with the characteristic parameters of the service persons in the database to calculate the matching degree of the household service persons and the user.
According to a preferred embodiment of the present invention, calculating the user intention degree according to the user characteristic parameter of the user includes: and calculating the order placing probability of the current user by adopting a machine learning algorithm based on the order data of the historical users, and using the probability as the user intention.
According to a preferred embodiment of the present invention, further comprising: acquiring current order data, and extracting user characteristic parameters from the current order data, wherein the user characteristic parameters comprise user intention characteristic data and user preference characteristic data.
According to a preferred embodiment of the present invention, the calculating the matching degree between each housekeeping service person and the user includes: screening out candidate housekeeping service personnel by adopting a preset matching rule; and calculating the matching degree of each candidate housekeeping service personnel by adopting a matching degree calculation model, and taking the candidate housekeeping service personnel with the matching degree meeting the preset conditions as the matched housekeeping service personnel.
According to a preferred embodiment of the present invention, comprises: establishing a match calculation model using a Bayesian algorithm, the match calculation model being trained using a training data set, the training data set being from at least one of: the method comprises the steps of ordering data of historical users, chatting data extracted from chatting APPs, service matching characteristic data, APP installation list data of the historical users and matched service personnel characteristic data.
According to a preferred embodiment of the present invention, the chatting data includes user age, taste preference, preference age section for service person extracted from guide question-and-answer type interview or chatting data for judging user service demand; and/or the attendant characteristic data comprises age, gender, geographic location, expert cuisine data, academic data, historical order data associated with each attendant.
The invention provides an intelligent matching system for home administration service personnel, which comprises a client and a server, wherein a home administration service personnel database is established on the server to store characteristic parameters of the service personnel of each home administration service personnel; the client is used for acquiring text data of the user about the requirement of the housekeeping service; the client or the server extracts the user characteristic parameters of the user from the text data; the server matches the user characteristic parameters with characteristic parameters of all the servers in the database to calculate the matching degree of all the housekeeping service personnel and the user; and the server transmits the information of the service personnel to the client according to the matching degree and a preset push strategy.
According to a preferred embodiment of the present invention, the client or the server calculates a user intention according to a user characteristic parameter of the user, and matches the user characteristic parameter with each server characteristic parameter in the database only when the user intention satisfies a predetermined condition, so as to calculate a matching degree of each housekeeping service person with the user.
According to a preferred embodiment of the present invention, the calculating, by the client or the server, the user intention degree according to the user characteristic parameter of the user includes: and calculating the order placing probability of the current user by adopting a machine learning algorithm based on the order data of the historical users, and using the probability as the user intention.
According to a preferred embodiment of the present invention, the calculating the matching degree between each housekeeping service person and the user includes: screening out candidate housekeeping service personnel by adopting a preset matching rule; and calculating the matching degree of each candidate housekeeping service personnel by adopting a matching degree calculation model, and taking the candidate housekeeping service personnel with the matching degree meeting the preset conditions as the matched housekeeping service personnel.
The third aspect of the present invention provides a computer device, configured as a client communicatively connected to a server, where an housekeeping service staff database is established on the server to store characteristic parameters of a server of each housekeeping service staff; the client is used for acquiring text data of the user about the requirement of the housekeeping service; the client or the server extracts the user characteristic parameters of the user from the text data; the server matches the user characteristic parameters with characteristic parameters of all the servers in the database to calculate the matching degree of all the housekeeping service personnel and the user; and the server transmits the information of the service personnel to the client according to the matching degree and a preset push strategy.
The fourth aspect of the present invention further provides a computer program product, which stores a computer executable program, and when the computer executable program is executed, the intelligent matching method for the housekeeping service staff is implemented.
(III) advantageous effects
Compared with the prior art, the method has the advantages that the housekeeping service personnel database and the user database are established, and the housekeeping service personnel, the users and the respective related characteristic data which are in dynamic change are respectively stored in real time, so that the intelligent matching process of the housekeeping service personnel can be further optimized; the user intention (namely the predicted order placing rate) of the user in the current order data can be accurately calculated, and the user with intention can be judged according to the user intention; by using the first requirement parameter and the second requirement parameter, the rough matching processing is performed on the user in the current order data and each housekeeping service person in the housekeeping service person database, and then the fine matching processing is performed by using model calculation, so that the housekeeping service person corresponding to the user can be matched more accurately, a more effective matching process can be realized, the calculation amount can be reduced, and the resources can be saved; the method and the system can effectively realize the adaptation service of the user customization demand, provide more effective push information for the user, and improve the user experience and the ordering rate.
Drawings
Fig. 1 is a flowchart of an example of an intelligent matching method for housekeeping service staff according to embodiment 1 of the present invention.
Fig. 2 is a flowchart of another example of the intelligent matching method for housekeeping service personnel according to embodiment 1 of the present invention.
Fig. 3 is a flowchart of another example of the intelligent matching method for housekeeping service personnel according to embodiment 1 of the present invention.
Fig. 4 is a schematic diagram of an example of the housekeeping service person intelligent matching system according to embodiment 2 of the present invention.
Fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
FIG. 6 is a schematic diagram of a computer program product of an embodiment of the invention.
Detailed Description
In describing particular embodiments, specific details of structures, properties, effects, or other features are set forth in order to provide a thorough understanding of the embodiments by one skilled in the art. However, it is not excluded that a person skilled in the art may implement the invention in a specific case without the above-described structures, performances, effects or other features.
The flow chart in the drawings is only an exemplary flow demonstration, and does not represent that all the contents, operations and steps in the flow chart are necessarily included in the scheme of the invention, nor does it represent that the execution is necessarily performed in the order shown in the drawings. For example, some operations/steps in the flowcharts may be divided, some operations/steps may be combined or partially combined, and the like, and the execution order shown in the flowcharts may be changed according to actual situations without departing from the gist of the present invention.
The block diagrams in the figures generally represent functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and/or processing unit systems and/or microcontroller systems.
The same reference numerals denote the same or similar elements, components, or parts throughout the drawings, and thus, a repetitive description thereof may be omitted hereinafter. It will be further understood that, although the terms first, second, third, etc. may be used herein to describe various elements, components, or sections, these elements, components, or sections should not be limited by these terms. That is, these phrases are used only to distinguish one from another. For example, a first device may also be referred to as a second device without departing from the spirit of the present invention. Furthermore, the term "and/or", "and/or" is intended to include all combinations of any one or more of the listed items.
In view of the above problems, the invention provides an intelligent matching method for housekeeping service personnel, which comprises the steps of extracting characteristic data from IM chat data between a user and a broker, between the broker and the housekeeping service personnel, forming a user characteristic parameter and a server characteristic parameter of the housekeeping service personnel, calculating the user intention degree by using the user characteristic parameter, and screening out candidate housekeeping service personnel by adopting a preset matching rule; and calculating the matching degree of each candidate housekeeping service personnel by adopting a matching degree calculation model, and taking the candidate housekeeping service personnel with the matching degree meeting the preset conditions as the matched housekeeping service personnel. Therefore, the housekeeping service personnel can be matched accurately, and the ordering rate of the user can be improved.
In order that the objects, technical solutions and advantages of the present invention will become more apparent, the present invention will be further described in detail with reference to the accompanying drawings in conjunction with the following specific embodiments.
Example 1
Fig. 1 is a flowchart of an example of an intelligent matching method for housekeeping service staff according to embodiment 1 of the present invention.
As shown in fig. 1, an intelligent matching method for home service staff is provided, which specifically includes the following steps.
Step S101, an housekeeping service personnel database is established to store the characteristic parameters of the service personnel of each housekeeping service personnel.
Step S102, text data of the user about the requirement of the housekeeping service is obtained through the client.
Step S103, extracting the user characteristic parameter of the user from the text data.
And step S104, matching the user characteristic parameters with the characteristic parameters of the service persons in the database to calculate the matching degree of the home service persons and the user.
And step S105, transmitting the information of the service personnel to the client according to the matching degree and a preset push strategy.
In this example, the method of the present invention is used to match the housekeeping staff to the user in the service order of the housekeeping service and recommend the matched housekeeping staff to the user. Therefore, the housekeeping service personnel can be matched accurately, and the ordering rate of the user can be improved.
First, in step S101, an housekeeping staff database is established to store the characteristic parameters of the servicers of each housekeeping staff.
Specifically, an housekeeping service personnel database is established and used for storing characteristic parameters of service personnel of each housekeeping service personnel, wherein the housekeeping service personnel comprise the housekeeping service personnel in historical order data and the housekeeping service personnel newly registered by each housekeeping service product APP, a text data of a user about the housekeeping service requirement is obtained through a chat tool for providing characters and/or voice on a client of each housekeeping service product APP.
More specifically, the housekeeping service personnel include a moon sao, a nurse, a temporary cleaner, and the like.
In this example, the server characteristic parameters include age, gender, geographic location, good cuisine data, scholarly data, historical order data associated with each server.
Further, a user database is established, and the user database is used for storing users needing the home services and user characteristic parameters thereof, wherein the users comprise historical users, users newly registered by various home service products APP, current users submitting service orders and the like.
Specifically, the user characteristic parameters include age, gender, type of required home services, service time, and taste characteristic data, and the like.
Therefore, the intelligent matching process of the housekeeping service personnel can be further optimized by establishing a housekeeping service personnel database and a user database, and respectively storing the housekeeping service personnel and the users which are dynamically changed and the respective related characteristic data in real time.
It should be noted that the above description is only given as a preferred example, and the present invention is not limited thereto.
Next, in step S102, text data of the user about the needs of the home services is acquired by the client.
Specifically, chat data between a user and a broker is obtained from a chat tool on a client side of a certain household service product APP, and text data of the user about household service requirements is obtained through the chat tool, wherein the chat tool is integrated in a mobile device APP or PC side application software for household services.
Further, the chat data is, for example, text data for guiding question and answer interviews or chatting, which includes user age, taste preference, geographical location of demand, academic requirement, character requirement, age zone of desired service personnel, salary range available, and other user service demand data, and the like.
In another example, the chat data further includes text data converted by speech, the text data including various data of the user's needs for the home service, and the like.
It should be noted that the specific chat data is described as an example, and is not to be construed as limiting the invention.
Next, in step S103, the user feature parameter of the user is extracted from the text data.
Specifically, from the text data acquired in step S102, the user characteristic parameters of the user are extracted.
For example, from the guided question-and-answer type interview or chat data for judging the service demand of the user, user characteristic parameters of the user age, taste preference, preference age zone to the service person, and the like are extracted.
In another example, the method further comprises extracting user intention characteristics from historical order data of the housekeeping service so as to further improve user characteristic parameters.
Further, extracting service matching feature and housekeeping staff feature data, and using the extracted data to build a training data set for training the model.
In yet another example, the user characteristic parameters further include APP installation list data of the user, where the APP installation list of the user is obtained and vector conversion is performed to generate the APP installation list data of the user.
Therefore, the user characteristic parameters of the user are extracted from multiple dimensions to obtain more accurate user characteristic parameters, and secondary calculation is carried out by using the user characteristic parameters.
And further, according to the obtained user characteristic parameters, users in the user data database are classified finely, and a corresponding user characteristic label is added for each user for subsequent data analysis.
It should be noted that the above description is only given by way of example, and the present invention is not limited thereto.
Fig. 2 is a flowchart showing another example of the housekeeping service person intelligent matching method of embodiment 1 of the present invention.
As shown in fig. 2, a step S201 of determining whether the user intention satisfies a predetermined condition is further included.
In step S201, it is determined whether the user intention satisfies a predetermined condition.
Specifically, the user intention is calculated from the user characteristic parameter of the user, which is the same as the physical meaning to which the user characteristic parameter in step S103 refers, the extraction method is the same, and therefore, the description thereof is omitted.
In this example, a machine learning algorithm is employed to calculate the probability of placing an order for a user of the current user based on order data of historical users, which is used as the user intent.
For example, using the FM algorithm, a user intent prediction model is constructed that is trained using a first training data set from at least one of: geographic location of the user, age, historical user ordering rate, service matching profile data, and server profile parameters of matched service personnel.
It should be noted that the above is only described as an example, and the present invention is not limited thereto, and in other examples, the user intention prediction model may be constructed by using an FFM algorithm, a DeepFM algorithm, a combination algorithm of the two algorithms, or other methods using machine learning.
Specifically, current order data are obtained, user intention characteristic data and taste characteristic data are extracted from the current order data to form user characteristic parameters, the user characteristic parameters are used, and a user prediction model is used for calculating the user intention of the user.
Preferably, the user characteristic parameters include user intention characteristic data and taste characteristic data, the user intention characteristic data including at least two characteristic data of geographic position of the user's demand, academic requirement, character requirement, age section of desired service personnel and salable range.
And further, inputting the extracted user intention characteristic data and the extracted taste characteristic data into the user intention prediction model, and calculating the user intention of the user.
Further, the calculated user intention is compared with a predetermined condition to determine whether the user satisfies a predetermined condition for one filtering.
Therefore, the user intention degree (namely the predicted order placing rate) of the user in the current order data can be accurately calculated, and the user with intention (namely the user with the user intention degree larger than a specific value) can be judged according to the user intention degree.
It should be noted that the above description is made only by way of example and not to be construed as limiting the invention,
next, in step S104, the user characteristic parameters are matched with the characteristic parameters of the service persons in the database, so as to calculate the matching degree between each housekeeping service person and the user.
Specifically, when the calculated user intention satisfies a predetermined condition, it is determined that the user is an intention user.
Further, according to a preset matching rule, the user characteristic parameter of the user is matched with (or matched with) the characteristic parameters of the service persons in the home service person database, so that candidate home service persons are screened out.
Fig. 3 is a flowchart showing still another example of the housekeeping service person intelligent matching method of embodiment 1 of the present invention.
As shown in fig. 3, a step S301 of determining a first requirement parameter and a second requirement parameter for matching processing is further included.
In step S301, a first requirement parameter and a second requirement parameter for matching processing are determined.
In this example, the matching process includes a first matching process for matching a plurality of first requirement parameters of the user and a second matching process for matching a plurality of second requirement parameters of the user.
Specifically, the first requirement parameter is a hard index, for example, including geographic location, salary data, age, whether to home, type of home service, and time.
Further, the second requirement parameter is a softness index, for example, including specific age range, academic calendar, and dietary flavor.
In this example, the importance coefficient is set for each first requirement parameter and each second requirement parameter, respectively.
Specifically, the first requirement parameter is used for calculating a first matching degree of each service staff and the user so as to obtain a service staff set subjected to primary matching screening;
further, under the condition that the first matching degree is larger than a specific value, the second matching degree of each service person and the user is calculated by using the second requirement parameters, then the first matching degree and the second matching degree are added in a weighted mode to obtain the matching degree of each service person and the user, and secondary matching screening processing is carried out on the service person set to form a service person matching list, namely the obtained candidate housekeeping service persons.
In a first matching process (i.e., coarse matching), for example, the first demand parameters include geographic location, salary, age, whether or not to home, the first match calculated using the first demand parameters is 62%,
while in the second matching process (i.e., fine matching), the second requirement parameters include age, academic calendar, good cuisine, etc., after the coarse matching is 62%, fine matching: the degree of matching of the housekeeping staff A is 92% after the age of 40 years (10%), the family (10%), the West Hunan cuisine, the Sichuan cuisine (10%), and the like.
For example, housekeeping staff B fine matches after a coarse match of 60%: the matching degree of home service staff B is 75 percent when the Chinese medicinal herbs are 45 years old (5 percent), special departments (5 percent), good at Hunan cuisine (5 percent), and the like
As another example, the degree of matching, such as housekeeping attendant C, is 71% to form a set of attendants with an ordering (AB C).
In another example, after the service personnel set subjected to matching screening is obtained, the matching degree of each candidate household service personnel is calculated by adopting a matching degree calculation model, and the candidate household service personnel is screened from the service personnel set through the calculated matching degree to serve as the matching household service personnel.
In this example, a match computation model is built, for example using a bayesian algorithm, and trained using a training data set, wherein the training data set is from at least one of: the system comprises the steps of ordering data of historical users, chatting data extracted from chatting APPs, service matching characteristic data, APP installation list data of the historical users, user characteristic parameters and server characteristic parameters of matched home service staff.
Specifically, the service matching feature data comprises a household service type, a service time and a geographic position.
It should be noted that the user characteristic parameter in this example is the same as the user characteristic parameter in step S103, the chat data is the same as the chat data in step S102, and the attendant characteristic parameter of the home service staff is the same as the attendant characteristic parameter of the home service staff in step S101, and therefore, the description of the above data is omitted.
Specifically, the trained matching degree calculation model is used for calculating the matching degree of the user and each household service staff in the service staff set, and candidate household service staff with the calculated matching degree meeting the preset conditions are used as matched household service staff.
In yet another example, the user intention degree of the user in the current order data and the proportion of the number of the service personnel in the service personnel set, which is more than a certain threshold, to the total number are weighted to be used as the order placing probability of the current order, so as to judge the order placing situation of the user.
Therefore, by using the first requirement parameter and the second requirement parameter, the rough matching processing is performed on the user in the current order data and each housekeeping service staff in the housekeeping service staff database, and then the fine matching processing is performed by using model calculation, so that the housekeeping service staff corresponding to the user can be matched more accurately, a more effective matching process can be realized, the calculation amount can be reduced, and resources can be saved.
It should be noted that the above description is only given as a preferred example, and the present invention is not limited thereto.
Next, in step S105, information of a service person is transmitted to the client according to the matching degree and a predetermined push policy.
Specifically, according to the matching degree obtained in step S104, matching housekeeping service staff is determined.
And further, transmitting the information of the matched household service personnel to a client corresponding to the user according to a preset push strategy.
More specifically, the predetermined push policy includes push time, push manner and number, push content, and a push person.
For example, after the matched housekeeping staff performs the first push, the user does not receive the push and does not place an order within a certain time, in which case, the second push is performed according to a preset push policy.
For another example, after the matched housekeeping staff performs the first push, the user receives the information within a specific time, but the housekeeping staff pushed by the user has been selected and ordered by another user when the user orders, in which case, the user performs the second push in real time to push another housekeeping staff equal to the housekeeping staff.
Preferably, the information of the service person pushed to the client is transmitted through the mobile device APP or PC application software.
In another example, according to the service staff set and the priority of each service staff, selecting the optimal service staff to return to the user in the current order data, or returning at least three home service staff ranked at the top in the service staff set to the user in the current order data, so as to provide selectable pages or pop-up pages for the user.
Therefore, the adaptation service of the user customization demand can be effectively realized, more effective push information is provided for the user, and the user experience and the ordering rate can be improved.
It should be noted that the above description is only given by way of example, and the present invention is not limited thereto.
Compared with the prior art, the method has the advantages that the housekeeping service personnel database and the user database are established, and the housekeeping service personnel, the users and the respective related characteristic data which are in dynamic change are respectively stored in real time, so that the intelligent matching process of the housekeeping service personnel can be further optimized; the user intention (namely the predicted order placing rate) of the user in the current order data can be accurately calculated, and the user with intention can be judged according to the user intention; by using the first requirement parameter and the second requirement parameter, the rough matching processing is performed on the user in the current order data and each housekeeping service person in the housekeeping service person database, and then the fine matching processing is performed by using model calculation, so that the housekeeping service person corresponding to the user can be matched more accurately, a more effective matching process can be realized, the calculation amount can be reduced, and the resources can be saved; the method and the system can effectively realize the adaptation service of the user customization demand, provide more effective push information for the user, and improve the user experience and the ordering rate.
Example 2
Embodiments of systems of the present invention are described below, which may be used to perform method embodiments of the present invention. Details described in the system embodiments of the invention should be considered supplementary to the above-described method embodiments; reference is made to the above-described method embodiments for details not disclosed in the system embodiments of the invention.
Referring to fig. 4, an intelligent matching system for home service staff according to embodiment 2 of the present invention will be described, where the intelligent matching system for home service staff includes a client and a server, and an home service staff database is established on the server to store characteristic parameters of the service staff of each home service staff; the client is used for acquiring text data of the user about the requirement of the housekeeping service; the client or the server extracts the user characteristic parameters of the user from the text data; the server matches the user characteristic parameters with characteristic parameters of all the servers in the database to calculate the matching degree of all the housekeeping service personnel and the user; and the server transmits the information of the service personnel to the client according to the matching degree and a preset push strategy.
In this example, the client or the server calculates a user intention degree according to a user characteristic parameter of the user, and matches the user characteristic parameter with each server characteristic parameter in the database only when the user intention degree satisfies a predetermined condition, so as to calculate a matching degree of each housekeeping service person with the user.
Specifically, the calculating, by the client or the server, the user intention degree according to the user characteristic parameter of the user includes: and calculating the order placing probability of the user of the current user by adopting a machine learning algorithm based on the order data of the historical user, and using the probability as the user intention.
Preferably, the matching degree of each housekeeping service personnel and the user is calculated, wherein candidate housekeeping service personnel are screened out by adopting a preset matching rule; and calculating the matching degree of each candidate housekeeping service personnel by adopting a matching degree calculation model, and taking the candidate housekeeping service personnel with the matching degree meeting the preset conditions as the matched housekeeping service personnel.
Preferably, the server further comprises a user database for storing users who require the home services and user characteristic parameters thereof, wherein the users include historical users, users newly registered for each home service product APP, current users submitting service orders, and the like.
It should be noted that the above description is only given by way of example, and the present invention is not limited thereto. In embodiment 2, the same portions as those in embodiment 1 are not described.
Those skilled in the art will appreciate that the modules in the above-described system embodiments may be distributed in the system as described, and that corresponding variations may be made in one or more systems other than the above-described embodiments. The modules of the above embodiments may be combined into one module, or further split into multiple sub-modules.
Compared with the prior art, the method has the advantages that the housekeeping service personnel database and the user database are established, and the housekeeping service personnel, the users and the respective related characteristic data which are in dynamic change are respectively stored in real time, so that the intelligent matching process of the housekeeping service personnel can be further optimized; the user intention (namely the predicted order placing rate) of the user in the current order data can be accurately calculated, and the user with intention can be judged according to the user intention; by using the first requirement parameter and the second requirement parameter, the rough matching processing is performed on the user in the current order data and each housekeeping service person in the housekeeping service person database, and then the fine matching processing is performed by using model calculation, so that the housekeeping service person corresponding to the user can be matched more accurately, a more effective matching process can be realized, the calculation amount can be reduced, and the resources can be saved; the method and the system can effectively realize the adaptation service of the user customization demand, provide more effective push information for the user, and improve the user experience and the ordering rate.
Example 3
The following describes an embodiment of the computer apparatus of the present invention, which may be considered as a concrete physical implementation of the above-described embodiments of the method and system of the present invention. Details described in relation to the computer device embodiment of the present invention should be considered supplementary to the method or system embodiment described above; for details not disclosed in the computer device embodiments of the invention, reference may be made to the above-described method or system embodiments.
Fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present invention, the computer device including a processor and a memory, the memory storing a computer-executable program, the processor executing the method of fig. 1 when the computer program is executed by the processor.
Specifically, the computer device is used as a client end which is in communication connection with a server, and an housekeeping service personnel database is established on the server to store characteristic parameters of service personnel of each housekeeping service personnel; the client is used for acquiring text data of the user about the requirement of the housekeeping service; the client or the server extracts the user characteristic parameters of the user from the text data; when the user intention degree meets a preset condition, the server matches the user characteristic parameters with the characteristic parameters of the servers in the database to calculate the matching degree of the housekeeping service personnel and the user; and the server transmits the information of the service personnel to the client according to the matching degree and a preset push strategy.
As shown in fig. 5, the computer device is in the form of a general purpose computing device. The processor can be one or more and can work together. The invention also does not exclude that distributed processing is performed, i.e. the processors may be distributed over different physical devices. The computer device of the present invention is not limited to a single entity, and may be a sum of a plurality of entity devices.
The memory stores a computer executable program, typically machine readable code. The computer readable program may be executed by the processor to enable a computer device to perform the method of the invention, or at least some of the steps of the method.
The memory may include volatile memory, such as Random Access Memory (RAM) and/or cache memory, and may also be non-volatile memory, such as read-only memory (ROM).
Optionally, in this embodiment, the computer device further includes an I/O interface, which is used for data exchange between the computer device and an external device. The I/O interface may be a local bus representing one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, and/or a memory storage device using any of a variety of bus architectures.
It should be understood that the computer device shown in fig. 5 is only one example of the present invention, and elements or components not shown in the above examples may also be included in the computer device of the present invention. For example, some computer devices also include display units such as display screens, and some computer devices also include human-computer interaction elements such as buttons, keyboards, and the like. The computer device can be considered to be covered by the present invention as long as the computer device can execute the computer readable program in the memory to implement the method of the present invention or at least part of the steps of the method.
It should be noted that the above description is only given by way of example, and the present invention is not limited thereto. In addition, in embodiment 3, the description of the same portions as those of embodiments 1 and 2 is omitted.
FIG. 6 is a schematic diagram of a computer program product of an embodiment of the invention. As shown in fig. 6, the computer program product has stored therein a computer executable program, which when executed, implements the above-described method of the present invention. The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
From the above description of the embodiments, those skilled in the art will readily appreciate that the present invention can be implemented by hardware capable of executing a specific computer program, such as the system of the present invention, and electronic processing units, servers, clients, mobile phones, control units, processors, etc. included in the system. The invention may also be implemented by computer software for performing the method of the invention, e.g. control software executed by a microprocessor, an electronic control unit, a client, a server, etc. It should be noted that the computer software for executing the method of the present invention is not limited to be executed by one or a specific hardware entity, and can also be realized in a distributed manner by non-specific hardware. For computer software, the software product may be stored in a computer readable storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or may be distributed over a network, as long as it enables the computer device to perform the method according to the present invention.
While the foregoing detailed description has described the objects, aspects and advantages of the invention in further detail, it should be appreciated that the present invention is not inherently related to any particular computer, virtual machine, or computer apparatus, as various general purpose systems may also implement the invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
Claims (15)
1. An intelligent matching method for housekeeping service personnel is characterized by comprising the following steps:
establishing an housekeeping staff database to store the characteristic parameters of the waiters of the housekeeping staff;
acquiring text data of a user about the requirement of the housekeeping service through a client;
extracting the user characteristic parameters of the user from the text data;
matching the user characteristic parameters with characteristic parameters of each service person in the database to calculate the matching degree of each housekeeping service person and the user;
and transmitting the information of the service personnel to the client according to the matching degree and a preset push strategy.
2. The intelligent matching method for housekeeping service personnel as claimed in claim 1, wherein the step of obtaining text data of the user about the housekeeping service requirement through the client comprises the steps of: the method comprises the steps of providing a text and/or voice chat tool on a client, and acquiring text data of a user about needs of the home services through the chat tool.
3. The intelligent matching method for housekeeping service personnel as claimed in claim 2, wherein the chat tool is integrated in a mobile device APP or PC-side application software for the housekeeping service.
4. The intelligent matching method for housekeeping service personnel as claimed in claim 3, wherein the information of the service personnel pushed to the client is transmitted through the mobile device APP or PC side application software.
5. The intelligent matching method for housekeeping service personnel according to any one of claims 1 to 4, wherein: the method further comprises calculating the user intention according to the user characteristic parameters of the user;
and only when the user intention meets a preset condition, matching the user characteristic parameters with the characteristic parameters of the service persons in the database to calculate the matching degree of the household service persons and the user.
6. The intelligent housekeeping service personnel matching method according to claim 5, wherein calculating the user intention according to the user characteristic parameters of the user comprises:
and calculating the order placing probability of the current user by adopting a machine learning algorithm based on the order data of the historical users, and using the probability as the user intention.
7. The intelligent housekeeping service personnel matching method of claim 6, further comprising:
acquiring current order data, and extracting user characteristic parameters from the current order data, wherein the user characteristic parameters comprise user intention characteristic data and user preference characteristic data.
8. The intelligent matching method for housekeeping service personnel according to any one of claims 1 to 4, wherein the calculating the matching degree of each housekeeping service personnel and the user comprises:
screening out candidate housekeeping service personnel by adopting a preset matching rule;
and calculating the matching degree of each candidate housekeeping service personnel by adopting a matching degree calculation model, and taking the candidate housekeeping service personnel with the matching degree meeting the preset conditions as the matched housekeeping service personnel.
9. The intelligent housekeeping service personnel matching method of claim 8, comprising:
establishing a match calculation model using a Bayesian algorithm, the match calculation model being trained using a training data set, the training data set being from at least one of: the method comprises the steps of ordering data of historical users, chatting data extracted from chatting APPs, service matching characteristic data, APP installation list data of the historical users and matched service personnel characteristic data.
10. The intelligent matching method for housekeeping service personnel as claimed in claim 8, wherein the chatting data comprises user age, taste preference, preference age section for service personnel extracted from a guided question-and-answer type interview or chatting data for judging user service requirement; and/or
The service personnel characteristic data comprises age, gender, geographic position, expert cuisine data, academic data and historical order data associated with each service personnel.
11. The utility model provides a housekeeping service personnel intelligence matching system, includes client and server, its characterized in that:
an housekeeping service personnel database is established on the server to store the characteristic parameters of the service personnel of each housekeeping service personnel;
the client is used for acquiring text data of the user about the requirement of the housekeeping service;
the client or the server extracts the user characteristic parameters of the user from the text data;
the server matches the user characteristic parameters with characteristic parameters of all the servers in the database to calculate the matching degree of all the housekeeping service personnel and the user;
and the server transmits the information of the service personnel to the client according to the matching degree and a preset push strategy.
12. The intelligent matching system for housekeeping service personnel according to claim 11, wherein the client or the server calculates a user intention degree according to a user characteristic parameter of the user, and matches the user characteristic parameter with each service personnel characteristic parameter in the database to calculate the matching degree of each housekeeping service personnel with the user only when the user intention degree satisfies a predetermined condition.
13. The intelligent housekeeping service personnel matching system of claim 12, wherein the client or server computing the user intent according to the user characteristic parameters of the user comprises:
and calculating the order placing probability of the current user by adopting a machine learning algorithm based on the order data of the historical users, and using the probability as the user intention.
14. The intelligent housekeeping service personnel matching system of claim 12, wherein said calculating the degree of matching of each housekeeping service personnel to the user comprises:
screening out candidate housekeeping service personnel by adopting a preset matching rule;
and calculating the matching degree of each candidate housekeeping service personnel by adopting a matching degree calculation model, and taking the candidate housekeeping service personnel with the matching degree meeting the preset conditions as the matched housekeeping service personnel.
15. A computer device as a client in communicative connection with a server,
an housekeeping service personnel database is established on the server to store the characteristic parameters of the service personnel of each housekeeping service personnel;
the client is used for acquiring text data of the user about the requirement of the housekeeping service;
the client or the server extracts the user characteristic parameters of the user from the text data;
the server matches the user characteristic parameters with characteristic parameters of all the servers in the database to calculate the matching degree of all the housekeeping service personnel and the user;
and the server transmits the information of the service personnel to the client according to the matching degree and a preset push strategy.
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