CN112907265A - Client type detection method, device and equipment - Google Patents
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Abstract
A client type detection method comprises the following steps: acquiring facial features of a second client who allies with a pre-registered first client to purchase a house; searching a first visiting client matched with the facial features of the second client in a pre-collected live image; acquiring the earliest visiting time of the matched first visiting client; and if the earliest visiting time of the first visiting client is earlier than the registration time of the first client, generating a prompt message that the first client is the self visitor user, so that the client type can be more effectively detected.
Description
Technical Field
The application belongs to the technical field of real estate, and particularly relates to a client type detection method, device and equipment.
Background
Along with the improvement of the social living standard, the housing level of people is greatly improved. The land manufacturers provide good living environment for people by building new buildings. In the process of trading a new real estate building, in order to improve the building trading efficiency, a business consultant such as a real estate agent or a broker is encouraged to buy the building through a channel brought by clients in a reward mode, namely, when the trading client is a channel client, the business consultant is given certain reward.
In order to obtain the reward, the employment counselor often intercepts a visiting customer who visits in advance, that is, a customer attracted by the publicity of the house-site manufacturer itself, as a channel customer and registers by registering a person related to the intercepted visiting customer, and when the customer type is judged by taking a snapshot, since the visiting time of the registered person is later than the registration time, the customer type may not be accurately judged.
Disclosure of Invention
In view of this, embodiments of the present application provide a method, an apparatus, and a device for detecting a client type, so as to solve the problem in the prior art that when a business counselor intercepts a visiting client and registers the visiting client through a relevant person, the client type cannot be accurately identified through image capturing.
A first aspect of an embodiment of the present application provides a client type detection method, where the client type detection method includes:
acquiring facial features of a second client who allies with a pre-registered first client to purchase a house;
searching a first visiting client matched with the facial features of the second client in a pre-collected live image;
acquiring the earliest visiting time of the matched first visiting client;
and if the earliest visiting time of the first visiting client is earlier than the registration time of the first client, generating prompt information that the first client is a visiting client.
With reference to the first aspect, in a first possible implementation manner of the first aspect, the step of acquiring a second client affiliated with a pre-registered first client to purchase a house includes:
determining one or more homeowners in the house purchase transaction information;
when the house owner in the house purchase transaction information is one and the house owner is different from the pre-registered first customer, determining that the house owner is the second customer;
and when the house owners in the house purchasing transaction information are multiple, searching one or more house owners different from the first customer from the multiple house owners, and determining the searched one or more house owners as second customers.
With reference to the first aspect, in a second possible implementation manner of the first aspect, the method further includes:
when a first client purchases a house independently, acquiring local features of the face of the first client;
searching a second client matched with the local characteristics of the face of the first client in a pre-collected live image;
when a matched second visiting client exists, obtaining the earliest visiting time of the second visiting client;
and if the earliest visiting time of the second visiting client is earlier than the registration time of the first client, generating prompt information that the first client is the self-visiting client.
With reference to the second possible implementation manner of the first aspect, in a third possible implementation manner of the first aspect, the local feature of the face includes one or more of an eye feature, a nose feature, a mouth feature, a face feature, a forehead feature and an ear feature.
With reference to the first aspect, in a fourth possible implementation manner of the first aspect, the method further includes:
acquiring relationship data of the first customer or the second customer;
determining the facial features of the relatives and friends of the first customer or the second customer according to the relationship data;
searching a third visiting client matched with the facial features of the relatives and friends in a pre-collected live image;
when a third matched visiting client exists, obtaining the earliest visiting time of the third visiting client;
and if the earliest visiting time of the third visiting client is earlier than the registration time of the first client, generating prompt information that the first client is the visiting client.
With reference to the fourth possible implementation manner of the first aspect, in a fifth possible implementation manner of the first aspect, the step of obtaining the relationship data of the first client or the second client includes:
acquiring social information of a first client or a second client;
determining relationship data of the first client or the second client according to social information of the first client or the second client.
With reference to the fifth possible implementation manner of the first aspect, in a sixth possible implementation manner of the first aspect, the step of obtaining social information of the first client or the second client includes:
acquiring a corresponding social contact account number according to the mobile phone number of the first customer or the second customer;
according to the social number or the social information of the first client or the second client.
A second aspect of an embodiment of the present application provides a client type detection apparatus, including:
the face feature acquisition unit is used for acquiring the face feature of a second client who allies with a pre-registered first client to purchase a house;
the matching unit is used for searching a first visiting client matched with the facial features of the second client in a pre-collected live image;
the visiting time acquiring unit is used for acquiring the earliest visiting time of the matched first visiting client;
a prompt information generating unit, configured to generate prompt information that the first client is a self-visiting client if an earliest visiting time of the first visiting client is earlier than a registration time of the first client.
A third aspect of embodiments of the present application provides a client type detection device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the client type detection method according to any one of the first aspect when executing the computer program.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium, which stores a computer program, wherein the computer program, when executed by a processor, implements the steps of the client type detection method according to any one of the first aspect.
Compared with the prior art, the embodiment of the application has the advantages that: in the house-purchasing transaction information, if a second client and a first client registered in advance are jointly purchased, the facial feature of the second client is obtained, a first visiting client is matched in a pre-collected live image through the facial feature of the second client, if the first visiting client is matched, the earliest visiting time of the first visiting client is obtained and compared with the registration time of the first client, and if the earliest visiting time of the first visiting client is earlier than the registration time of the first client, the first client is probably the second client intercepted by the consultant, so that the client type can be detected more effectively.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart illustrating an implementation of a client type detection method according to an embodiment of the present application;
fig. 2 is a schematic flow chart illustrating an implementation of a method for determining a second client according to an embodiment of the present application;
fig. 3 is a schematic flow chart illustrating an implementation of another client type detection method provided in an embodiment of the present application;
FIG. 4 is a flowchart illustrating an implementation of a method for detecting a client type according to relationship data according to an embodiment of the present application;
FIG. 5 is a schematic diagram of a client type detection apparatus provided in an embodiment of the present application;
fig. 6 is a schematic diagram of a client type detection device provided in an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
Fig. 1 is a schematic flow chart of an implementation of a client type detection method provided in an embodiment of the present application, which is detailed as follows:
in step S101, a facial feature of a second client who allies with a pre-registered first client to purchase a house is acquired;
specifically, the method and the system are mainly used for detecting the problem that when the real estate developer sells a house, part of clients attracted by propaganda of the real estate developer, namely channel clients intercepted as a business counselor by visitors, are blocked. The visiting client is a client which is not guided by a business consultant and goes to a building selling site for building purchase. The channel client refers to a client for purchasing a house brought by the drainage of a business consultant. In order to distinguish channel clients from visiting clients, the presence advisor needs to register the channel clients before the channel clients visit their premises, i.e., the channel clients' profile information needs to be registered before the channel clients arrive on site, and unregistered site clients are identified as visiting clients.
Wherein the first client is a client registered by a presence advisor. The second client is a client who has made a transaction according to the first client contact name registered by the aforementioned consulting agent. The joint name may be registration information of the first client, and the second client and the first client together serve as a house purchaser, or may be registration information of the first client and the second client alone serve as the house purchaser.
Wherein, the step of acquiring the second customer for purchase in connection with the pre-registered first customer may be as shown in fig. 2, including:
in step S101, determining one or more homeowners in the house purchase transaction information;
one or more homeowners who purchase the premises, i.e., the house purchasers for one or more sets of premises in a transaction corresponding to the first client registered by the live advisor, may be determined from the house purchase contract or the property registration information.
In step S102, when one house owner is in the house purchase transaction information and the house owner is different from the pre-registered first customer, determining that the house owner is the second customer;
and if the house owners in the house purchasing transaction information are one and the house owners are different from the pre-registered first customers, determining that the second customer is the house owner in the house purchasing transaction information. In this case, the presence advisor may improve the evidence of the association between the first client and the second client, such as a couple relationship, a parent-child relationship, etc.
In step S203, when there are a plurality of owners in the house purchase transaction information, one or more owners different from the first customer are searched from the plurality of owners, and the searched one or more owners are determined as the second customer.
If the house owners in the house purchasing transaction information comprise a plurality of house owners, screening can be performed according to the plurality of house owners, first customers included in the plurality of house owners are screened, and one or more screened house owners are obtained and serve as second customers.
Through the confirmation of the second client shown in fig. 2, the information of the house owner, which is not the first client, in the house purchase transaction information can be obtained, and the facial image of the second client can be obtained at the time of transaction, and the facial feature of the second client can be obtained through analysis.
In step S102, a first visiting client matching with the facial feature of the second client is searched in a pre-collected live image;
the live image can comprise a live image at a building sale place and the like. The face recognition can be performed on the acquired live images in advance to obtain the number of people included in the live images, and the corresponding relation between each person in the live images and the face features can be established. When a matching instruction is received, matching the facial features of a second client with the facial features in the pre-collected live image, and determining a first visiting client in the live image matched with the second client.
For example, the face features in the live image may be compared with the face features of the second client through comparison of face similarity, the similarity between the face of the second client and the face in the live image may be determined, and it may be determined whether the two are the same person through a preset similarity threshold, and if the similarity between the two is greater than the similarity threshold, the matching object in the live image may be determined as the first visited client.
In step S103, obtaining the earliest visiting time of the matched first visiting client;
according to the image of the first visiting client which is matched with the face feature of the second client possibly matched in the live image when the live image is subjected to portrait matching, the multiple visiting times of the first visiting client can be determined according to the shooting time corresponding to the matched visiting image. Comparing the plurality of visiting times may determine an earliest visiting time of the first visiting client.
In step S104, if the earliest visiting time of the first visiting client is earlier than the registration time of the first client, a prompt message that the first client is a visiting client is generated.
And comparing the earliest visiting time of the first visiting client with the registration time of the first client, wherein if the earliest visiting time of the first visiting client is later than the registration time of the first client and the second client is in close relationship with the first client, the registered first client is a channel client. If the registration time of the first customer is later than the earliest visiting time of the first visiting customer, the registered first customer is an intercepted customer, and a prompt that the first customer is a visiting customer can be generated and can be checked and confirmed by staff.
When a second client and a pre-registered first client are jointly purchased, the facial features of the second client are acquired, a first visiting client is matched in a pre-collected live image through the facial features of the second client, if the first visiting client is matched, the earliest visiting time of the first visiting client is acquired and compared with the registration time of the first client, and if the earliest visiting time of the first visiting client is earlier than the registration time of the first client, the first client is probably the second client intercepted by a service advisor, so that the client type can be more effectively detected.
In an embodiment, as shown in fig. 3, the client type identification method according to the present application may further include:
in step S301, when a house is purchased separately by a first client, local features of a face of the first client are acquired;
the first client purchases rooms separately, and the house owner in the room purchase transaction information is the same as the pre-registered first client. To determine whether the first customer is a valid channel customer, local features of the first customer's face may be obtained, and the first customer is verified based on the local features of the first customer's face.
Wherein the local features of the first customer's face may include one or more of eye features, nose features, mouth features, face features, forehead features, ear features. By decomposing the facial features of the first client into a plurality of local features, the face in the field image can be more effectively matched, and the portrait with the same or similar partial features can be obtained.
In step S302, a second client matching the local feature of the face of the first client is searched for in a pre-captured live image;
matching the pre-captured live image with the local features of the first client's face allows for finding a portrait that matches the local features of the first client's face. For example, similarity calculation is performed through local features, such as eye features or nose features, in a pre-acquired live image, if the similarity of the matched local features is greater than a predetermined value, it may be considered that the local features of the face of the first client are matched with the local features of the portrait in the live image, and a second visiting client corresponding to the matched portrait is obtained. If the local feature of the face of the second visiting client is the same as the local feature of the face of the first client, the second visiting client may have a certain blood relationship with the first client.
In step S303, when there is a matching second visiting client, obtaining the earliest visiting time of the second visiting client;
when the visiting images of a plurality of second visiting clients are acquired, a plurality of visiting times of the second visiting clients can be determined according to the acquisition time of the field images, and the earliest visiting time of the second visiting clients can be found through comparison.
In step S304, if the earliest visiting time of the second visiting client is earlier than the registration time of the first client, a prompt message that the first client is a visiting client is generated.
If the earliest visiting time of the second visiting client is earlier than the registration time of the first client, the second visiting client which is relatively close to the first client is shown to visit before the registration time, the second visiting client may be the visiting client intercepted by the professional consultant, the information that the first client is the client after interception and replacement can be generated, and prompt information that the first client is the visiting client can be generated and verified and confirmed by staff.
In an embodiment of the present application, as shown in fig. 4, the verifying the client type through relationship data may further include:
in step S401, obtaining relationship data of the first customer or the second customer;
wherein the relationship data may be obtained from social information of the first client and the second client. The social information may be used to search for a corresponding social account number according to the mobile phone number of the first customer or the second customer, or to determine the social account number of the first customer or the second customer according to social data filled in by the first customer or the second customer.
In step S402, determining the facial features of the relatives and friends of the first customer or the second customer according to the relationship data;
according to the relationship data, for example, according to the social relationship data of the first client or the second client, a close friend having a close relationship with the first client or the second client is determined, and the facial features of the close friend having an affinity value with the first client or the second client greater than a predetermined affinity threshold value are further obtained.
In step S403, a third visiting client matching the facial features of the relatives and friends is searched for in a pre-collected live image;
and performing feature matching with a pre-acquired live image according to the facial features of the relatives and friends determined according to the relationship data, and determining whether the relatives and friends of the first client or the second client appear in the live image.
In step S404, when there is a matching third visiting client, obtaining the earliest visiting time of the third visiting client;
when the facial features of the relatives and friends are matched with a third visiting client, the relatives and friends of the first client or the second client exist in the live image, and the earliest visiting time of the third visiting client can be determined according to the live image.
In step S405, if the earliest visiting time of the third visiting client is earlier than the registration time of the first client, generating a prompt message that the first client is the visiting client.
If the earliest visiting time of the third visiting client is earlier than the registration time of the first client, indicating that the first client is a client that may be intercepted by a live advisor, a prompt may be generated that the first client is a visiting client for further verification processing by the staff member.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Fig. 5 is a schematic structural diagram of a client type detection apparatus according to an embodiment of the present application, which is detailed as follows:
the client type detection device comprises:
a facial feature acquisition unit 501 for acquiring a facial feature of a second client who allies with a pre-registered first client to purchase a house;
a matching unit 502, configured to search a pre-acquired live image for a first visiting client that matches the facial feature of the second client;
a visit time obtaining unit 503, configured to obtain the earliest visit time of the matched first visiting client;
a prompt information generating unit 504, configured to generate prompt information that the first visiting client is a visiting client if an earliest visiting time of the first visiting client is earlier than a registration time of the first client.
The client type detection apparatus shown in fig. 5 corresponds to the client type detection method shown in fig. 1.
Fig. 6 is a schematic diagram of a client type detection device according to an embodiment of the present application. As shown in fig. 6, the client type detection apparatus 6 of this embodiment includes: a processor 60, a memory 61 and a computer program 62, such as a client type detection program, stored in said memory 61 and executable on said processor 60. The processor 60, when executing the computer program 62, implements the steps in the various client type detection method embodiments described above. Alternatively, the processor 60 implements the functions of the modules/units in the above-described device embodiments when executing the computer program 62.
Illustratively, the computer program 62 may be partitioned into one or more modules/units that are stored in the memory 61 and executed by the processor 60 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 62 in the client type detection device 6. For example, the computer program 62 may be divided into:
the face feature acquisition unit is used for acquiring the face feature of a second client who allies with a pre-registered first client to purchase a house;
the matching unit is used for searching a first visiting client matched with the facial features of the second client in a pre-collected live image;
the visiting time acquiring unit is used for acquiring the earliest visiting time of the matched first visiting client;
a prompt information generating unit, configured to generate prompt information that the first client is a self-visiting client if an earliest visiting time of the first visiting client is earlier than a registration time of the first client.
The client type detection device 6 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The client type detection device may include, but is not limited to, a processor 60, a memory 61. It will be appreciated by those skilled in the art that fig. 6 is merely an example of a client type detection device 6 and does not constitute a limitation of the client type detection device 6 and may comprise more or less components than those shown, or some components may be combined, or different components, e.g. the client type detection device may also comprise input output devices, network access devices, buses, etc.
The Processor 60 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 61 may be an internal storage unit of the client type detection device 6, such as a hard disk or a memory of the client type detection device 6. The memory 61 may also be an external storage device of the client type detection device 6, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the client type detection device 6. Further, the memory 61 may also include both an internal storage unit and an external storage device of the client type detection device 6. The memory 61 is used for storing the computer program and other programs and data required by the client type detection device. The memory 61 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A client type detection method, characterized in that the client type detection method comprises:
acquiring facial features of a second client who allies with a pre-registered first client to purchase a house;
searching a first visiting client matched with the facial features of the second client in a pre-collected live image;
acquiring the earliest visiting time of the matched first visiting client;
and if the earliest visiting time of the first visiting client is earlier than the registration time of the first client, generating prompt information that the first client is a visiting client.
2. The client type detection method according to claim 1, wherein the step of acquiring a second client affiliated with the first client registered in advance to purchase a house comprises:
determining one or more homeowners in the house purchase transaction information;
when the house owner in the house purchase transaction information is one and the house owner is different from the pre-registered first customer, determining that the house owner is the second customer;
and when the house owners in the house purchasing transaction information are multiple, searching one or more house owners different from the first customer from the multiple house owners, and determining the searched one or more house owners as second customers.
3. The customer type detection method according to claim 1, wherein the method further comprises:
when a first client purchases a house independently, acquiring local features of the face of the first client;
searching a second client matched with the local characteristics of the face of the first client in a pre-collected live image;
when a matched second visiting client exists, obtaining the earliest visiting time of the second visiting client;
and if the earliest visiting time of the second visiting client is earlier than the registration time of the first client, generating prompt information that the first client is the self-visiting client.
4. The client type detection method according to claim 3, wherein the local features of the face include one or more of eye features, nose features, mouth features, face features, forehead features, ear features.
5. The customer type detection method according to claim 1, wherein the method further comprises:
acquiring relationship data of the first customer or the second customer;
determining the facial features of the relatives and friends of the first customer or the second customer according to the relationship data;
searching a third visiting client matched with the facial features of the relatives and friends in a pre-collected live image;
when a third matched visiting client exists, obtaining the earliest visiting time of the third visiting client;
and if the earliest visiting time of the third visiting client is earlier than the registration time of the first client, generating prompt information that the first client is the visiting client.
6. The client type detection method according to claim 5, wherein the step of obtaining relationship data of the first client or the second client comprises:
acquiring social information of a first client or a second client;
determining relationship data of the first client or the second client according to social information of the first client or the second client.
7. The client type detection method according to claim 6, wherein the step of obtaining social information of the first client or the second client comprises:
acquiring a corresponding social contact account number according to the mobile phone number of the first customer or the second customer;
according to the social number or the social information of the first client or the second client.
8. A client type detection apparatus, characterized in that the client type detection apparatus comprises:
the face feature acquisition unit is used for acquiring the face feature of a second client who allies with a pre-registered first client to purchase a house;
the matching unit is used for searching a first visiting client matched with the facial features of the second client in a pre-collected live image;
the visiting time acquiring unit is used for acquiring the earliest visiting time of the matched first visiting client;
a prompt information generating unit, configured to generate prompt information that the first client is a self-visiting client if an earliest visiting time of the first visiting client is earlier than a registration time of the first client.
9. A client type detection device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor implements the steps of the client type detection method according to any one of claims 1 to 7 when executing said computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the client type detection method according to any one of claims 1 to 7.
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