CN112712393A

CN112712393A - Method and device for adjusting house source price

Info

Publication number: CN112712393A
Application number: CN202110003749.1A
Authority: CN
Inventors: 张思佳; 梁志婷; 邓佳唯
Original assignee: Shanghai Minglue Artificial Intelligence Group Co Ltd
Current assignee: Shanghai Minglue Artificial Intelligence Group Co Ltd
Priority date: 2021-01-04
Filing date: 2021-01-04
Publication date: 2021-04-27

Abstract

The application discloses a method and a device for adjusting house source price. The invention comprises the following steps: the method comprises the steps of collecting conversation content in the house selling process, carrying out role separation on voice of the conversation content through a voiceprint recognition technology, converting the content matched with a second voiceprint in the conversation content into first text information, marking a plurality of labels on a house source corresponding to the first text information through a semantic analysis technology, carrying out quantitative analysis on the labels to obtain the coefficient relation between the house source price and the labels, and adjusting the reference price of the unsold house source according to the real-time change of the coefficient relation. The problem that the house price formulation in the related technology does not accord with the actual demand of the customer is solved, and the effect of flexibly adjusting the house source price according to the collected actual demand of the customer is achieved.

Description

Method and device for adjusting house source price

Technical Field

The application relates to the field of computers, in particular to a method and a device for adjusting house source prices.

Background

In the real estate pricing in the related technology, most real estate developers add prices according to the cost or compare the prices with the same party, and the traditional pricing mode is only the unilateral willingness price of the real estate developers; it is possible for a customer to have some of the premises priced beyond the budget and also to have a lower budget than the customer; the willingness interval of the client to the house price cannot be estimated, so that hot house resources are robbed or part of house resources are lost;

aiming at the problem that the house price formulation in the related technology does not meet the actual requirements of customers, an effective solution is not provided at present.

Disclosure of Invention

The application mainly aims to provide a method and a device for adjusting house source price so as to solve the problem that the house price formulation in the related technology does not meet the actual requirements of customers.

To achieve the above object, according to one aspect of the present application, there is provided a method of adjusting a price of a house source. The invention comprises the following steps: collecting conversation contents of a sales role and a customer role in a house source sales process, carrying out voiceprint recognition on the conversation contents, matching a recognition result with a pre-stored first voiceprint characteristic of the sales role, and separating a second voiceprint characteristic of the customer role; converting the content matched with the second voice print in the conversation content into first text information, marking a plurality of labels on a corresponding room source of the first text information through a semantic analysis technology, and performing associated storage on the first text information and the corresponding room source; aggregating and quantifying the plurality of labels, and performing linear regression analysis after aiming at the sold house source to obtain the coefficient relation between the house source price and the plurality of labels; and adjusting the reference price of the unsold house source according to the coefficient relation.

There is also provided, in accordance with another embodiment of the present application, an apparatus for adjusting a price of a house source, including: the separation module is used for collecting conversation contents of a sales role and a customer role in the house source sales process, carrying out voiceprint recognition on the conversation contents, matching the recognition result with a pre-stored first voiceprint characteristic of the sales role and separating a second voiceprint characteristic of the customer role; the storage module is used for converting the content matched with the second voice print in the conversation content into first text information, marking a plurality of labels on corresponding house sources of the first text information through a semantic analysis technology, and storing the first text information and the corresponding house sources in an associated manner; the acquisition coefficient module is used for aggregating and quantifying the plurality of labels, and performing linear regression analysis after aiming at the sold house source to obtain the coefficient relation between the house source price and the plurality of labels; and the adjusting module is used for adjusting the reference price of the unsold house source according to the coefficient relation.

According to the method and the device, conversation content in the house sale process is collected, the voice of the conversation content is subjected to role separation through a voiceprint recognition technology, the content matched with a second voiceprint in the conversation content is converted into first text information, a plurality of labels are marked on a house source corresponding to the first text information through a semantic analysis technology, then the plurality of labels are subjected to quantitative analysis, coefficient relations between the house source price and the plurality of labels are obtained, and the reference price of the unsold house source is adjusted according to real-time changes of the coefficient relations. The problem that the house price formulation in the related technology does not accord with the actual demand of the customer is solved, and the effect of flexibly adjusting the house source price according to the collected actual demand of the customer is achieved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:

FIG. 1 is a flow chart of a method of adjusting a price of a house source according to an embodiment of the present application; and

fig. 2 is a flowchart of a method of a mobile terminal and a server according to an embodiment of the present application;

fig. 3 is a schematic diagram of an apparatus for adjusting a price of a house source according to an embodiment of the present application.

Detailed Description

It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.

In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

For convenience of description, some terms or expressions referred to in the embodiments of the present application are explained below:

according to the method and the system, the willingness of a customer to each dimension of different house sources in the process of communicating with the customer can be accurately extracted according to the correlation between the intelligent voice technology and the price adjusting system in the related technology, and reference pricing is given to price adjustment of different influence factors in proportion through the price adjusting system.

According to an embodiment of the present application, a method of adjusting a price of a house source is provided.

Fig. 1 is a flow chart of a method of adjusting a price of a house source according to an embodiment of the present application. As shown in fig. 1, the present invention comprises the steps of:

step S101, collecting conversation contents of a sales role and a customer role in a house source sales process, carrying out voiceprint recognition on the conversation contents, matching a recognition result with a pre-stored first voiceprint characteristic of the sales role, and separating a second voiceprint characteristic of the customer role;

the scheme can be used in the scenes of house sale or house lease, and the specific implementation environment can be the positions of building sales places and the like.

Optionally, before the conversation content of the sales role and the customer role in the house source sales process is collected, receiving a control signal input by a target object; and opening a voice acquisition function of the terminal according to the control signal, wherein the terminal is worn by the sales role.

Optionally, the terminal is configured with a peripheral button, and when the button is pressed at the beginning of the conversation, the conversation voice information is collected.

Step S102, converting the content matched with the second voice print in the conversation content into first text information, marking a plurality of labels for the corresponding house sources of the first text information through a semantic analysis technology, and performing associated storage on the first text information and the corresponding house sources; and marking corresponding labels on the text information of the customers through a set label system, importing the text information into a pricing system, and matching corresponding house resources.

Processing the voice information, and when the voice information has voiceprint characteristics matched with the voiceprint characteristics of the sales role pre-stored in the voiceprint model, separating the voiceprint of the customer role and converting the voice into text information through ASR;

optionally, marking a plurality of labels for the corresponding house sources of the first text information by a semantic analysis technology, including: performing semantic analysis on the first text information to obtain a plurality of labels, wherein the labels are at least used for describing one of the following characteristics of the corresponding house source: traffic status, floor, property service, developer rating.

Optionally, the associating and storing the first text information and the corresponding house source includes: and storing the first text information and the plurality of labels to a knowledge graph of the house source price.

Step S103, aggregating and quantifying the plurality of labels, and performing linear regression analysis after aiming at the sold house source to obtain the coefficient relation between the house source price and the plurality of labels;

optionally, multiple tags are categorized and then quantified in aggregate.

And step S104, adjusting the reference price of the unsold house source according to the coefficient relation.

Optionally, after adjusting the reference price of the unsold house source according to the coefficient relationship, the method further includes: after the unsold house source is sold, optimizing the coefficient relation between the house source price and the plurality of labels by using the difference between the selling price and the reference price.

The scheme provides a method for processing the text with the labels based on the intelligent voice, which is characterized in that after the voice of a client is transcribed into the text by information communicated and communicated between a sales role and the client through a role separation and transcription technology, the processed text with the labels is imported into a pricing system according to an established label system, the text labels are split and clustered according to the influence factors of the room price, each influence factor is quantized to give a weight, and finally, the pricing system gives final reference pricing. The influence factor weight and the final reference pricing are matched with the house resources and provided for real estate openers, so that the house resources can be sold with larger profits better from the perspective of customers and in combination with actual pricing.

Fig. 2 is a flowchart of a method of a mobile terminal and a server according to an embodiment of the present application, and as shown in fig. 2, the mobile terminal performs the following processes:

(1) step of voice acquisition

Voice collection is used to automatically collect voice information.

(2) Step of speech processing

Including preliminary speech processing such as noise removal, etc.

(3) Voiceprint recognition

Marketing role voiceprint information can be identified.

(4) Role separation

And separating the voiceprints of the sales role and the customer role, thereby realizing role separation.

(5) Conversion to text information

And converting the voice information of the customer into the text information.

(6) Data transmission

And after the voiceprint information of the customer is converted into text information, transmitting the text information to the server side.

The server side is provided with:

(7) label knowledge base system

And importing the text information into the established label knowledge base system, and marking corresponding house price influence factor labels, such as traffic conditions, floor heights, property services, developer credit levels and the like.

(8) Matching house source

And matching the sold and unsold house sources with the texts and the labels through the text information and the house source sales records.

(9) And generating a factor relation between the label and the house source price.

And quantifying the label of the sold house source, and continuously inputting the received text information and the label, so that the obtained factor coefficient of the linear regression model is more accurate.

(10) And inputting the unsold house source into a pricing system to obtain a reference price.

And combining the existing linear regression model with the quantized label of the unsold house source to obtain the reference pricing of the unsold house source for the reference pricing of the developer.

By adopting the method flow of the mobile terminal and the server, the information fed back by the client is accurately captured and applied, the pricing is carried out from the perspective of customers for real estate developers, and real estate sources are better sold.

It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.

The embodiment of the present application further provides a device for adjusting a house source price, and it should be noted that the device for adjusting a house source price of the embodiment of the present application can be used to execute the method for adjusting a house source price provided by the embodiment of the present application. The following describes an apparatus for adjusting the price of a house source according to an embodiment of the present application.

Fig. 3 is a schematic diagram of an apparatus for adjusting a price of a house source according to an embodiment of the present application. As shown in fig. 3, the apparatus includes:

a separation module 32, configured to collect conversation contents of a sales role and a customer role in a house source sales process, perform voiceprint recognition on the conversation contents, match a recognition result with a pre-stored first voiceprint feature of the sales role, and separate a second voiceprint feature of the customer role;

a storage module 34, configured to convert content in the conversation content that matches the second voiceprint into first text information, print a plurality of tags on a corresponding room source of the first text information through a semantic analysis technique, and store the first text information and the corresponding room source in an associated manner;

the obtaining coefficient module 36 is configured to perform aggregation and quantization on the multiple tags, and perform linear regression analysis on the sold house resources to obtain a coefficient relationship between the house resource price and the multiple tags;

and the adjusting module 38 is used for adjusting the reference price of the unsold house source according to the coefficient relation.

Optionally, the separation module 32 is further configured to receive a control signal input by the target object before the collecting of the conversation content of the sales character and the customer character in the house source sales process; and a voice acquisition function for opening the terminal according to the control signal, wherein the terminal is worn by the sales character.

Optionally, the storage module 34 is further configured to perform semantic analysis on the first text information to obtain a plurality of tags, where the tags are at least used for describing one of the following features of the corresponding house source: traffic status, floor, property service, developer rating.

Optionally, the storage module 34 is further configured to store the first text information and the plurality of labels to a knowledge graph of house source prices.

Optionally, after adjusting the reference price of the unsold house source according to the coefficient relationship, the adjusting module 38 is further configured to optimize the coefficient relationship between the house source price and the plurality of tags using the difference between the sold price and the reference price after the unsold house source is sold.

The device for adjusting the house source price comprises a processor and a memory, wherein the separation module 32, the storage module 34, the obtaining coefficient module 36, the adjusting module 38 and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.

The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to be one or more than one, the problem that the house price formulation in the related technology does not conform to the actual needs of the customer is solved by adjusting the kernel parameters, and the effect of flexibly adjusting the house source price according to the acquired actual needs of the customer is achieved.

The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.

An embodiment of the present application provides a storage medium, on which a program is stored, which when executed by a processor implements the method for adjusting a price of a house source.

The embodiment of the application provides a processor, wherein the processor is used for running a program, and the program executes the Z method during running.

The embodiment of the application provides equipment, the equipment comprises a processor, a memory and a program which is stored on the memory and can run on the processor, and the following steps are realized when the processor executes the program: collecting conversation contents of a sales role and a customer role in a house source sales process, carrying out voiceprint recognition on the conversation contents, matching a recognition result with a pre-stored first voiceprint characteristic of the sales role, and separating a second voiceprint characteristic of the customer role; converting the content matched with the second voice print in the conversation content into first text information, marking a plurality of labels on a corresponding room source of the first text information through a semantic analysis technology, and performing associated storage on the first text information and the corresponding room source; aggregating and quantifying the plurality of labels, and performing linear regression analysis after aiming at the sold house source to obtain the coefficient relation between the house source price and the plurality of labels; and adjusting the reference price of the unsold house source according to the coefficient relation. The device herein may be a server, a PC, a PAD, a mobile phone, etc.

The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: collecting conversation contents of a sales role and a customer role in a house source sales process, carrying out voiceprint recognition on the conversation contents, matching a recognition result with a pre-stored first voiceprint characteristic of the sales role, and separating a second voiceprint characteristic of the customer role; converting the content matched with the second voice print in the conversation content into first text information, marking a plurality of labels on a corresponding room source of the first text information through a semantic analysis technology, and performing associated storage on the first text information and the corresponding room source; aggregating and quantifying the plurality of labels, and performing linear regression analysis after aiming at the sold house source to obtain the coefficient relation between the house source price and the plurality of labels; and adjusting the reference price of the unsold house source according to the coefficient relation.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.

The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method of adjusting a price of a house source, comprising:

collecting conversation contents of a sales role and a customer role in a house source sales process, carrying out voiceprint recognition on the conversation contents, matching a recognition result with a pre-stored first voiceprint characteristic of the sales role, and separating a second voiceprint characteristic of the customer role;

converting the content matched with the second voice print in the conversation content into first text information, marking a plurality of labels on a corresponding room source of the first text information through a semantic analysis technology, and performing associated storage on the first text information and the corresponding room source;

aggregating and quantifying the plurality of labels, and performing linear regression analysis after aiming at the sold house source to obtain the coefficient relation between the house source price and the plurality of labels;

and adjusting the reference price of the unsold house source according to the coefficient relation.

2. The method of claim 1, wherein prior to collecting conversational content of the sales character and the customer character during the house-source sales process, the method further comprises:

receiving a control signal input by a target object;

and opening a voice acquisition function of the terminal according to the control signal, wherein the terminal is worn by the sales role.

3. The method of claim 1, wherein tagging corresponding sources of the first textual information by semantic analysis techniques comprises:

performing semantic analysis on the first text information to obtain a plurality of labels, wherein the labels are at least used for describing one of the following characteristics of the corresponding house source: traffic status, floor, property service, developer rating.

4. The method of claim 3, wherein storing the first text message in association with the corresponding house source comprises:

and storing the first text information and the plurality of labels to a knowledge graph of the house source price.

5. The method of claim 1, wherein after adjusting the reference price of the unsold source according to the coefficient relationship, the method further comprises:

after the unsold house source is sold, optimizing the coefficient relation between the house source price and the plurality of labels by using the difference between the selling price and the reference price.

6. An apparatus for adjusting the price of a house source, comprising:

the separation module is used for collecting conversation contents of a sales role and a customer role in the house source sales process, carrying out voiceprint recognition on the conversation contents, matching the recognition result with a pre-stored first voiceprint characteristic of the sales role and separating a second voiceprint characteristic of the customer role;

the storage module is used for converting the content matched with the second voice print in the conversation content into first text information, marking a plurality of labels on corresponding house sources of the first text information through a semantic analysis technology, and storing the first text information and the corresponding house sources in an associated manner;

the acquisition coefficient module is used for aggregating and quantifying the plurality of labels, and performing linear regression analysis after aiming at the sold house source to obtain the coefficient relation between the house source price and the plurality of labels;

and the adjusting module is used for adjusting the reference price of the unsold house source according to the coefficient relation.

7. The apparatus of claim 6, wherein the separation module is further configured to receive a control signal input by the target object before the collecting of the conversation content of the sales character and the customer character in the house source sales process; and a voice acquisition function for opening the terminal according to the control signal, wherein the terminal is worn by the sales character.

8. The apparatus of claim 6, wherein the storage module is further configured to perform semantic analysis on the first text information to obtain a plurality of tags, wherein the plurality of tags are at least used for describing one of the following characteristics of the corresponding house source: traffic status, floor, property service, developer rating.

9. A "computer-readable storage medium" or "non-volatile storage medium", wherein the "computer-readable storage medium" or "non-volatile storage medium" includes a stored program, and when the program runs, the apparatus in which the "computer-readable storage medium" or "non-volatile storage medium" is controlled performs the method for adjusting the house source price according to any one of claims 1 to 5.

10. A processor, characterized in that the processor is configured to run a program, wherein the program when running performs the method of adjusting a price of a house source according to any one of claims 1 to 5.