Intention type analysis method and device, electronic equipment and vehicle

Abstract

The invention discloses an intention type analysis method and device, electronic equipment and a vehicle, and relates to the technical field of automobile information mining. The method comprises the following steps: acquiring intention information of a user for different vehicle types at different time stages; calculating an intention analysis parameter by using the intention information, performing time dimension analysis by using the intention analysis parameter, and calculating intention values of the user for different vehicle types; and determining an intention type of the user based on the intention value. Compared with the prior art, the method has the advantages that time dimension analysis is performed on the intention information of different vehicle types at different time stages in the sales process, the intention value is calculated, and then the intention type of the user is determined, so that the problem that the user intention cannot be analyzed and compared from the perspective of timeliness in the current intention type analysis method is solved; therefore, the problem that the analysis result is inaccurate is solved, and the intention recognition accuracy is improved.

Description

Technical Field

[0001] The present application relates to the technical field of automobile information mining, and in particular to an intention type analysis method, device, electronic equipment and vehicle. Background Art

[0002] In the process of car sales, the user's pre-purchased car model is called the pre-purchase car model intention. The commonly used intent type analysis method is usually based on historical log construction model or user tags or text word vectors to perform intent type analysis. However, in the actual process, the car model that the user has queried and test-driven is not necessarily the car model that the user finally purchased, which will cause intention judgment errors, leading to user complaints or user loss. In other words, the current intent type analysis methods lack analysis and comparison of user intentions from the perspective of timeliness, resulting in inaccurate analysis results. Summary of the invention

[0003] In view of this, the present application provides an intent type analysis method, device, electronic device and vehicle, which can improve the problem that current intent type analysis methods lack analysis and comparison of user intentions from a timeliness perspective, thereby leading to inaccurate analysis results.

[0004] In a first aspect, the present application provides an intent type analysis method, comprising:

[0005] Obtain information about users' intentions for different models at different time stages;

[0006] Calculating intention analysis parameters using the intention information, and performing time dimension analysis using the intention analysis parameters to calculate the user's intention values ​​for different vehicle models;

[0007] Based on the intent value, the user's intent type is determined.

[0008] Optionally, obtaining the user's intention information for different car models includes: querying the user's attention time for the car model within a preset time period and the release time of the car model.

[0009] Optionally, the intention analysis parameters include a first time interval and a second time interval;

[0010] The method of using the intention information to calculate the intention analysis parameters, and using the intention analysis parameters to perform time dimension analysis to calculate the user's intention values ​​for different car models, includes: calculating the difference between each time the user pays attention to the same car model and the first time the user pays attention to the same car model, as the first time interval; calculating the difference between the user's most recent attention to the same car model and the release time of the car model, as the second time interval; taking all the first time intervals and the second time intervals as inputs of the intention analysis function to calculate the user's intention value for the car model.

[0011] Optionally, determining the user's intention type based on the intention value includes: determining the user's intention type based on the vehicle type with the highest intention value.

[0012] Optionally, after determining the user's intention type based on the intention value, the method further includes: collecting the user's current vehicle-related information; and modifying the intention type based on the vehicle-related information; wherein the vehicle-related information includes at least one of the user's existing vehicle models, the user's vehicle demand scenarios, purchase requirements, and test drive satisfaction with different vehicle models.

[0013] Optionally, the intention type is modified based on the response information, including: if the vehicle model corresponding to the user's intention type is the same as the existing vehicle model, the intention type is modified; or, text semantic recognition is performed on the user's car demand scenario and the purchase requirements to obtain a semantic recognition result; the intention type is modified based on the semantic recognition result; or, the intention type is modified according to the user's test drive satisfaction with different vehicle models.

[0014] In a second aspect, the present application provides an intention type analysis device, comprising:

[0015] an acquisition unit, configured to acquire user's intention information for different vehicle models at different time stages;

[0016] a calculation unit configured to calculate intention analysis parameters using the intention information, and to perform time dimension analysis using the intention analysis parameters to calculate the user's intention values ​​for different vehicle models;

[0017] The analyzing unit is configured to determine the user's intention type based on the intention value.

[0018] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the intention type analysis method described in the first aspect is implemented.

[0019] In a fourth aspect, the present application provides an electronic device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the intent type analysis method described in the first aspect when executing the computer program.

[0020] In a fifth aspect, the present application provides a vehicle, comprising the intention type analysis device as mentioned in the second aspect or the electronic device as mentioned in the fourth aspect.

[0021] By means of the above technical solution, the present application provides an intention type analysis method, device, electronic device and vehicle, which first obtains the user's intention information for different models at different time stages, and then uses the intention information to calculate the intention analysis parameters, and performs time dimension analysis based on the intention analysis parameters to calculate the user's intention value for different models, and determines the user's purchase intention through the intention value. Compared with the related art, the present application performs time dimension analysis on the intention information of different models at different time stages in the sales process, calculates the intention value, and then determines the user's intention type, which solves the problem that the current intention type analysis methods lack analysis and comparison of user intentions from the perspective of timeliness, resulting in inaccurate analysis results, and improves the accuracy of intention recognition.

[0022] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0025] Figure 1 A schematic diagram of a flow chart of an intention type analysis method provided in an embodiment of the present application is shown;

[0026] Figure 2 A schematic diagram of a process flow of another intent type analysis method provided in an embodiment of the present application is shown;

[0027] Figure 3 A schematic diagram of the structure of an intention type analysis device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0028] In order to be able to more clearly understand the above-mentioned purposes, features and advantages of the present application, the scheme of the present application will be further described below. It should be noted that, in the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other. In addition, in order to be able to understand the characteristics and technical content of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings, and the attached drawings are only for reference purposes and are not used to limit the embodiments of the present disclosure. In the following technical description, for the convenience of explanation, a full understanding of the disclosed embodiments is provided by multiple details. However, in the absence of these details, one or more embodiments can still be implemented. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0029] The intent type analysis method provided in this embodiment is applied to an intent type analysis device, which can be installed in electronic equipment in automotive-related scenarios, such as intelligent marketing, sales operation analysis, etc.

[0030] In order to improve the problem that the current intent type analysis methods lack analysis and comparison of user intent from the perspective of timeliness, thus resulting in inaccurate analysis results, this embodiment proposes an intent type analysis method. Figure 1 As shown, the method includes:

[0031] S101, obtaining user intention information for different car models at different time stages.

[0032] The intention information specifically includes the time when users pay attention to different models and the release time of the corresponding models. Among them, the consultation time, number and content, and test drive time are called attention time, which indicates that the user has an intention to pay attention to a certain model. For example, if a user consults and test drives model A, it can be determined that the user has paid attention to a certain model.

[0033] In addition, the intention information can also be divided according to different time stages. For example, the test drive time of a certain model can be used as the dividing line to determine the content and time of the user's consultation on the model before the test drive, as well as the content and time of the user's consultation on the model after the test drive, thereby preparing for the subsequent time dimension analysis.

[0034] Specifically, in the process of selling cars, there are often multiple communications, and there is a certain time interval between each communication. For example, a user first consulted about a certain model M through the app on January 6, and test-drove the M model in the store on March 6. During this period, there were multiple inquiries about the M model. Therefore, there are multiple corresponding consultation times and test drive times for the M model.

[0035] S102, using the intention information to calculate intention analysis parameters, and using the intention analysis parameters to perform time dimension analysis to calculate the user's intention values ​​for different vehicle models.

[0036] Time dimension analysis is a method that combines the time dimension and calculates the user's intention value for each car model based on the user's intention information at different time nodes. The above mentioned intention information includes multiple attention times and release times. Based on the intention information, the intention analysis function can be calculated to perform time dimension analysis and obtain the user's intention value for different car models.

[0037] S103: Determine the user's intention type based on the intention value.

[0038] The intention value can be used as the user's preference for different car models after conducting a time dimension analysis. After calculating the user's intention value for different car models, the user's intention type can be determined according to the intention value.

[0039] In this embodiment, the user's intention information for different car models at different time stages is first obtained, and then the intention information is used to calculate the intention analysis parameters, and the time dimension analysis is performed based on the intention analysis parameters to calculate the user's intention value for different car models, and the user's purchase intention is determined by the intention value. Compared with the related art, this embodiment performs a time dimension analysis on the intention information of different car models at different time stages in the sales process, calculates the intention value, and then determines the user's intention type, which solves the problem that the current intention type analysis methods lack analysis and comparison of user intentions from the perspective of timeliness, resulting in inaccurate analysis results, and improves the accuracy of intention recognition.

[0040] At the same time, most of the existing intent recognition solutions are based on historical log construction models or user tags or text word vectors for intent analysis. Although the above solutions can analyze the user's intention, they lack timeliness analysis and cannot effectively solve the problem of timeliness intention transformation. For example, according to the user's initial consultation content for the M model, the M model is more detailed, and the similar model N of the M model is the latest model. The N model inherits many advantages of the M model, so the user did not continue to inquire about it and sold the N model. If it is based on the existing intention recognition solution, since the consultation content of the M model is more detailed and complete, the identified intentions are mostly the M model, which ignores the problem of timeliness intention transformation. This embodiment combines the model release time and user behavior to customize the model intention analysis formula, focusing on solving the problem of intention transformation in the time dimension. Therefore, the accuracy of intent recognition is improved, which not only avoids the loss of users as a whole, but also effectively reduces the burden on sales staff and improves communication efficiency.

[0041] Optionally, obtaining the user's intention information for different car models includes: querying the user's attention time for the car model within a preset time period and the release time of the car model.

[0042] In this embodiment, the preset time period can be set from the first inquiry of the user to the completion of the vehicle purchase, and can also be set according to actual conditions.

[0043] The intention information specifically includes the time when users pay attention to different models and the release time of the corresponding models. Among them, the consultation time, frequency and content, and test drive time are called attention time, which indicates that the user has an intention to pay attention to a certain model. The specific consultation time, frequency, and interval time in the intention information can be used as a basis for analyzing the user's purchase intention, which facilitates the subsequent time dimension analysis.

[0044] Optionally, the intention analysis parameter includes a first time interval and a second time interval. The intention analysis parameter is calculated using the intention information, and the intention analysis parameter is used to perform time dimension analysis to calculate the user's intention value for different car models, including: calculating the difference between the time when the user pays attention to the same car model each time and the time when the user first pays attention to the same car model as the first time interval; calculating the difference between the time when the user most recently paid attention to the same car model and the release time of the car model as the second time interval; taking all the first time intervals and the second time intervals as inputs of the intention analysis function to calculate the user's intention value for the car model.

[0045] Furthermore, the formula of the intent analysis function is as follows:

[0046]

[0047] In formula 1, T 0 Indicates the intention value of vehicle type code 0, t 1 Indicates the time when the intention for the model first appears (the appearance of the intention includes the first consultation about the model, or the user's understanding of a model through test driving or other means. According to the logic of consultation first and test driving later, t 1 is the time of first consultation), t i Indicates the time point when the nth word appears in the vehicle model intention, t l is the time of the most recent consultation on this model, t 0 Indicates the time when the model is released to the market. i -t 1 With t l -t 0 The interval time represented is rounded to the nearest month. Each month is calculated as 30 days. The time interval is divided by 30 and the value is rounded off.

[0048] In this embodiment, there are often multiple communications during the process of selling cars, and there is a certain time interval between each communication. The first time interval is the difference between each attention time and the first attention time for a certain model, that is, t i -t 1 The second time interval is the difference between the most recent attention time and the release time of the model, that is, t l -t 0 The above formula can be used to calculate the user's intention value for each car model. Generally speaking, the longer the time period, the lower the attention.

[0049] Optionally, determining the user's intention type based on the intention value includes: determining the user's intention type based on the vehicle type with the highest intention value.

[0050] In this embodiment, the intention values ​​can be arranged from high to low, and the vehicle type corresponding to the item with the highest intention value can be used as the user's intention type; in addition, several items with the highest intention values ​​can be used as the results of intention recognition to provide more possible references. Determining the user's intention through the intention value improves the accuracy of intention recognition.

[0051] Optionally, after determining the user's intention type based on the intention value, the method also includes: collecting relevant information of the user's current vehicle; modifying the intention type based on the vehicle-related information; wherein the vehicle-related information includes at least one of the user's existing vehicle models, the user's vehicle demand scenarios, purchase requirements, and test drive satisfaction with different vehicle models.

[0052] In this embodiment, the intention type can be modified by the relevant information of the user's current vehicle. For example, after determining the intention type, the final result can also be modified by the user's response information to the car-related questionnaire. For example, based on the intention value, the user's intention type is determined to be the M model first and the N model second; then the result is modified by the user's existing car models, demand scenarios, purchase requirements, and test drive satisfaction with the M and N models, so that the recognition is more accurate.

[0053] Optionally, based on the response information, the intent type is modified, including: if the vehicle model corresponding to the user's intent type is the same as an existing vehicle model, the intent type is modified; or, text semantic recognition is performed on the user's car demand scenarios and purchase requirements to obtain semantic recognition results; the intent type is modified based on the semantic recognition results; or, the intent type is modified according to the user's test drive satisfaction with different vehicle models.

[0054] In this embodiment, taking the above as an example, if the user already has an M model, the intent type is modified; semantic recognition is performed on the user's demand scenario and purchase requirements at the time of purchase, that is, the user's concerns. If the trial scenario, price, displacement, etc. of the M model do not meet the user's requirements, the intent type is modified, and the intent type is modified according to the test drive satisfaction. By modifying the recognition result after determining the intent type, the recognition result is more accurate.

[0055] like Figure 2 FIG. 1 is a flow chart of another method for analyzing intent types provided in an embodiment of the present application, the method comprising:

[0056] S201, obtaining user intention information based on different vehicle types according to vehicle type.

[0057] In this embodiment, a practical case is given to illustrate the intention type analysis method proposed in this embodiment. First of all, in this embodiment, the user's intention involves the M model and the N model. On January 6, 2023, the user consulted about the M model. The consultation method can be through window inquiry, employee consultation, and APP dialogue, etc., again without limitation. Then on March 6, I went to the store to test drive the M model. And on March 6, I learned that the N model is a new model of the M model, and then on March 10, I went to the store to test drive the N model. The release time of the M model is October 6, 2022, and the release time of the N model is December 6, 2022.

[0058] The intention information includes the time and content of the user's consultation on different models, the test drive time, and the release time of the corresponding models. Therefore, in the above content, the M model includes 1 consultation and 1 test drive, and the N model includes 1 consultation and 1 test drive, as well as the release time of the M model and the N model. It should be noted that when calculating, the test drive time is also counted as indicating the intention for a certain model, but it is distinguished from the consultation time. The purpose is to divide the time dimension based on the test drive time. For example, different weights can be further assigned to the test drive time and the consultation time, so that the calculation of the intention analysis function is more accurate.

[0059] S202: Calculate a first time interval and a second time interval based on the intention information of each vehicle model.

[0060] In the process of selling cars, there are often multiple communications, and each communication has a certain time interval. In this embodiment, the first time interval is the difference between each consultation time and the first consultation time for a certain model. In this embodiment, the second time interval is the difference between the most recent test drive time and the release time of the model.

[0061] S203: Input the first time interval and the second time interval into an intention analysis function to calculate the user's intention values ​​for different vehicle types.

[0062] The formula of the intention analysis function is the same as the above-mentioned formula 1, which will not be repeated here. The intention analysis function is input through the first time interval and the second time interval, so as to calculate the user's intention value for different vehicle types from the time dimension.

[0063] Specifically, combined with the above case, we can get the user's intention value T for the M model. 0 , (t l -t 0 )=5,T 0 =e -2 +e -5 =0.142073. The user's intention value for N models is T 1 , (t l -t 0 )=3,T 1 =e -0 +e -3 =1.04978.

[0064] Therefore, the user's vehicle model intention value T 1 >T 0 , so it is judged that the current intention is N model.

[0065] S204, arranging the user's intention values ​​for different vehicle types in descending order, and taking the vehicle type that ranks first in the arrangement result as the user's intention type.

[0066] S205, collecting the user's response information to the preset question, and modifying the intention type based on the response information.

[0067] After determining the intent type, the intent type obtained from the intent recognition result can be modified by the user's answer information to preset questions, such as obtaining relevant information about the user's current vehicle through a questionnaire survey. For example, based on the intent value, the user's intent type is determined to be model N first and model M second; and then the result is modified by the user's existing models, demand scenarios, purchase requirements, and test drive satisfaction with the two models M and N, so that the recognition is more accurate.

[0068] In this embodiment, the user's intention information for different models is first obtained. The intention information may include the consultation time and the corresponding content and number of times for a certain model, the test drive time, and the time when the model is launched. Then, the intention information is analyzed in the time dimension, the user's intention value for different models is calculated, and then the user's purchase intention is determined by the intention value. Compared with the relevant technology, this embodiment analyzes the intention information of different models at different time stages in the sales process in the time dimension, calculates the intention value, and then determines the user's intention type, which solves the problem that the current intention type analysis method lacks analysis and comparison of user intentions from the perspective of timeliness, resulting in inaccurate analysis results, and improves the accuracy of intention recognition. In addition, this embodiment innovatively proposes the concept of vehicle model intention recognition based on the time dimension. Combined with the intention time in the automobile sales process, combined with the model release time and user behavior to customize the vehicle model intention analysis formula, the problem of intention transformation in the time dimension is mainly solved. Therefore, the accuracy of intention recognition is improved, which not only avoids the loss of users as a whole, but also effectively reduces the burden on sales staff and improves communication efficiency.

[0069] Further, as Figure 1 and Figure 2 The specific implementation of the method shown in this embodiment provides an intention type analysis device, such as Figure 3 As shown, the device includes: an acquisition unit 301, a calculation unit 302, and an analysis unit 303.

[0070] The acquisition unit 301 is configured to acquire the user's intention information for different car models at different time stages;

[0071] A calculation unit 302 is configured to calculate intention analysis parameters using the intention information, and perform time dimension analysis using the intention analysis parameters to calculate the user's intention values ​​for different vehicle models;

[0072] The analyzing unit 303 is configured to determine the user's intention type based on the intention value.

[0073] In a specific application scenario, the acquisition unit 301 is specifically configured to query the user's attention time to the model within a preset time period and the release time of the model.

[0074] In a specific application scenario, the calculation unit 302 is further configured to calculate the difference between each time the user pays attention to the same model and the first time the user pays attention to the same model, as the first time interval; calculate the difference between the user's most recent attention to the same model and the release time of the model, as the second time interval; use all the first time intervals and the second time intervals as inputs to the intention analysis function to calculate the user's intention value for the model.

[0075] In a specific application scenario, the analysis unit 303 is further configured to determine the user's intention type based on the vehicle type with the highest intention value.

[0076] In a specific application scenario, the analysis unit 303 is further configured to collect the user's current vehicle-related information; based on the vehicle-related information, modify the intention type; wherein the vehicle-related information includes at least one of the user's existing vehicle models, the user's vehicle demand scenarios, purchase requirements, and test drive satisfaction with different vehicle models.

[0077] In a specific application scenario, the analysis unit 303 is further configured to modify the intention type if the vehicle model corresponding to the user's intention type is the same as the existing vehicle model; or, perform text semantic recognition on the user's car demand scenario and the purchase requirements to obtain a semantic recognition result; modify the intention type based on the semantic recognition result; or, modify the intention type according to the user's test drive satisfaction with different vehicle models.

[0078] It should be noted that for other corresponding descriptions of the functional units involved in the intention type analysis device provided in this embodiment, please refer to Figure 1 and Figure 2 The corresponding description in will not be repeated here.

[0079] Based on the above Figure 1 and Figure 2 The method shown in the embodiment also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned Figure 1 and Figure 2 The method shown.

[0080] Based on this understanding, the technical solution of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, USB flash drive, mobile hard disk, etc.), including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of the present application.

[0081] Based on the above Figure 1 and Figure 2 The method shown, and Figure 3 In order to achieve the above-mentioned purpose, the embodiment of the present application further provides an electronic device, which can be configured on a computer side or a vehicle side, etc. The device includes a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to achieve the above-mentioned Figure 1 and Figure 2 The method shown.

[0082] Based on the above electronic device, the embodiment of the present application further provides a vehicle, which may specifically include: Figure 3 The device shown in the figure or the electronic device as described above. The vehicle can be a new energy vehicle or a traditional vehicle.

[0083] Optionally, the above-mentioned physical device may also include a user interface, a network interface, a camera, a radio frequency (RF) circuit, a sensor, an audio circuit, a WI-FI module, etc. The user interface may include a display, an input unit such as a keyboard, etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (such as a WI-FI interface), etc.

[0084] Those skilled in the art will appreciate that the above-mentioned physical device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or a combination of certain components, or different arrangements of components.

[0085] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the above-mentioned physical device, and supports the operation of the information processing program and other software and / or programs. The network communication module is used to realize the communication between the components inside the storage medium, and the communication with other hardware and software in the information processing physical device.

[0086] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform, or by hardware. Applying the solution of this embodiment, first obtain the user's intention information for different models at different time stages, and then use the intention information to calculate the intention analysis parameters, and perform time dimension analysis based on the intention analysis parameters to calculate the user's intention values ​​for different models, and determine the user's purchase intention through the intention value. Compared with the related art, the present application analyzes the intention information of different models at different time stages in the sales process in the time dimension, calculates the intention value, and then determines the user's intention type, which solves the problem that the current intention type analysis methods lack analysis and comparison of user intentions from the perspective of timeliness, resulting in inaccurate analysis results, and improves the accuracy of intention recognition.

[0087] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprises" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0088] The above description is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features of the present application.

[0089] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent possible changes only. Unless explicitly required, separate components and functions are optional, and the order of operation may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The term "and / or" as used in this application refers to any and all possible combinations of one or more associated listings. In addition, when used in this application, the term "comprise" and its variants "comprises" and / or including (comprising) refer to the existence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the existence or addition of one or more other features, wholes, steps, operations, elements, components and / or these groups. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method or device including the elements. In this document, each embodiment may focus on the differences from other embodiments, and the same or similar parts between the embodiments may refer to each other. For the methods, devices, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts may refer to the description of the method part.

[0090] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods for each specific application to implement the described functions, but such implementations should not be considered to exceed the scope of the embodiments of the present disclosure. The technicians may clearly understand that, for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above may refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0091] In the embodiments disclosed herein, the disclosed methods and products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units can be only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to implement this embodiment. In addition, each functional unit in the embodiment of the present disclosure may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit.

[0092] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A method for analyzing intention type, characterized in that: include: Obtain information about users' intentions for different models at different time stages; Calculating intention analysis parameters using the intention information, and performing time dimension analysis using the intention analysis parameters to calculate the user's intention values ​​for different vehicle models; Based on the intent value, the user's intent type is determined.

2. The method according to claim 1, characterized in that The obtaining of user intention information for different vehicle models includes: Query the user's attention time on the model within a preset time period and the release time of the model.

3. The method according to claim 2, characterized in that The intention analysis parameters include a first time interval and a second time interval; The calculating of the intention analysis parameters by using the intention information, and performing time dimension analysis by using the intention analysis parameters to calculate the user's intention values ​​for different vehicle models, includes: Calculate the difference between each time the user pays attention to the same model and the time when the user first pays attention to it, as the first time interval; Calculate the difference between the time when the user paid the most recent attention to the same car model and the time when the car model was released, as the second time interval; All the first time intervals and the second time intervals are used as inputs of an intention analysis function to calculate the user's intention value for the vehicle type.

4. The method according to claim 1, characterized in that: The determining the user's intention type based on the intention value includes: The vehicle type with the highest intention value is used to determine the user's intention type.

5. The method according to any one of claims 1 to 4, characterized in that After determining the user's intention type based on the intention value, the method further includes: Collecting relevant information of the user's current vehicle; Based on the vehicle-related information, modify the intention type; The vehicle-related information includes at least one of the user's existing car models, the user's car usage demand scenarios, purchase requirements, and test drive satisfaction with different car models.

6. The method according to claim 5, characterized in that The modifying the intent type based on the response information includes: If the vehicle type corresponding to the user's intention type is the same as the existing vehicle type, then modifying the intention type; or, Performing text semantic recognition on the user's car demand scenario and the purchase requirement to obtain a semantic recognition result; modifying the intention type based on the semantic recognition result; or, The intention type is modified according to the user's test drive satisfaction with different vehicle models.

7. An intention type analysis device, characterized in that: include: an acquisition unit, configured to acquire user's intention information for different vehicle models at different time stages; a calculation unit configured to calculate intention analysis parameters using the intention information, and to perform time dimension analysis using the intention analysis parameters to calculate the user's intention values ​​for different vehicle models; The analyzing unit is configured to determine the user's intention type based on the intention value.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

9. An electronic device comprising a storage medium, a processor, and a computer program stored in the storage medium and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

10. A vehicle, characterized in that: include: The device as claimed in claim 7 or the electronic device as claimed in claim 9.

Images