TW202312078A - Device for inducting and analyzing key factors especially for investigating the convenience around a home according to a survey of home purchase intentions - Google Patents

Abstract

A device for inducting and analyzing key factors, which includes an object database, a customer activity database, a data collection module, a processing module, and a transmission module. The processing module calculates customer preference demands relative to a customer code based on the occurrence ratio of the object characteristics of the objects in a plurality of activity contents to which the customer code belongs, and transmits it to a client device through the transmission module.

Description

Inductive Analysis Device of Key Factors

The present disclosure relates to a display processing device, and in particular to a key factor inductive analysis device.

According to the survey of house purchase intentions, people care about the convenience around their homes. The property requirements that buyers will consider include: proximity to living and consumption business districts, proximity to parks and green spaces, proximity to MRT/high-speed rail/stations, etc. House items with good items can increase the convenience of life for the homeowner. Nowadays, with the popularity of the Internet, people are used to searching for the information they want online. For the supply of real estate objects, some real estate object providers will present photos, layouts and housing information of the objects on their websites. Some real estate object providers will use the map to present objects such as school districts and hospitals around the object. When a customer sees an object of interest on the website, he will actively contact the real estate agent, and the agent will relatively assign a broker to serve.

However, under the existing model, most of the brokers who go to serve customers know nothing about the needs of customers, forcing brokers to always think of ways to adapt to the situation, unable to do their homework in advance, making it difficult to improve service quality.

In order to solve the problem of unclear customer needs, one purpose of the present invention is to provide a device and method for inductive analysis of key factors Law. A device for summarizing and analyzing key factors includes an object database, a customer activity database, a data collection module, a processing module, and a transmission module. The processing module calculates a customer preference demand relative to the customer code based on the occurrence ratio of the object characteristics of the objects in the plurality of active contents to which the customer code belongs, and sends it to the client device through the transmission module.

10: Object system

111, 112, 113, 114: objects

111A, 112A, 113A, 114A: actual distance

111P, 112P, 113P, 114P: Object characteristics

121: Additional Objects

121A: Actual distance

121P: Additional object features

131: Recommended Items

131A: Actual distance

131P: Recommended object features

15: Customer Code

15P: Customer's frequent location

20: Display system

21: Data processing device

211: Object database

212: Processing module

2121: Search component

2122: Map generator component

2123: Recommended components

213: Data collection module

22: Client device

221: display screen

26: Database group

28:Inductive analysis device for key factors

31: Teleportation Module

91: user

D111, D112, D113, D114: object information

D111A, D112A, D113A, D114A: Activity Range Data Unit

D111A1, D112A1, D113A1, D114A1: Attribute terms

D111A2, D112A2, D113A2, D114A2: quantity string

D111A3, D112A3, D113A3, D114A3: Interactive Content Words

D111H, D112H, D113H, D114H: object characteristic category indicator

D111P, D112P, D113P, D114P: location information

D121: Additional object information

D121A: Additional Range of Activities Information Unit

D121A1: Additional Attribute Words

D121A2: Extra Quantity String

D121A3: Additional interactive content words

D121H: Additional Object Feature Category Indicator

D121P: Additional location information

D131: Recommended object information

D131A: Actual distance data unit

D131A1: Recommended Attribute Words

D131A2: Recommended Quantity String

D131A3: Suggest words for interactive content

D131H: Recommended object feature category indicator

D131P: Recommended location information

D15: Real estate information unit

D15H: Real estate category indicator

D15P: Real estate location information

D1A: Scope of Activities Information Unit

D5: Geographic information

D51: Icon data

D52: map data block

D53: Multiple map data blocks

D54: The third map data block

D55: The fourth map data block

D61: Object attribute image data block

D62: Object attribute image data block

DA1: multiple object data

DHA1, DHA2: object characteristic category indicator

DL1: active range value

EA1, EA2, EA3, EA4: object candidate category items

EL1, EL2, EL3, EL4: Candidate distance items

H111, H112, H113, H114: object characteristic category

HA1, HA2: object feature category

HB1: Additional Object Feature Classes

HC1: Recommended Object Feature Classes

HD1: Real estate category

K111, K112, K113, K114: icons

K121: Icons

KA2: plural icons

KA3: The third icon

KB3: Third icon

KA4: The fourth icon

L1: Activity range radius

M1: map

M111P, M112P, M113P, M114P: marked position

M121P: additional marking position

M131P: Recommended marking position

M15P: Real estate sign location

M2: Multiple maps

M3: Third Map

M4: Fourth map

M5: fifth map

MA1: multiple marked positions

MA2: multiple marked positions

MA3: The third marked position

MA4: The fourth marked position

MA5: The fifth marked position

MR1: specific map area

Q1: Optional icons

R1: range of activities

S11: plural event contents

S12: plural event contents

S13: The content of the third activity

S14: Fourth activity content

U1: screen

This disclosure can be understood more deeply through the detailed description of the following diagrams:

Figure 1: A schematic diagram of a display system in various embodiments of the present disclosure.

Figure 2: Schematic diagram of an object system in various embodiments of the present disclosure.

FIG. 3: A schematic diagram of the structure of an object database in FIG. 1.

Figure 4: Schematic illustration of a map in various embodiments of the present disclosure.

Fig. 5: a schematic diagram of demand analysis in various embodiments of the present disclosure.

See pictures 1, 2 and 3. FIG. 1 is a schematic diagram of a display system 20 in various embodiments of the present disclosure. FIG. 2 is a schematic diagram of an object system 10 in various embodiments of the present disclosure. FIG. 3 is a schematic diagram of the structure of an object database in a database group 26 in FIG. 1 . As shown in FIG. 1 , the display system 20 includes a data processing device 21 and a client device 22 coupled to the data processing device 21 . The data processing device 21 includes an object database 211 coupled to the data unit A processing module 212 of 211 , and a data collection module 213 coupled to the processing module 212 . The object database 211 includes the database group 26, and the database group 26 is further divided into an object database and a customer activity database. The client device 22 includes a display screen 221 . For example, there is a transmission module 31 between the data collection module 213 and the client device 22, and the transmission module 31 is coupled therebetween.

As shown in FIG. 2 , the object system 10 includes a plurality of objects 111 , 112 , 113 and 114 . For example, the item system 10 may further include at least one additional item 121 , a recommended item 131 and a customer code 15 . There are a plurality of interaction relationships 111A, 112A, 113A and 114A between the client code 15 and the objects 111 , 112 , 113 , 114 respectively. The objects 111, 112, 113, 114 respectively have a plurality of object characteristics 111P, 112P, 113P, and 114P. The additional object 121 has an additional motion range 121A and an additional object feature 121P. The recommended object 131 has an actual distance 131A and a recommended object feature 131P. The customer code 15 has a real estate customer frequent location 15P. The processing module 212 calculates an actual distance between the objects falling within the plurality of sent activity contents and the customer's usual location.

These objects 111, 112, 113 and 114 belong to a plurality of object characteristic categories H111, H112, H113 and H114 respectively, each of the object characteristic categories H111, H112, H113 and H114 is a plurality of object characteristic categories HA1 and HA2 one of the . The additional object 121 belongs to an additional object characteristic class HB1, which is different from any one of the object characteristic classes HA1 and HA2. The recommendation Item 121 belongs to a recommended item feature category HC1. The customer code 15 belongs to a real estate category HD1.

For example, the object feature categories HA1 and HA2 are environment category and life function category respectively, and the additional object feature category HB1 is medical category. For example, two objects 112 and 113 belong to the environmental category and the living function category respectively, so the actual distance 112A of the object 112 and the actual distance 113A of the object 113 are respectively the closest of 10 meters and 100 meters.

In FIG. 1 , the data collection module 213 receives a plurality of activity contents S11 of a plurality of customer activities from a broker user 91 or a plurality of activity contents S12 from a client user 91 . The plurality of activity contents S11 includes the customer code and the plurality of service demands of the customer code, and the service demand is mainly for the object 111, 112, 113 and 114. The service demand is mainly for the object, plural An activity content indicates the customer code, and a plurality of geographic locations for the customer code. The above-mentioned service requirements can be service requirements for broker service exploration or object viewing summary, or customer active condition subscription, search condition summary, and online house viewing summary. Active subscription is similar to search conditions, except that after the subscription is completed, the system will prompt the customer through a predetermined communication channel when an object that meets the subscription conditions is found.

To put it simply, in this case, the processing module 212 calculates the customer preference demand relative to the customer code based on the occurrence ratio of the object characteristics of the objects in the plurality of activity contents to which the customer code belongs. In this way, the broker or counterparty can rely on the relative customer preference of the customer code Need to judge whether to spend time in probing and contacting.

The price information in the object feature is collected from a plurality of active content S11 or a plurality of active content S12 from the customer's user 91, which represents different object feature types and the same object feature obtained under different service requirements. Information. If the processing module 212 finds the proportions of these object features, it means the reliability is high. If the feature of the object is a number, the predetermined range is a numerical range; if the feature of the object is a character, the predetermined range is a synonym or abbreviation of the character.

As shown in Fig. 5, for example, if the processing module 212 finds that the occurrence ratio of the object feature belonging to the parking space is significantly higher (0.91), then it will be considered that the urgent parking space is the customer preference requirement of the customer code, and the building height Then it is only 0.21, which means that the building height is not the customer's preference. The inductive analysis principles for the remaining object features are roughly the same, so that complete customer preference requirements can be discovered from different object feature categories.

In order to be able to view the customer preference requirement relative to the client code, the processing module 212 makes the client device 22 display the client preference requirement relative to the client code by a predetermined display means according to the client preference requirement relative to the client code. in personal messages.

In order to achieve the above purpose, the system needs to establish an object database first, and each object data in the object database has an object index code and a plurality of objects to which the object index code belongs. Among them, the object includes the abbreviation, price, community name, address, floor, building registration area, land registration area, unit price per unit area, type, layout, house age, parking space, seat orientation, elevator, etc. selected from the real estate object. management fee, layout plan, vital functions.

The object feature category database 211 stores a plurality of object feature category data, each object feature category data has an object index code, and the object; a plurality of objects to which the index code belongs, and each object is mainly based on a single object feature or multiple defined by object characteristics.

The processing module 212 will use a weight calculation formula to obtain the main influencing object and its relative object characteristic category according to the object characteristics of the objects in the plurality of active contents to which the client code belongs, and then according to the object characteristic category According to the content defined by a single object feature or multiple object features in the object, multiple real estate information that meet the conditions are found to generate customer preference requirements that include a specific number of multiple real estate information.

In order to collect more information about user 91's activities, the system can also place a special device in a specific physical location, so that the existence of the device used by user 91 can be discovered, for example, it will be recorded once the WIFI signal of the mobile phone is detected , that is to say, it is also possible for the user 91 to send out a plurality of active content S12 in a passive state. The plurality of activity contents S12 indicate the customer code and the plurality of geographical locations of the customer code (that is, the location of the above-mentioned special device).

In some embodiments, the object system 10 further includes an activity range R1. The activity range R1 is centered on the customer code 15 and has an activity range radius L1 calculated from the customer code 15 as the center. The active range radius L1 indicates the active range R1 relative to the client code 15 .

In addition, an actual distance L between the customer code 15 and the objects 111 , 112 , 113 , and 114 can also be represented by the summed walking distance based on the distance information of streets and alleys.

As shown in Fig. 1 and Fig. 3, the object database in the database group 26 includes geographic information D5, and a plurality of object data D111, D112, D113 and D114, may further include at least one additional object data D121 representing the at least one additional object 121, may further include a recommended object data D131 representing the recommended object 131, and may further include a real estate data unit D15 representing the customer code 15 .

In FIG. 3, the object data D111, D112, D113, and D114 respectively include a plurality of position information D111P, D112P, D113P, and D114P representing the object characteristics 111P, 112P, 113P, and 114P, respectively indicating the objects A plurality of object characteristic category indicators D111H, D112H, D113H and D114H of the characteristic categories H111, H112, H113 and H114, and a plurality of activity range data units D111A, D112A, D113A and D114A.

The additional object data D121 includes an additional location information D121P representing the additional object characteristic 121P, an additional object characteristic type indicator D121H indicating the additional object characteristic type HB1, and an additional activity range data unit representing the additional activity range 121A D121A. The recommended object data D131 includes a recommended location information D131P representing the recommended object feature 131P, a push button indicating the recommended object feature category HC1 The recommended object characteristic category indicator D131H, and an actual distance data unit D131A representing the actual distance 131A. The real estate data unit D15 includes a real estate location information D15P representing the frequent location 15P of the real estate customer, and a real estate category indicator D15H indicating the real estate category HD1.

As shown in Figures 2 and 3, the interaction relationships 111A, 112A, 113A, and 114A in Figure 2 are respectively represented by a plurality of attribute words D111A1, D112A1, D113A1, and D114A1, and are respectively formed with the The plurality of quantities corresponding to the interactive relationships 111A, 112A, 113A, and 114A, and the plurality of interactive contents respectively corresponding to the interactive relationships 111A, 112A, 113A, and 114A.

The customer activity database in the database group 26, the customer activity database is used to store multiple customer activity data, each customer activity data mainly includes customer code, customer's frequent location and multiple activity content S11 or multiple activity content S12, wherein the plurality of activity contents S11 include the customer code and the plurality of service requirements of the client code, and the service requirements are mainly issued for the object, and the plurality of activity contents S12 indicate the client code and the client code A plurality of geographic locations simultaneously receive the customer evaluation given by the customer code on the object through the communication module, and store the customer evaluation into the customer activity database. The weight distribution rate of the objects is determined according to the interaction frequency between the objects and the client code, and the higher the interaction frequency, the greater the impact of the object on the client preference requirement of the client code.

The data collection module 213 receives plural activity content S11 and a plurality of activity contents S12, and transmit a plurality of map data blocks D53 and the third map data block D54 to the client device 22 at different times, so that the client device 22 is at different times at different times A plurality of maps M2 and the third map M3 are displayed on the display screen 221 . For example, the data collection module 213 is coupled to the client device 22 via the transmission module 31 .

In some embodiments, the user 91 has issued order records (ie, multiple activity contents) for the objects 111 and 114, and the user 91 has passed by a special device near the objects 112 and 113, and the user 91 can be found. Existence of the device used (ie, multiple activity contents), and through the above-mentioned geographical locations, the activity range R1 can be surrounded on the map. In other words, if the user 91 needs to buy a house in the future, if the object he is interested in falls within the activity range R1, the system will mark the user 91 as a local guest. However, the system can flexibly expand the range covered by the activity range R1, so that local customers can judge more accurately, because it may just happen that the behavior track information left by user 91 in the system is not enough, causing the system to Misjudgment. In contrast, if the object of interest of the user 91 falls within the activity range R1, the system will mark the user 91 as a non-resident.

Only, sometimes the user 91 does it only occasionally, and runs to an area where he is not frequently active. For this, the processing module 212 first removes the object characteristics or the object characteristics of the objects in the plurality of active contents S11 to which the client code belongs. Only when the plurality of geographic locations in the plurality of activity contents S12 exceed a predetermined deviation value, can the relative activity range of the customer code be calculated. Relatively, if the amount of data is too small, it may also make the system misjudgment, and need to To establish a threshold value, the processing module 212 first confirms that the object characteristics of the objects in the plurality of active contents S11 to which the customer code belongs or the plurality of geographical locations in the plurality of active contents S12 exceed a predetermined number before calculating The relative scope of activity for this client code.

In addition, the processing module 212 can display the relevant information of the objects that the user 91 has interacted with on the electronic map, and transmit the activity range and multiple maps to the client device through the transmission module 31 twenty two. Specifically, the processing module 212 will also filter out the objects falling within the plurality of sent activity contents, and then generate a plurality of map data blocks representing a plurality of maps, wherein the plurality of maps are in the map The marked positions on the map respectively present a map with a plurality of icons, and the icons respectively mark the objects.

Please refer to FIG. 4, the plurality of active contents S12 indicates a plurality of icons KA2 (such as icon K112) selected among the icons K111, K112, K113 and K114, and the plurality of icons KA2 are located in the plurality of maps M2 A plurality of marked positions MA1 (such as marked positions M112P), and corresponding to a plurality of object data DA1 (such as object data D112) in the object data D111, D112, D113 and D114, and a plurality of maps M2 have corresponding The plurality of marked positions MA1 and the plurality of marked positions MA2.

The system can selectively display the related information between the user 91 and the object based on the selection of the user. Please refer to FIG. 1, FIG. 3, and FIG. 4, the client device 22 is operated by the user 91 to generate interactive operations at a plurality of times and a plurality of times after the plurality of times, respectively, And transmit the interactive operation to the data processing device 21 at different times. For example, the data processing device 21 can calculate an actual distance between the dropped objects and the frequent location of the customer. By receiving a user input from the user 91, when the plurality of icons KA2 displayed on the display screen 221 are selected, the actual distances in the plurality of object data DA1 are presented on the plurality of icons KA2 near.

Many variations and other embodiments of the present disclosure presented herein will be appreciated by those skilled in the art having the benefit of the teachings presented in the foregoing description and associated drawings. Therefore, it should be understood that the present disclosure is not limited to the disclosed specific embodiments, and modifications and other embodiments are intended to be included within the scope of the following claims.

20: Display system

21: Data processing device

211: Object database

212: Processing module

2121: Search component

2122: Map generator component

2123: Recommended components

213: Data collection module

22: Client device

221: display screen

26: Database group

28:Inductive analysis device for key factors

31: Teleportation Module

91: user

D111, D112, D113, D114: object data

D121: Additional object data

D131: Recommended object information

D15: Real estate information unit

D1A: Scope of Activities Information Unit

D5: Geographic Information

D53: Multiple map data blocks

D54: The third map data block

D55: The fourth map data block

D61: Object attribute image data block

D62: Object attribute image data block

DA1: multiple object data

DHA1, DHA2: object characteristic category indicator

DL1: active range value

M2: Multiple maps

M3: Third Map

M4: Fourth map

M5: fifth map

S11: plural event contents

S12: plural event contents

S13: The content of the third activity

S14: Fourth activity content

U1: screen

Claims (5)

A device for summarizing and analyzing key factors for transmitting information to a client device, comprising: an object database, the object database includes a plurality of geographic information of a plurality of objects, and a plurality of object data respectively representing the plurality of objects, and the objects all have an object characteristic; A customer activity database, the customer activity database is used to store a plurality of customer activity data, each customer activity data mainly includes a customer code, a plurality of activity contents, and the characteristics of the object corresponding to the plurality of activity contents and a Customer evaluation, wherein the multiple activities include the customer code and the multiple service demands of the customer code, and the service demand is mainly issued for the object; A data collection module, coupled to the customer activity database, receives a plurality of activity contents from the client device through a communication module, and stores the plurality of activity contents in the client activity database; A processing module, coupled with the data collection module, the object database, and the customer activity database, calculates the customer code based on the occurrence ratio of the object characteristics of the objects in the plurality of activity contents to which the customer code belongs As opposed to a customer preference requirement, the customer preference requirement is composed of a plurality of objects and the object characteristic of each object has a predetermined range; and A transmission module, coupled with the data collection module, the object database, and the customer activity database, is used to transmit the customer preference requirement to the client device. The device for summarizing and analyzing key factors as described in claim item 1, wherein the plurality of service requirements can be broker service exploration, object viewing summarization, active condition subscription, search condition summarization, and online property viewing summation. The inductive analysis device for key factors as described in claim item 1, wherein the feature of the object is a number, the predetermined range is a numerical range, the feature of the object is a character, and the predetermined range is a synonym for the character, Abbreviation. The device for inductive analysis of key factors as described in Claim 1, wherein the processing module calculates an actual distance between the objects falling within the sent out plurality of activity contents and a customer's frequent location; Wherein, when a plurality of icons displayed on a display screen are selected, the actual distance is presented near the plurality of icons. The device for inductive analysis of key factors as described in claim 1, wherein the processing module first eliminates the position of the objects in the plurality of active contents to which the client code belongs exceeds a predetermined deviation value, and then calculates the client An activity range surrounded by a plurality of objects corresponding to the code.

Images