TWM630888U - Family Member Induction Device Based on Search Behavior - Google Patents

Abstract

A family member induction device based on search behavior includes an object database, a customer habit database, a data collection module, a processing module, and a transmission module. The processing module calculates the relative family member list of the family based on the plurality of constituent features in the first search condition sent by the client code, and transmits the list to the client device through the transmission module.

Description

Family Member Induction Device Based on Search Behavior

The present disclosure relates to a display processing device, and more particularly, to a search behavior-based family member induction device.

According to the survey of home purchase intentions, people are concerned about the convenience of their homes. The property needs that buyers will consider include: proximity to consumer shopping districts, proximity to parks and green spaces, proximity to MRT/high-speed rail/station, etc. Housing features with good features can increase the convenience of living for the occupants.

Nowadays, with the popularity of the Internet, people are accustomed to searching for the desired information on the Internet. 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 the surrounding school districts, hospitals and other objects.

In order to improve the convenience of users when using home-buying websites, most home-buying websites will provide users with the function of favorites. During the process of browsing and searching for house objects, users can click the "Favorite" button or similar function button on the object display page. To do the collection operation, you can add your favorite objects to your favorites. After that, users can use their favorites to check, track, compare, or buy things they like or are interested in on a daily basis.

However, in many cases, users can only Search around a certain number of objects, and then check whether they meet your needs and include them in your favorites, but the efficiency of finding objects in this way is still too low, and it will take a lot of time and effort to find objects of the same nature. (For example, they are all in Taipei City, and they are all close to hospitals, parks, etc.).

In order to solve these problems, various object recommendation mechanisms have been derived, but these recommendation mechanisms often do not regard the same family or family as the existence of a single individual, which leads to changes in the design of recommendation mechanisms. Only the opinion of the leader must be taken into account.

In order to solve the problem of having too many objects and not knowing where to choose, one purpose of the present invention is to provide a family member induction device based on search behavior. A family member induction device based on search behavior includes an object database, a customer habit database, a data collection module, a processing module, and a transmission module. The processing module calculates the relative family member list of the family based on the plurality of constituent features in the first search condition sent by the client code, and transmits the list to the client device through the transmission module.

10: Object Display System

111, 112, 113, 114: Objects

111A, 112A, 113A, 114A: Interaction

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

121: Extra Objects

121A: Extra location

121P: Additional composition features

131: Recommended objects

131A: Location

131P: Recommended composition features

15:Customer code

15P: Where customers are often located

20: Display system

21: Data processing device

211: Object Database

212: Processing modules

2121: Search component

2122: Map Generator Component

2123: Recommended Components

213: Data Collection Module

22: Client Device

221: display screen

26: Customer Habit Database

28: Family Member Induction Device Based on Search Behavior

31: Teleportation Module

91: User

D111, D112, D113, D114: Object Labels

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

D111A1, D112A1, D113A1, D114A1: attribute words

D111A2, D112A2, D113A2, D114A2: Quantity string

D111A3, D112A3, D113A3, D114A3: Interactive content words

D111H, D112H, D113H, D114H: Label category indicator

D111P, D112P, D113P, D114P: Location Information

D121: Extra Object Label

D121A: Additional Activity Area Data Element

D121A1: Additional attribute words

D121A2: Extra Quantity String

D121A3: Additional Interactive Content Words

D121H: Extra object type indicator

D121P: Additional location information

D131: Recommended Object Label

D131A: Actual Distance Data Unit

D131A1: Recommended attribute words

D131A2: Recommended quantity string

D131A3: Recommend interactive content words

D131H: Recommended Label Category Indicator

D131P: Recommended location information

D15: Real Estate Information Unit

D15H: Real estate class indicator

D15P: Real Estate Location Information

D1A: Activity Scope Data Unit

D5: Geographic Information

D51: Icon data

D52: Map Data Block

D53: Second map data block

D54: The third map data block

D55: Fourth map data block

D61: Object attribute image data block

D62: Object attribute image data block

DA1: first object label

DHA1, DHA2: Object class indicator

DL1: Active range value

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

EL1, EL2, EL3, EL4: Candidate distance items

H111, H112, H113, H114: Label categories

HA1, HA2: Object class

HB1: Additional Object Type

HC1: Recommended Object Category

HD1: Real estate category

K111, K112, K113, K114: Icons

K121: Icon

KA2: Second Icon

KA3: The third icon

KB3: Third Icon

KA4: Fourth Icon

L1: Active range radius

M1: Map

M111P, M112P, M113P, M114P: Marking position

M121P: Additional marking position

M131P: Recommended marking position

M15P: Real estate marked location

M2: Second map

M3: The third map

M4: Fourth map

M5: Fifth Map

MA1: The first marked position

MA2: Second marked position

MA3: The third marked position

MA4: Fourth marked position

MA5: Fifth marked position

MR1: specific map area

Q1: Optional Icons

R1: Active range

S11: First search condition

S12: Second search condition

S13: Third search condition

S14: Fourth search condition

U1: Screen

This disclosure may be better understood through the detailed description of the following figures:

FIG. 1 is a schematic diagram of a display system in various embodiments of the present disclosure.

FIG. 2 is a schematic diagram of an object display system in various embodiments of the present disclosure.

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

Figure 4: A schematic diagram of a map in various embodiments of the present disclosure.

FIG. 5 shows a schematic diagram of the classification of a specific embodiment of the recommendation device based on the tag category proposed in the present invention.

See Figures 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 display system 10 in various embodiments of the present disclosure. FIG. 3 is a schematic diagram of the structure of the object database in the customer habit database 26 in FIG. 1 . As shown in FIG. 1 , the display system 20 includes a data processing device 21 , the object database 211 , a customer habit database 26 , and a client device 22 coupled to the data processing device 21 . The data processing device 21 includes an object database 211 , a processing module 212 , and a data collection module 213 coupled to the processing module 212 . 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 display system 10 includes a plurality of objects 111 , 112 , 113 and 114 . For example, the object display system 10 may further include at least one additional object 121 , a recommended object 131 and a customer code 15 . There are a plurality of interactive relationships 111A, 112A, 113A and 114A between the client code 15 and the plurality of objects 111 , 112 , 113 and 114 respectively. The plurality of objects 111 , 112 , 113 and 114 respectively have a plurality of constituent features 111P, 112P, 113P and 114P. The extra object 121 has an extra Location 121A and an additional component feature 121P. The recommended object 131 has a location 131A and a recommended composition feature 131P. The customer code 15 has a frequent location 15P for real estate customers. The processing module 212 calculates an actual distance between the plurality of objects within the issued first search condition and the location where the customer is often located.

The plurality of objects 111, 112, 113 and 114 belong to a plurality of label classes H111, H112, H113 and H114, respectively, and each class of the plurality of label classes H111, H112, H113 and H114 is of the plurality of object classes HA1 and HA2 one of them. The extra object 121 belongs to an extra object class HB1 which is different from any one of the plurality of object classes HA1 and HA2. The recommended object 121 belongs to a recommended object category HC1.

For example, the plurality of object categories HA1 and HA2 are a hospital category and a store category, respectively, and the additional object category HB1 is a restaurant category. For example, two objects 112 and 113 belong to the hospital category and the store category, respectively, so the real estate customer with the customer code 15 is often located at the actual distance 112A and the actual distance 112A of the object 112 and the object 113 113A respectively. 10 meters and 100 meters.

The customer habit database in the customer habit database 26, the customer habit database is used to store multiple pieces of customer habit data, each customer habit data mainly includes the customer code, the customer's usual location, and the first search condition S11 or the second search Condition S12, wherein the first search condition S11 includes the customer code and a plurality of constituent features of the customer code, and the constituent features are mainly composed of the constituent features selected from the Abbreviation, price, community name, address, floor, building registration area, land registration area, unit price per unit area, type, layout, age of house, parking space, seat orientation, elevator, management fee, layout plan, and living functions. Each of the plurality of constituent features has a priority, and the higher the priority is, the higher the overlap will be, and the results presented in the family member list will be affected.

The data collection module 213 receives the first search condition S11 and the second search condition S12 at different times, and sends the second map data block D53 and the third map data block D54 to the client at different times The device 22 transmits, so that the client device 22 displays the second map M2 and the third map M3 on the display screen 221 at different times, and stores the first search condition S11 and the second search condition S12 in the Database of customer habits. 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 sent a search record (ie, the first search condition) for the objects 111 and 114, and the user 91 has passed by the special devices near the objects 112 and 113, and can find out what the user 91 uses The existence of the device (ie, the second search condition), and through the above-mentioned several geographic locations, the activity range R1 can be surrounded on the map. In other words, if the object of interest to the user 91 falls within the activity range R1 when the user 91 requests a house in the future, the system will register the user 91 as a local guest. However, the system can flexibly expand the range covered by the activity range R1 outwards, so that local guests can judge more accurately, because it may just happen that the habitual trajectory information left by the user 91 in the system is not enough, resulting in System misjudged. On the other hand, if the object that the user 91 is interested in falls within the activity range R1, the system will mark the user 91 as a non-local guest.

However, sometimes the user 91 only does it occasionally, and runs to the area where he is not often active, and the processing module 212 first removes the plurality of constituent features or the first search condition S11 issued by the client code. Only when the second geographic location in the second search condition S12 exceeds a predetermined deviation value, the relative activity range of the client code is calculated. Correspondingly, if the amount of data is too small, the system may misjudge, and a threshold value needs to be set. Therefore, the processing module 212 first confirms the plurality of constituent features or the The relative activity range of the client code is calculated only when the second geographic location in the second search condition S12 exceeds a predetermined number.

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 the second map to the client through the transmission module 31 device 22. Specifically, the processing module 212 will also filter out the plurality of objects that fall within the sent first search condition, and then generate the second map data block representing a second map, wherein the second The map is a map in which a plurality of icons are respectively displayed at the plurality of marked positions on the map, and the plurality of icons respectively indicate the plurality of objects.

In FIG. 1 , the data collection module 213 receives a first search condition S11 or a second search condition S12 from a user 91 . The first search condition S11 includes the customer code and a plurality of constituent features of the customer code, and the constituent features are mainly for the objects 111, 112, The composition features issued by 113 and 114 are mainly issued for the object.

The processing module 212 summarizes a custom tag relative to the client code based on a plurality of constituent features in the first search condition sent by the client code or the second geographic location of the second search condition to obtain each client The composition feature of the code is calculated, and the relative family member list of the family is calculated according to the similarity between the custom tags of the plurality of client codes.

In other words, it is to judge the relative demand of the customer code by analyzing and summarizing the plurality of constituent features in the first search condition, and to simplify the so-called house purchase demand with the custom label, and the custom label and the object label are actually equivalent. In this way, according to the similarity of the customary tags of a plurality of customer codes to each other, and at the same time, the actual distance between the real estate customer of the customer code and the object can also be considered for the family members. Because the same family members will have similarities in habitual labels, they will also be geographically related to objects of interest.

The processing module 212 calculates a relative family member list of the family based on the plurality of constituent features in the first search condition sent by the client code. More specifically, the processing module calculates the family member list according to the label category and the corresponding subject comparison table as shown in FIG. 5 .

In order to achieve this purpose, the system needs to create an object database first, and each object data in the object database has an object index code and a plurality of constituent features to which the object index code belongs.

The object database 211 stores plural tag type data, each Each tag type data has an object index code, and a plurality of constituent features to which the object; index code belongs, and each constituent feature is mainly defined by a single constituent feature or a plurality of constituent features. For example, the composition feature is that three generations live in the same house, and the relative composition feature is a larger room (more than 3 bedrooms and more than 30 pings), and the rest of the correspondence is shown in Figure 5.

The processing module 212 uses a weight calculation formula to obtain the main influence object and its relative label type according to the plurality of constituent features in the first search condition issued by the client code, and then according to the composition of the label class From the content defined by a single component feature or a plurality of component features in the features, find out the plural real estate information that meet the conditions, and generate a family member list including a specific number of plural real estate information. For example, if the main impact tag category is three generations living in the same house (for example, an object suitable for three generations to go together, such as an IKEA furniture store), the processing module 212 uses the composition features of 3 rooms or more and 30 ping or more in the object database 211. search. In this way, the user only needs to simply select a specific object, and the system can search for the corresponding object for selection.

In order to collect more information about the activities of the user 91, the system can also place a special device in a specific physical location, so as to detect the existence of the device used by the user 91, for example, once the mobile phone WIFI signal is detected, it will be recorded. , that is, the user 91 may also issue the second search condition S12 in a passive state. The second search condition S12 indicates the customer code and a second geographic location of the customer code (ie, the location of the above-mentioned special device).

In some embodiments, the object display system 10 further includes Contains 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 with respect to the client code 15 .

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

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

In Figure 3, the plurality of object labels D111, D112, D113 and D114 respectively include a first plurality of position information D111P, D112P, D113P and D114P representing the constituent features 111P, 112P, 113P and 114P, respectively indicating the plurality of A plurality of label class indicators D111H, D112H, D113H and D114H of label classes H111, H112, H113 and H114, and a plurality of active range data units D111A and D112A respectively representing the plurality of interaction relationships 111A, 112A, 113A and 114A , D113A and D114A.

The extra object label D121 includes an extra position information D121P representing the extra composition feature 121P, indicating the extra object type An extra object type indicator D121H of HB1, and an extra active range data element D121A representing the extra location 121A. The recommended object label D131 includes a recommended location information D131P representing the recommended composition feature 131P, a recommended label type indicator D131H indicating the recommended object type HC1, and an actual distance data unit D131A representing the location 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 type indicator D15H indicating the real estate type HD1.

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

Please refer to FIG. 4 , the second search condition S12 indicates that a second icon KA2 (such as the icon K112 ) is selected among the plurality of icons K111 , K112 , K113 and K114 , and the second icon KA2 is located in the A first marked position MA1 (eg marked position M112P) in the second map M2 corresponds to a first object label DA1 (eg, object label D112) in the plurality of object labels D111, D112, D113 and D114, And the second map M2 has a second marked position MA2 corresponding to the first marked position MA1.

The system can selectively display relevant information between the user 91 and the object based on the user's selection. Please refer to Figure 1, Figure 3, In FIG. 4, the client device 22 is operated by the user 91 to generate interactive operations at a first time and a second time after the first time, respectively, and the interactive operations are transferred to the data processing at different times Device 21 transmits. For example, the data processing device 21 can calculate an actual distance between the plurality of objects and the location where the customer is often located. By receiving a user input from the user 91, when the second icon KA2 displayed on the display screen 221 is selected, the actual distance in the first object label DA1 is presented in the second Near the icon KA2.

Many modifications and other embodiments of the disclosure presented herein will be appreciated by those skilled in the art having the benefit of the teachings presented in the foregoing descriptions and associated drawings. Therefore, it should be understood that the present disclosure is not limited to the specific embodiments disclosed, 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 modules

2121;Search component

2122: Map Generator Component

2123: Recommended Components

213: Data Collection Module

22: Client Device

221: display screen

26: Customer Habit Database

28: Family Member Induction Device Based on Search Behavior

31: Teleportation Module

91: User

D111, D112, D113, D114: Object Labels

D121: Extra Object Label

D131: Recommended Object Label

D15: Real Estate Information Unit

D1A: Activity Scope Data Unit

D5: Geographic Information

D53: Second map data block

D54: The third map data block

D55: Fourth map data block

D61: Object attribute image data block

D62: Object attribute image data block

DA1: first object label

DHA1, DHA2: Object class indicator

DL1: Active range value

M2: Second map

M3: The third map

M4: Fourth Map

M5: Fifth Map

S11: First search condition

S12: Second search condition

S13: Third search condition

S14: Fourth search condition

U1: Screen

Claims (5)

A family member induction device based on search behavior, including: an object database, the object database includes a geographic information, and a plurality of object labels respectively representing a plurality of objects, the plurality of objects have a composition feature, and the plurality of objects belong to one of the plurality of label categories; a customer habit database, the customer habit database is used for storing a plurality of pieces of customer habit data, each piece of customer habit data mainly includes a customer code and a first search condition, wherein the first search condition includes the customer code, and a plurality of constituent characteristics relative to the client code; a data collection module coupled to the customer habit database, receiving the first search condition from a plurality of client devices through a communication module, and storing the first search condition in the customer habit database; a processing module, coupled with the data collection module, the object database, and the customer habit database, and based on a plurality of constituent features in the first search condition sent by each customer code, summarizes the relative data of the customer code a custom label, and calculate a family relative list of family members according to a degree of similarity between the custom labels of the plurality of client codes; and A transmission module, coupled to the data collection module, the object database, and the customer habit database, is used for transmitting the family member list to the client device. The device for summarizing family members based on search behavior as claimed in claim 1, wherein the object tag in the object database includes a plurality of constituent features Each constituent feature is mainly defined by a single constituent feature or multiple constituent features; Wherein, the processing module is based on the custom tag and the content defined by a single composition feature or a plurality of composition features in the composition feature of the tag category, and according to the approximation of the custom tags of a plurality of client codes with each other degree, find out the plural customer codes whose conditions are mutually matched, so as to calculate the list of the family members relative to the customer code. The device for summarizing family members based on search behavior as claimed in claim 2, wherein the processing module calculates a relationship between the plurality of objects falling within the issued first search condition and a frequent location of a customer actual distance; Wherein, when a second icon displayed on a display screen is selected, the actual distance is displayed near a second icon. The device for summarizing family members based on search behavior according to claim 3, wherein the processing module first removes the positions of the plurality of objects in the first search condition issued by the client code that exceed a predetermined deviation value, The list of family members relative to the customer code is calculated. The device for summarizing family members based on search behavior according to claim 3, wherein the processing module first confirms that the plurality of objects in the first search condition issued by the client code exceeds a predetermined number, and then calculates the client code Relative list of members of the family.

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