CN110796515A - House resource recommendation method and device, storage medium and mobile terminal - Google Patents
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Abstract
The invention discloses a house source recommendation method, a house source recommendation device, a storage medium and a mobile terminal, wherein the method comprises the following steps: collecting user information of a user in a preset mode; determining user tag data respectively corresponding to one or more preset tags according to the user information; matching the user tag data with a pre-stored preset tag of each house source in a plurality of house sources respectively to obtain the matching degree of the user and each house source; selecting a preset number of house sources arranged in the front according to the matching degree of the user and each house source and the sequence from high to low of the matching degree; pushing the preset number of house sources to the user; according to the method, the corresponding house resources can be matched according to the diversified information of the user, the pushed house resources can better meet the requirements of the user, and the user experience is improved.
Description
Technical Field
The invention relates to the technical field of mobile internet, in particular to a house source recommending method, a house source recommending device, a storage medium and a mobile terminal.
Background
Along with the development of mobile internet, more and more real estate enterprises have all promoted own APP, adopt three-dimensional digital image technique, network technology, artificial intelligence etc. to provide omnidirectional show for the building, when the user adopts the APP of buying a house to search for the house source, all are the various conditions of manual input, and user experience is poor.
Disclosure of Invention
The invention provides a room source recommending method, a room source recommending device, a storage medium and a mobile terminal, and aims to solve the problem that the existing room purchasing application user experience is poor.
In a first aspect, an embodiment of the present invention provides a house source recommendation method, including:
collecting user information of a user in a preset mode;
determining user tag data respectively corresponding to one or more preset tags according to the user information;
matching the user tag data with a pre-stored preset tag of each house source in a plurality of house sources respectively to obtain the matching degree of the user and each house source;
selecting a preset number of house sources arranged in the front according to the matching degree of the user and each house source and the sequence from high to low of the matching degree;
and pushing the preset number of house sources to the user.
Further, the user information of the user is collected in a preset mode, and the method comprises the following steps:
when a questionnaire filling request sent by a user is received, calling a questionnaire page to perform pushing display, and acquiring user information uploaded by the user through the questionnaire page; or
And acquiring user information of the user according to historical search data of the user.
Further, the matching the user tag data with the pre-stored preset tag of each of the plurality of house sources respectively to obtain the matching degree between the user and each house source includes:
matching the user tag data with a pre-stored preset tag of each house source in a plurality of house sources respectively to obtain tags and tag quantity matched with each house source by a user;
and determining the matching degree of the user and each house source according to the labels matched with the user and each house source and the number of the labels.
Further, the determining the matching degree between the user and each house source according to the tags matched with the user and each house source and the number of the tags includes:
obtaining a first matching parameter according to the label matched with each house source and the weight value corresponding to each label;
obtaining a second matching parameter according to the number of the tags matched with each house source by the user and the weight values corresponding to the different numbers of the tags;
and obtaining the matching degree of the user and each house source according to the first matching parameter and the second matching parameter.
Further, the preset label comprises a city where the house is located, a total price of the house, house types and house areas; the user information comprises the city where the user is located, the age of the user, family member information and bearable monthly supply;
determining user tag data respectively corresponding to one or more preset tags according to the user information, including:
determining the city where the house expected by the user is located according to the city where the user is located;
determining the total house price which can be borne by the user according to the age of the user and the sustainable monthly supply;
and determining the house type and the house area expected by the user according to the family member information.
Further, the preset labels further comprise house orientation, house floor and house type; the user information further includes customization data including a desired orientation, a desired floor, and a desired type;
determining user tag data respectively corresponding to one or more preset tags according to the user information, including:
and determining the house orientation, the house floor and the house type which are expected by the user according to the self-defined data.
Further, before collecting user information of a user in a predetermined manner, the method further includes:
and when login request information sent by a user is received, verifying the login request information, and allowing the user to log in after the verification is passed.
In a second aspect, an embodiment of the present invention provides a house source recommending apparatus, including:
the information acquisition module is used for acquiring user information of a user in a preset mode;
the data determining module is used for determining user tag data respectively corresponding to one or more preset tags according to the user information;
the matching module is used for respectively matching the user tag data with a preset tag of each house source in a plurality of pre-stored house sources to obtain the matching degree of the user and each house source;
the house source selection module is used for selecting the house sources in the preset number from high to low according to the matching degree of the user and each house source;
and the pushing module is used for pushing the preset number of the house sources to the user.
In a third aspect, an embodiment of the present invention provides a storage medium storing a plurality of instructions, which are loaded and executed by a processor to enable the processor to execute the above-mentioned room source recommending method.
In a fourth aspect, an embodiment of the present invention provides a mobile terminal, including a processor and a memory connected to the processor, where the memory stores a plurality of instructions, and the instructions are loaded and executed by the processor, so that the processor can execute the above-mentioned room source recommending method.
The house source recommending method, the house source recommending device, the storage medium and the mobile terminal provided by the invention at least have the following beneficial effects:
(1) determining user tag data according to the user information, further determining the matching degree of the user and the house source based on the user tag data and the tag data of the house source, and finally recommending the house source according to the matching degree, so that the recommended house source can meet the user requirements more accurately;
(2) the questionnaire mode is adopted to collect the user information, and better user experience can be given to the user compared with the mode of directly inputting search conditions;
(3) the matching degree is determined by diversified labels, the house sources which best meet the requirements of the user can be obtained finally, the house sources which are arranged in the front and in the preset number are selected according to the sequence from high matching degree to low matching degree, and the user can find the most suitable house source at the highest speed.
Drawings
Fig. 1 is a flowchart of an embodiment of a house source recommendation method provided by the present invention.
Fig. 2 is a schematic structural diagram of an embodiment of the house source recommending apparatus provided by the present invention.
Fig. 3 is a schematic structural diagram of an embodiment of a mobile terminal provided in the present invention.
Detailed description of the preferred embodiments
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
Example one
Referring to fig. 1, the present embodiment provides a house source recommendation method, including:
step S101, collecting user information of a user in a preset mode;
step S102, determining user tag data respectively corresponding to one or more preset tags according to the user information;
step S103, matching the user tag data with a pre-stored preset tag of each house source in a plurality of house sources respectively to obtain the matching degree of the user and each house source;
step S104, selecting a preset number of house sources arranged in the front according to the matching degree of the user and each house source from high to low;
and step S105, pushing the preset number of house sources to the user.
According to the house source recommending method provided by the embodiment, the user tag data is determined according to the user information, the matching degree of the user and the house source is further determined based on the user tag data and the label data of the house source, and finally the house source is recommended according to the matching degree, so that the recommended house source can meet the user requirements more accurately.
Specifically, step S101 is executed, and user information of the user is collected in a predetermined manner, which specifically includes:
when a questionnaire filling request sent by a user is received, calling a questionnaire page to perform pushing display, and acquiring user information uploaded by the user through the questionnaire page; or
And acquiring user information of the user according to historical search data of the user.
In a preferred embodiment, the user information includes a city of a house, an age, a family condition, a sustainable monthly supply, and the like.
At the moment, the questionnaire mode is adopted to collect the user information, so that the user requirements can be more comprehensively known and better user experience can be provided for the user compared with the mode of directly inputting search conditions; or based on the historical search data of the user, the user information of the user is automatically analyzed and collected, manual operation of the user is not needed, and convenience and intellectualization are improved.
Further, step S102 is executed, and user tag data corresponding to one or more preset tags is determined according to the user information, where the preset tags include a city where the house source is located, a total house price, a house type, and a house area.
Determining user tag data respectively corresponding to one or more preset tags according to the user information, including:
determining the city where the house expected by the user is located according to the city where the user is located;
determining the total house price which can be borne by the user according to the age of the user and the sustainable monthly supply;
and determining the house type and the house area expected by the user according to the family member information.
Wherein, the total house price which can be borne by the user is calculated by the following conditions:
the first payment proportion is calculated according to 35 percent, and the total credit account accounts for 65 percent
Total sum of loan/0.65 ÷ total house price
Loan interest rate: 4.9 percent
The age is less than 30 loan years and is 30 years; age 30-35 loan year 20 years; age 35-45 loan year-old 20 years; age 45+ loan age 10 years.
If the user is a single person, determining that the house type expected by the user is a small-area living room, if the user is a family of three persons, determining that the house type expected by the user is two living rooms and three living rooms of 80-120 level, and if the user is a family of four persons, determining that the house type expected by the user is three living rooms or four living rooms of more than 120 level.
At the moment, the house type, the area and the total price are determined according to the self condition of the user, so that the matched house source can better meet the requirements of the user.
As a preferred embodiment, the user information further comprises customization data including a desired orientation, a desired floor, and a desired type. The preset labels further comprise house orientation, house floor and house type; therefore, in step S102, determining, according to the user information, user tag data corresponding to one or more preset tags, further includes:
and determining the house orientation, the house floor and the house type which are expected by the user according to the self-defined data.
At the moment, the user can also customize the tag data according to the self requirement so as to match the house source in an all-round way. The custom data is not limited to the expected orientation, the expected floor and the expected type, and may also include any other parameters related to the house purchasing requirement, and may be specifically set according to the actual requirement.
Further, step 103 is executed to match the user tag data with a pre-stored preset tag of each of the plurality of house sources, so as to obtain a matching degree between the user and each house source, which specifically includes:
matching the user tag data with a pre-stored preset tag of each house source in a plurality of house sources respectively to obtain tags and tag quantity matched with each house source by a user;
and determining the matching degree of the user and each house source according to the labels matched with the user and each house source and the number of the labels.
At this moment, the matching degree of the user and each house source can be accurately determined according to the matched tags and the number of the tags by respectively matching the user tag data with the preset tags of each house source.
For example, the user tag data includes a city where a house desired by the user is located, a total house price which can be borne by the user, a house type and a house area which are desired by the user, and also includes user-defined data such as a house orientation, a house floor and a house type which are desired by the user, and correspondingly, the preset tag of the house source includes a city where the house source is located, a total house price, a house type, a house area, a house orientation, a house floor and a house type; matching the user tag data with the city, the total house price, the house type, the house area, the house orientation, the house floor and the house type of each house source respectively to obtain matching tags and tag quantity, and finally, according to the matching tags and the tag quantity, accurately determining the matching degree of the user and each house source.
Further, the determining the matching degree between the user and each house source according to the tags matched with the user and each house source and the number of the tags includes:
obtaining a first matching parameter according to the label matched with each house source and the weight value corresponding to each label;
obtaining a second matching parameter according to the number of the tags matched with each house source by the user and the weight values corresponding to the different numbers of the tags;
and obtaining the matching degree of the user and each house source according to the first matching parameter and the second matching parameter.
At the moment, a first matching parameter is obtained based on the matching labels and the weight value of each label, a second matching parameter is obtained based on the number of the labels and the weight values of different label numbers, and the matching degree obtained by integrating multiple parameters of the first matching parameter and the second matching parameter is more accurate.
As a preferred embodiment, the first matching parameter and the second matching parameter are added to obtain the matching degree. But not limited thereto, such as a way of multiplying the first matching parameter and the second matching parameter may also be adopted.
For example, if the city expected by the user matches the city where the house source is located, the weight value is 10, if the total price that the user can bear matches the total house price, the weight value is 30, if the house type expected by the user matches the house type of the house source, the weight value is 20, and the weight values meeting the above-mentioned conditions are added to obtain the first matching parameter.
If one of the user-defined tags is consistent with one of the corresponding preset tags, the weight value is 10, if two tags are consistent, the weight value is 20, if three tags are consistent, the weight value is 30, and a second matching parameter is obtained according to the number of the tags meeting the condition.
And adding the first matching parameters and the second matching parameters to obtain a matching degree, and then executing a step S104 to select a preset number of room sources arranged in the front according to the sequence from high matching degree to low matching degree, wherein the preset number can be set according to the requirement.
At the moment, the matching degree is determined by diversified labels, the house sources which best meet the requirements of the user can be obtained finally, the house sources with the preset number are selected according to the sequence from high matching degree to low matching degree, and the user can find the most appropriate house source at the highest speed.
Further, step S105 is executed to push the preset number of house sources to the user.
Further, before executing step S101, the method further includes:
and when login request information sent by a user is received, verifying the login request information, and allowing the user to log in after the verification is passed.
At the moment, the user login information is verified, so that the user login safety is guaranteed.
The house source recommending method provided by the embodiment at least comprises the following beneficial effects:
(1) determining user tag data according to the user information, further determining the matching degree of the user and the house source based on the user tag data and the tag data of the house source, and recommending the house source according to the matching degree, so that the recommended house source can meet the user requirements more accurately;
(2) the questionnaire mode is adopted to collect the user information, and better user experience can be given to the user compared with the mode of directly inputting search conditions;
(3) the matching degree is determined by diversified labels, the house sources which best meet the requirements of the user can be obtained finally, the house sources which are arranged in the front and in the preset number are selected according to the sequence from high matching degree to low matching degree, and the user can find the most suitable house source at the highest speed.
Example two
Referring to fig. 2, the present embodiment provides a house source recommending apparatus, including:
an information acquisition module 201, configured to acquire user information of a user in a predetermined manner;
a data determining module 202, configured to determine, according to the user information, user tag data corresponding to one or more preset tags, respectively;
the matching module 203 is configured to match the user tag data with a pre-stored preset tag of each of the plurality of house sources, respectively, so as to obtain a matching degree between the user and each house source;
the house source selecting module 204 is configured to select, according to the matching degree between the user and each house source, a preset number of house sources arranged in the front in a descending order of the matching degree;
a pushing module 205, configured to push the preset number of house resources to the user.
Specifically, the information collecting module 201 is further configured to: when a questionnaire filling request sent by a user is received, calling a questionnaire page to perform pushing display, and acquiring user information uploaded by the user through the questionnaire page; or, collecting user information of the user according to historical search data of the user.
Further, the matching module 203 is further configured to: matching the user tag data with a pre-stored preset tag of each house source in a plurality of house sources respectively to obtain tags and tag quantity matched with each house source by a user; and determining the matching degree of the user and each house source according to the labels matched with the user and each house source and the number of the labels.
Further, the matching module 203 is further configured to: obtaining a first matching parameter according to the label matched with each house source and the weight value corresponding to each label; obtaining a second matching parameter according to the number of the tags matched with each house source by the user and the weight values corresponding to the different numbers of the tags; and obtaining the matching degree of the user and each house source according to the first matching parameter and the second matching parameter.
Further, the preset label comprises a city where the house is located, a total price of the house, house types and house areas; the user information comprises the city where the user is located, the age of the user, family member information and bearable monthly supply.
Further, the data determination module 202 is further configured to:
determining the city where the house expected by the user is located according to the city where the user is located;
determining the total house price which can be borne by the user according to the age of the user and the sustainable monthly supply;
and determining the house type and the house area expected by the user according to the family member information.
Further, the preset labels further comprise house orientation, house floor and house type; the user information also includes customization data including a desired orientation, a desired floor, and a desired type, and thus, the data determination module 202 is further operable to: and determining the house orientation, the house floor and the house type which are expected by the user according to the self-defined data.
Further, the apparatus provided in this embodiment further includes a login authentication module 206, configured to authenticate login request information sent by a user when the login request information is received, and allow the user to log in after the authentication is passed.
For the specific working principle, please refer to the first embodiment, which is not described herein again.
The house source recommending device provided by the embodiment at least has the following beneficial effects:
(1) determining user tag data according to the user information, further determining the matching degree of the user and the house source based on the user tag data and the tag data of the house source, and finally recommending the house source according to the matching degree, so that the recommended house source can meet the user requirements more accurately;
(2) the questionnaire mode is adopted to collect the user information, and better user experience can be given to the user compared with the mode of directly inputting search conditions;
(3) the matching degree is determined by diversified labels, the house sources which best meet the requirements of the user can be obtained finally, the house sources which are arranged in the front and in the preset number are selected according to the sequence from high matching degree to low matching degree, and the user can find the most suitable house source at the highest speed.
EXAMPLE III
Referring to fig. 3, the present embodiment provides a mobile terminal 300, which includes a processor 301 and a memory 302 connected to the processor 301, where the memory 302 stores a plurality of instructions, and the instructions can be loaded and executed by the processor 301, so that the processor 301 can execute the processing method of the online booking information.
In addition, the present embodiment also provides a storage medium, where the storage medium stores a plurality of instructions, and the instructions are loaded and executed by a processor, so that the processor can execute the processing method of the online booking information.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention. It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A house source recommendation method, comprising:
collecting user information of a user in a preset mode;
determining user tag data respectively corresponding to one or more preset tags according to the user information;
matching the user tag data with a pre-stored preset tag of each house source in a plurality of house sources respectively to obtain the matching degree of the user and each house source;
selecting a preset number of house sources arranged in the front according to the matching degree of the user and each house source and the sequence from high to low of the matching degree;
and pushing the preset number of house sources to the user.
2. The house source recommending method of claim 1, wherein the collecting of the user information of the user by a predetermined manner comprises:
when a questionnaire filling request sent by a user is received, calling a questionnaire page to perform pushing display, and acquiring user information uploaded by the user through the questionnaire page; or
And acquiring user information of the user according to historical search data of the user.
3. The house source recommendation method according to claim 1, wherein the step of matching the user tag data with a pre-stored preset tag of each house source in a plurality of house sources to obtain a matching degree between the user and each house source comprises:
matching the user tag data with a pre-stored preset tag of each house source in a plurality of house sources respectively to obtain tags and tag quantity matched with each house source by a user;
and determining the matching degree of the user and each house source according to the labels matched with the user and each house source and the number of the labels.
4. The house source recommending method of claim 3, wherein said determining the matching degree of the user and each house source according to the tags and the number of tags matched with each house source by the user comprises:
obtaining a first matching parameter according to the label matched with each house source and the weight value corresponding to each label;
obtaining a second matching parameter according to the number of the tags matched with each house source by the user and the weight values corresponding to the different numbers of the tags;
and obtaining the matching degree of the user and each house source according to the first matching parameter and the second matching parameter.
5. The house source recommending method according to claim 1, wherein the preset labels include a city where a house is located, a total house price, house unit type and house area; the user information comprises the city where the user is located, the age of the user, family member information and bearable monthly supply;
determining user tag data respectively corresponding to one or more preset tags according to the user information, including:
determining the city where the house expected by the user is located according to the city where the user is located;
determining the total house price which can be borne by the user according to the age of the user and the sustainable monthly supply;
and determining the house type and the house area expected by the user according to the family member information.
6. The house source recommendation method of claim 1, wherein the preset labels further comprise house orientation, house floor and house type; the user information further includes customization data including a desired orientation, a desired floor, and a desired type;
determining user tag data respectively corresponding to one or more preset tags according to the user information, including:
and determining the house orientation, the house floor and the house type which are expected by the user according to the self-defined data.
7. The house source recommending method of claim 1, wherein before collecting the user information of the user in a predetermined manner, the method further comprises:
and when login request information sent by a user is received, verifying the login request information, and allowing the user to log in after the verification is passed.
8. A house source recommendation device, comprising:
the information acquisition module is used for acquiring user information of a user in a preset mode;
the data determining module is used for determining user tag data respectively corresponding to one or more preset tags according to the user information;
the matching module is used for respectively matching the user tag data with a preset tag of each house source in a plurality of pre-stored house sources to obtain the matching degree of the user and each house source;
the house source selection module is used for selecting the house sources in the preset number from high to low according to the matching degree of the user and each house source;
and the pushing module is used for pushing the preset number of the house sources to the user.
9. A storage medium storing a plurality of instructions that are loadable and executable by a processor to enable the processor to perform the method of premises recommendation of any of claims 1-7.
10. A mobile terminal comprising a processor and a memory coupled to the processor, the memory storing a plurality of instructions that are loadable and executable by the processor to enable the processor to perform the method of any of claims 1-7.
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| CN201910918747.8A CN110796515A (en) | 2019-09-26 | 2019-09-26 | House resource recommendation method and device, storage medium and mobile terminal |
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| CN201910918747.8A CN110796515A (en) | 2019-09-26 | 2019-09-26 | House resource recommendation method and device, storage medium and mobile terminal |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112232933A (en) * | 2020-12-11 | 2021-01-15 | 深圳市房多多网络科技有限公司 | House source information recommendation method, device, equipment and readable storage medium |
| CN112528135A (en) * | 2020-11-27 | 2021-03-19 | 深圳市中博科创信息技术有限公司 | Resource pushing method, terminal device and storage medium |
| CN112561269A (en) * | 2020-12-07 | 2021-03-26 | 深圳市思为软件技术有限公司 | Advisor recommendation method and device |
| CN112949891A (en) * | 2020-05-22 | 2021-06-11 | 深圳市明源云客电子商务有限公司 | House resource recommendation method and device based on client intention prediction |
| CN113763030A (en) * | 2021-07-22 | 2021-12-07 | 北京房江湖科技有限公司 | House resource recommendation method and device, computer program product and storage medium |
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| CN112528135A (en) * | 2020-11-27 | 2021-03-19 | 深圳市中博科创信息技术有限公司 | Resource pushing method, terminal device and storage medium |
| CN112561269A (en) * | 2020-12-07 | 2021-03-26 | 深圳市思为软件技术有限公司 | Advisor recommendation method and device |
| CN112232933A (en) * | 2020-12-11 | 2021-01-15 | 深圳市房多多网络科技有限公司 | House source information recommendation method, device, equipment and readable storage medium |
| CN113763030A (en) * | 2021-07-22 | 2021-12-07 | 北京房江湖科技有限公司 | House resource recommendation method and device, computer program product and storage medium |
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