CN110852836A - Intelligent co-rental system and method based on big data processing - Google Patents
Intelligent co-rental system and method based on big data processing Download PDFInfo
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Abstract
The invention discloses an intelligent lease system and method based on big data processing, comprising the following steps: a first extraction module configured to extract the property lease information; a calculation module configured to calculate a maximum number of tenants; the second extraction module is configured to extract the same amount of tenant information; the first judgment module is configured to judge whether the tenant information is matched with the property lease information; the first screening module is configured to screen out the matched tenant information replaced by the new tenant information; the second judging module is configured to judge whether the daily lives and rest of the tenants are matched or not; the second screening module is configured to retain the tenant information with consistent work and rest and screen new tenant information to replace inconsistent tenant information; the sending module is configured to send the house renting information and the tenant information of the co-renting to the tenant according to the contact way; and the signing module is configured to generate a lease contract when all tenants agree with the house lease information and the tenant information of the lease combination.
Description
Technical Field
The invention relates to the field of data processing, in particular to an intelligent lease-closing system and method based on big data processing.
Background
With the increasing number of tenants, more and more tenants select a renting mode, so that the requirements of the tenants on houses can be met, and part of tenants can be saved.
However, social contradictions which are difficult to solve are brought by the co-tenants, for example, most of the sub-tenants are strangers who live under one eave, and the safety of the tenants cannot be guaranteed, especially under the condition of mixed tenants of men and women; different tenants have different daily lives, and the daily lives of part of the tenants are disturbed by other tenants, so that contradictions are caused; in addition, the problems that objects are easy to lose among tenants, water and electricity charge is not uniformly distributed and the like are difficult to adjust.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects in the background art, the embodiment of the invention provides an intelligent lease system based on big data processing and a method thereof, which can effectively solve the problems related to the background art.
The technical scheme is as follows:
the utility model provides an intelligence system of hiring together based on big data processing, includes the lease platform, the lease platform is stored with house property lease information and tenant information, house property lease information includes house property position, house type and lease price, tenant information includes target position, target house type, target price, life work and contact, and wherein, house property lease information is input by the landlord, inputs the system after the authentication, and tenant information is input by the tenant, inputs the system after the authentication, the system of hiring together includes:
the first extraction module is configured to extract the house leasing information published on the leasing platform;
a calculation module configured to calculate a maximum number of tenants to be combined according to the house type;
the second extraction module is configured to extract the same number of tenant information according to the number of the tenants;
the first judgment module is configured to judge whether the target position, the target house type and the target price are matched with the house rental information or not according to the tenant information;
the first screening module is configured to screen new tenant information to replace unmatched tenant information when the tenant information is unmatched with the real estate lease information, and the first judging module judges the new tenant information until the same number of tenant information can be reserved;
the second judging module is configured to judge whether the daily lives of the tenants are matched or not according to the daily lives;
the first judgment module and the second judgment module judge the new tenant information until the same amount of tenant information can be reserved;
the sending module is configured to send the house renting information and the renter information of the shared rents to the renters according to the contact way when the same number of the renter information are matched with each other;
and the signing module is configured to generate a lease contract when all tenants agree with the house lease information and the tenant information of the lease combination.
In a preferred embodiment of the present invention, the life information includes a sex request, a time to get up, and a time to fall asleep, and if the tenant does not have any request for any of the requests, the tenant does not fill in information corresponding to the request.
As a preferred embodiment of the present invention, the rental system further includes:
and the lease recording module is configured to establish a corresponding relation of tenant information of successful lease combination and record the corresponding relation when the signing module successfully signs the lease combination.
As a preferred embodiment of the present invention, the rental system further includes:
and the third judging module is configured to judge whether the tenant information extracted by the second extracting module has a corresponding relation.
As a preferred embodiment of the present invention, the rental system further includes:
the receiving module is configured to receive tenant information sent by a tenant;
the third extraction module is configured to extract tenant information stored in a rental platform by the tenant;
the fourth judgment module is configured to judge whether the received tenant information is completely consistent with the extracted tenant information;
the replacing module is configured to replace the tenant information in the rental platform with the received tenant information when the fourth judging module judges that the result is negative;
and the deleting module is configured to delete the corresponding relation containing the original tenant information in the lease recording module when the fourth judging module judges that the result is negative.
A working method of an intelligent lease system based on big data processing comprises the following working steps:
extracting house rental information published on a rental platform;
calculating the maximum number of the tenants according to the house type;
extracting the tenant information with the same number as the maximum number of tenants;
judging whether the tenant information is matched with the house property leasing information or not;
if not, rejecting unmatched tenant information, and screening new tenant information from the rental platform;
judging whether the screened new tenant information is matched with the house property leasing information;
if yes, judging whether the living work and rest included in each tenant information are matched or not until the tenant information with the same number as the maximum number of the tenants is screened out;
if not, rejecting unmatched tenant information, and screening new tenant information from the rental platform;
judging whether the screened new tenant information is matched with the house property lease information and other tenant information;
if yes, sending the house renting information and the renter information of the renters to a contact way of the renters until the number of the renter information which is the same as the maximum number of the renters to be rented is screened out;
judging whether all the tenants agree;
and if so, generating a rental contract for the tenancy.
As a preferred mode of the present invention, the determining whether the daily work and rest included in each tenant information matches further includes:
if the tenant information input by the tenant comprises one or more requirements of sex requirement, getting-up time and falling asleep time, judging each requirement in the daily work and rest one by one, and when any two daily work and rest comprise a certain requirement, judging that the requirements are matched;
and when all the items are matched, judging that the daily work and rest are matched.
As a preferred mode of the present invention, generating a rental contract further includes:
and establishing a corresponding relation for each tenant information and recording the corresponding relation.
As a preferred mode of the present invention, the determining whether the daily work and rest included in each tenant information matches further includes:
judging whether the tenant information has a corresponding relation;
and if so, directly judging that the tenant information with the corresponding relationship is matched.
As a preferred embodiment of the present invention, the present invention further comprises:
receiving first tenant information sent by a tenant;
extracting second tenant information stored in a rental platform by the tenant;
judging whether the first tenant information and the second tenant information are completely consistent;
if not, replacing the second tenant information with the first tenant information;
judging whether the second tenant information exists in a lease record module;
and if so, deleting the corresponding relation containing the second tenant information.
The invention realizes the following beneficial effects:
1. the house renting information is uploaded to a renting platform by a landlord, tenant information is uploaded to the renting platform by a tenant, wherein the tenant information comprises requirements of the tenant on houses and the tenant, the system automatically carries out intelligent matching on the house renting information and the tenant information to obtain the house renting information and the tenant information which are matched with each other, when the matching result of each tenant shows agreement, the system automatically generates a renting contract, and the landlord and the tenant can completely rent items according to the renting contract.
2. The tenant information comprises the life work and rest set by the tenant, and the life work and rest specifically comprises the sex requirement, the getting-up time and the falling-asleep time of the tenant for the tenant, so that the life work and rest between the tenants can be ensured to be similar, and the probability of being influenced by other people during sleep can be reduced.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a block diagram of a lease system structure provided in the present invention.
Fig. 2 is a flowchart of a first working method of the rental system provided by the present invention.
Fig. 3 is a flowchart of a method for mapping tenant information according to the present invention.
Fig. 4 is a flowchart of a second working method of the rental system provided by the present invention.
Fig. 5 is a flowchart of a tenant information change method provided by the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Example one
As shown in fig. 1, this embodiment provides an intelligent lease system based on big data processing, the lease system includes a lease platform, house lease information and tenant information are stored in the lease platform, the house lease information includes house location, house type and lease price, the tenant information includes target location, target house type, target price, daily work and contact mode, wherein, the house lease information is input by the landlord, the system is input after the certification, the tenant information is input by the tenant, the system is input after the certification, the system is characterized in that, the lease system includes: a first extraction module 101 configured to extract the property rental information published on the rental platform; a calculation module 102 configured to calculate a maximum number of tenants per house type; a second extraction module 103 configured to extract the same number of tenant information according to the number of the tenants; a first judging module 104, configured to judge whether the target location, the target house type and the target price are all matched with the property lease information according to the tenant information; the first screening module 105 is configured to screen new tenant information to replace unmatched tenant information when the tenant information is unmatched with the real estate rental information, and the first judging module 104 judges the new tenant information again until the same number of tenant information can be reserved; the second judging module 106 is configured to judge whether the daily lives of the tenants are matched according to the daily lives; the second screening module 107 is configured to, when the daily lives and rest among the tenants are not matched, retain tenant information with consistent work and screen new tenant information to replace the inconsistent tenant information, and the first judging module 104 and the second judging module 106 judge the new tenant information again until the same amount of tenant information can be retained; the sending module 108 is configured to send the property lease information and the leased leaser information of the shared lease to the leaser according to the contact way when the same number of the leaser information are matched with each other; and the signing module 109 is configured to generate a lease contract when all tenants agree with the house lease information and the tenant information of the lease.
The life information comprises sex requirements, getting-up time and falling-asleep time, and if no requirements are required by the tenant, the information aiming at the requirements is not filled.
The system of renting still includes:
and the lease recording module 110 is configured to establish a corresponding relationship between the tenant information of successful lease and record the corresponding relationship when the lease module 109 successfully subscribes the lease.
The system of renting still includes:
a third determining module 111 configured to determine whether there is a corresponding relationship in the tenant information extracted by the second extracting module 103.
The system of renting still includes:
a receiving module 112 configured to receive tenant information sent by a tenant;
a third extraction module 113 configured to extract tenant information stored in the rental platform by the tenant;
a fourth determining module 114 configured to determine whether the received tenant information is completely consistent with the extracted tenant information;
a replacing module 115, configured to, when the fourth determining module 114 determines that the result is negative, replace the tenant information in the rental platform with the received tenant information by the replacing module 115;
a deleting module 116, configured to delete the corresponding relationship including the original tenant information in the lease record module 110 when the fourth determining module 114 determines that the result is negative.
Specifically, the users of the system comprise two identities, namely a landlord and a rental tenant, the landlord and the rental tenant need to be respectively registered to become users of the rental system, and then the system can be used behind the users of the rental system, after the registration is finished, the landlord uploads the house rental information to the rental platform in a text, picture and video mode, and after the registration is finished, the house rental information is published on the rental platform after the auditing and authentication of workers of the rental platform are finished.
The house renting information comprises a house position, a house type, renting prices and a house-east contact mode, wherein the house position is specifically located on a certain floor of a certain building, the house type comprises the orientation and the area of each room, and the renting prices comprise the renting prices of the rooms.
And the tenant uploads tenant information to the lease platform, the tenant information is stored in the lease platform after the tenant information is audited and authenticated by staff of the lease platform, and both the landlord and the tenant need to be authenticated in a real-name system.
The tenant information comprises a plurality of target positions, a plurality of target house types, a plurality of target prices, a plurality of daily jobs and rest and a plurality of contact ways, and only one of the target positions is matched with the house property position; the target house type comprises the requirements of the tenant on the whole house and the requirements of the tenant on the rented units, for example, the former can be set as two rooms for one toilet or three rooms for two toilets, and the latter can be set as a main bed or a secondary bed; the target price may be set to one price period; the daily work and rest comprises the sex requirement, the getting-up time and the falling-asleep time of the closing tenant, wherein the getting-up time and the falling-asleep time can be set to be a time interval.
Example two
As shown in fig. 2, the present embodiment provides a working method of an intelligent rental system based on big data processing, including the following working steps:
extracting house rental information published on a rental platform; calculating the maximum number of the tenants according to the house type; extracting the tenant information with the same number as the maximum number of tenants; judging whether the tenant information is matched with the house property leasing information or not; if not, rejecting unmatched tenant information, and screening new tenant information from the rental platform; judging whether the screened new tenant information is matched with the house property leasing information; if yes, judging whether the living work and rest included in each tenant information are matched or not until the tenant information with the same number as the maximum number of the tenants is screened out; if not, rejecting unmatched tenant information, and screening new tenant information from the rental platform; judging whether the screened new tenant information is matched with the house property lease information and other tenant information; if yes, sending the house renting information and the renter information of the renters to a contact way of the renters until the number of the renter information which is the same as the maximum number of the renters to be rented is screened out; judging whether all the tenants agree; and if so, generating a rental contract for the tenancy.
Judging whether the daily work and rest included in each tenant information is matched further comprises:
if the tenant information input by the tenant comprises one or more requirements of sex requirement, getting-up time and falling asleep time, judging each requirement in the daily work and rest one by one, and when any two daily work and rest comprise a certain requirement, judging that the requirements are matched; and when all the items are matched, judging that the daily work and rest are matched.
Specifically, the embodiment can perform intelligent matching between the house rental information and the tenant information and between the house rental information and the tenant information, and seek the most appropriate co-rental relationship.
The house rental information published on the rental platform is sorted in a descending order according to the published date, that is, the most recently published house rental information is arranged at the top and sorted downwards, and in this embodiment, the house rental information is extracted and analyzed according to the sorting method.
Taking any property lease information as an example, the maximum number of tenants that can be accommodated by the house is calculated according to the property lease information including the house type, the number of tenants is based on the number of bedrooms, for example, if the house type includes two bedrooms, the maximum number of tenants is two.
After the maximum number of tenants is determined, the same number of tenant information as the maximum number of tenants is extracted from the lease platform, for example, if the maximum number of tenants is two, two tenant information are extracted first, and the following embodiments are described by taking the maximum number of tenants as two.
Judging whether the tenant information is matched with the house property leasing information or not, comparing the target position, the target house type and the target price which are included by the tenant information with the house property position, the house type and the leasing price which are included by the house property leasing information respectively, and comparing the two tenant information when the target position, the house type and the leasing price are matched, namely the house property position is located at one of the target positions, the house type is located at one of the target house types, and the leasing price is located in a target price interval.
If one of the three is not matched, the unmatched tenant information is removed, and one tenant information is screened out again and compared with the house renting information again until two tenant information matched with the house renting information appear.
When the two pieces of tenant information are compared, whether the life work and rest included in the tenant information are matched or not is mainly judged, and whether the house types included in the tenant information are matched or not is judged.
When living things are compared, the coincidence degree of the falling-asleep time period and the getting-up time period is judged, the span of the time periods is not more than one hour, in the embodiment, a preset coincidence degree is set, when both calculated coincidence degrees are more than or equal to the preset coincidence degree, the living things of two tenants are matched, for example, the preset coincidence degree is set to be 60%, the falling-asleep time period of the tenant A is [23:00,00:00], the getting-up time period is [7:30,8:00], the falling-asleep time period of the tenant B is [22:40, 23:40], the getting-up time is [7:20, 7:50], the coincidence degree of the falling-asleep time periods of the tenants A and the B is 2/3, the coincidence degree of the getting-up time is 2/3, and the coincidence degree of the getting-up time is more than 60%, and the living things of the tenants A and the B are.
When house types are compared, whether the single units required by the two tenants are overlapped or not is judged, and if the single units are not overlapped, the house types of A and B are matched; if the result is coincident, screening out the tenant information of C, D by taking the tenant information of A, B as a reference, if the tenant information of C, D is matched with the house property lease information, comparing the living work of A with the living work of C, comparing the living work of B with the living work of D, comparing the house type until a new tenant information is matched with the tenant information of A or B, stopping the comparison of the other reference, mutually sending the two successfully matched tenant information and the house property lease information to the other tenant, generating a co-tenant contract for the landlord and the two tenants after the two tenants agree, and negotiating and signing a formal contract between the landlord and the tenant according to the co-tenant contract.
EXAMPLE III
As shown in fig. 3, generating the rental contract further includes:
and establishing a corresponding relation for each tenant information and recording the corresponding relation.
As shown in fig. 4, determining whether the daily lives and rest included in each tenant information match further includes:
judging whether the tenant information has a corresponding relation; and if so, directly judging that the tenant information with the corresponding relationship is matched.
As shown in fig. 5, receiving first tenant information sent by a tenant; extracting second tenant information stored in a rental platform by the tenant; judging whether the first tenant information and the second tenant information are completely consistent; if not, replacing the second tenant information with the first tenant information; judging whether the second tenant information exists in a lease record module; and if so, deleting the corresponding relation containing the second tenant information.
Specifically, in order to facilitate matching tenant information as soon as possible next time, the embodiment establishes a corresponding relationship between tenant information that is successfully signed a lease contract, for example, when comparing two tenant information next time, it is determined whether the two tenant information have a corresponding relationship, if yes, the two tenant information can be directly determined to be matched without comparison.
The tenant can change the tenant information by oneself, after the tenant information is changed, the first tenant information will replace the second tenant information, and the corresponding relation including the second tenant information is all deleted from the lease platform.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All equivalent changes or modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (10)
1. The utility model provides an intelligence system of hiring together based on big data processing, includes the lease platform, the lease platform is stored with house property lease information and tenant information, house property lease information includes house property position, house type and lease price, tenant information includes target position, target house type, target price, life work and contact, and wherein, house property lease information is input by the landlord, inputs the system after the authentication, and tenant information is input by the tenant, inputs the system after the authentication, its characterized in that, the system of hiring together includes:
the first extraction module is configured to extract the house leasing information published on the leasing platform;
a calculation module configured to calculate a maximum number of tenants to be combined according to the house type;
the second extraction module is configured to extract the same number of tenant information according to the number of the tenants;
the first judgment module is configured to judge whether the target position, the target house type and the target price are matched with the house rental information or not according to the tenant information;
the first screening module is configured to screen new tenant information to replace unmatched tenant information when the tenant information is unmatched with the real estate lease information, and the first judging module judges the new tenant information until the same number of tenant information can be reserved;
the second judging module is configured to judge whether the daily lives of the tenants are matched or not according to the daily lives;
the first judgment module and the second judgment module judge the new tenant information until the same amount of tenant information can be reserved;
the sending module is configured to send the house renting information and the renter information of the shared rents to the renters according to the contact way when the same number of the renter information are matched with each other;
and the signing module is configured to generate a lease contract when all tenants agree with the house lease information and the tenant information of the lease combination.
2. The intelligent renting system based on big data processing according to claim 1, wherein: the life information comprises sex requirements, getting-up time and falling-asleep time, and if no requirements are required by the tenant, the information aiming at the requirements is not filled.
3. The intelligent renting system based on big data processing according to claim 1, wherein: the system of renting still includes:
and the lease recording module is configured to establish a corresponding relation of tenant information of successful lease combination and record the corresponding relation when the signing module successfully signs the lease combination.
4. The intelligent renting system based on big data processing according to claim 3, wherein: the system of renting still includes:
and the third judging module is configured to judge whether the tenant information extracted by the second extracting module has a corresponding relation.
5. The intelligent renting system based on big data processing according to claim 3, wherein: the system of renting still includes:
the receiving module is configured to receive tenant information sent by a tenant;
the third extraction module is configured to extract tenant information stored in a rental platform by the tenant;
the fourth judgment module is configured to judge whether the received tenant information is completely consistent with the extracted tenant information;
the replacing module is configured to replace the tenant information in the rental platform with the received tenant information when the fourth judging module judges that the result is negative;
and the deleting module is configured to delete the corresponding relation containing the original tenant information in the lease recording module when the fourth judging module judges that the result is negative.
6. The working method of the intelligent rent-closing system based on big data processing according to any one of claims 1-5, characterized by comprising the following working steps:
extracting house rental information published on a rental platform;
calculating the maximum number of the tenants according to the house type;
extracting the tenant information with the same number as the maximum number of tenants;
judging whether the tenant information is matched with the house property leasing information or not;
if not, rejecting unmatched tenant information, and screening new tenant information from the rental platform;
judging whether the screened new tenant information is matched with the house property leasing information;
if yes, judging whether the living work and rest included in each tenant information are matched or not until the tenant information with the same number as the maximum number of the tenants is screened out;
if not, rejecting unmatched tenant information, and screening new tenant information from the rental platform;
judging whether the screened new tenant information is matched with the house property lease information and other tenant information;
if yes, sending the house renting information and the renter information of the renters to a contact way of the renters until the number of the renter information which is the same as the maximum number of the renters to be rented is screened out;
judging whether all the tenants agree;
and if so, generating a rental contract for the tenancy.
7. The working method of the intelligent rental system based on big data processing according to claim 6, wherein: judging whether the daily work and rest included in each tenant information is matched further comprises:
if the tenant information input by the tenant comprises one or more requirements of sex requirement, getting-up time and falling asleep time, judging each requirement in the daily work and rest one by one, and when any two daily work and rest comprise a certain requirement, judging that the requirements are matched;
and when all the items are matched, judging that the daily work and rest are matched.
8. The working method of the intelligent rental system based on big data processing according to claim 6, wherein: generating the rental contract further comprises:
and establishing a corresponding relation for each tenant information and recording the corresponding relation.
9. The working method of the intelligent rental system based on big data processing according to claim 8, wherein: judging whether the daily work and rest included in each tenant information is matched further comprises:
judging whether the tenant information has a corresponding relation;
and if so, directly judging that the tenant information with the corresponding relationship is matched.
10. The working method of the intelligent rental system based on big data processing according to claim 8, wherein: further comprising:
receiving first tenant information sent by a tenant;
extracting second tenant information stored in a rental platform by the tenant;
judging whether the first tenant information and the second tenant information are completely consistent;
if not, replacing the second tenant information with the first tenant information;
judging whether the second tenant information exists in a lease record module;
and if so, deleting the corresponding relation containing the second tenant information.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201911007443.2A CN110852836A (en) | 2019-10-22 | 2019-10-22 | Intelligent co-rental system and method based on big data processing |
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| CN201911007443.2A CN110852836A (en) | 2019-10-22 | 2019-10-22 | Intelligent co-rental system and method based on big data processing |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112509277A (en) * | 2020-11-13 | 2021-03-16 | 北京软通智慧城市科技有限公司 | Rental house monitoring method, device, equipment and storage medium |
| TWI799900B (en) * | 2021-06-23 | 2023-04-21 | 陳儀坦 | Shared rental platform system |
-
2019
- 2019-10-22 CN CN201911007443.2A patent/CN110852836A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112509277A (en) * | 2020-11-13 | 2021-03-16 | 北京软通智慧城市科技有限公司 | Rental house monitoring method, device, equipment and storage medium |
| TWI799900B (en) * | 2021-06-23 | 2023-04-21 | 陳儀坦 | Shared rental platform system |
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Application publication date: 20200228 |