CN111080407A - House information recommendation method and device, electronic equipment and readable storage medium - Google Patents
House information recommendation method and device, electronic equipment and readable storage medium Download PDFInfo
- Publication number
- CN111080407A CN111080407A CN201911227380.1A CN201911227380A CN111080407A CN 111080407 A CN111080407 A CN 111080407A CN 201911227380 A CN201911227380 A CN 201911227380A CN 111080407 A CN111080407 A CN 111080407A
- Authority
- CN
- China
- Prior art keywords
- information
- house
- client
- price
- range
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 29
- 230000015654 memory Effects 0.000 claims description 28
- 230000001737 promoting effect Effects 0.000 abstract 1
- 238000004891 communication Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 10
- 238000012545 processing Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 230000002093 peripheral effect Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000012423 maintenance Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012163 sequencing technique Methods 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0645—Rental transactions; Leasing transactions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/16—Real estate
Abstract
The invention discloses a house information recommendation method, a house information recommendation device, electronic equipment and a computer readable storage medium, wherein the method comprises the following steps: acquiring price preference information of a client; acquiring the working position information of a client; acquiring business circle preference information of a client; and recommending house information according to the price preference information, the working position information and the business district preference information. The invention solves the problems that the publicity efficiency of rentable and saleable house sources is low, the selectivity of customers is limited and more suitable house source information cannot be provided for the customers due to single recommended house source in the prior art, thereby improving the precision of house source provision for the customers, improving the house source selection efficiency of the customers, promoting the publicity of available house sources and improving the customer experience.
Description
Technical Field
The invention relates to the field of information processing, in particular to a house information recommendation method and device, electronic equipment and a computer-readable storage medium.
Background
With the progress of science and technology, computer technology is popularized and applied to the production and life of human beings to the greatest extent, and particularly, the popularization of networks makes the publishing, storage, updating and sharing of data information more convenient. In terms of house intermediary operation, the traditional transaction mode is thoroughly changed, the internet becomes a main channel for releasing house property intermediary information, the product of house intermediary operation is essentially an information resource, the information is efficiently managed, profits are created to the maximum extent by utilizing the information, and the accurate and rapid processing of a large amount of information is very important by fully utilizing the network and the computer technology.
Currently, for clients with house renting and house buying requirements, the clients need to log on a Location Based Services (LBS) related platform through the internet, input corresponding house renting and house buying source requirements, and can query house sources meeting conditions in shared house sources. The function of the recommended house source under the current LBS house renting scene is divided into a business district searching person and a room searching person, but the recommended house source condition is single, for example, only a correspondingly suitable house source can be recommended according to the price preference of a client or the geographic position preference of the client for the house, so that the advertising efficiency of the rentable and saleable house source is low, the selectivity of the client is limited, and more suitable house source information cannot be provided for the client.
Disclosure of Invention
In view of this, embodiments of the present invention provide a house information recommending method, an apparatus, an electronic device, and a computer-readable storage medium, so as to solve the problems in the prior art that a single house source recommending source is used, so that the propaganda efficiency of a rentable house source is low, the selectivity of a client is limited, and more appropriate house source information cannot be provided for the client.
Therefore, the embodiment of the invention provides the following technical scheme:
in a first aspect of the present invention, a method for recommending house information is provided, including: acquiring price preference information of a client; acquiring the working position information of a client; acquiring business circle preference information of a client; and recommending house information according to the price preference information, the working position information and the business district preference information.
Optionally, the obtaining price preference information of the customer comprises: acquiring first price information of a client for renting a house historically; acquiring second price information of historical clicks and/or searches and/or houses collected by the client; and calculating the price preference information according to the first price information and/or the second price information.
Optionally, the obtaining of the work location information of the client includes: acquiring daytime historical positioning information of a client; and calculating the working position information according to the daytime historical positioning information of the client.
Optionally, the obtaining of the business district preference information of the customer includes: obtaining the position information of a historical rented house of a client; acquiring business circle information of historical search and/or collection and/or click of a client; and calculating the preference information of the business district according to the position information of the house rented by the customer history and/or the business district information.
Optionally, recommending the house information according to the price preference information, the work location information, and the business district preference information includes: determining first range house information according to the price preference information; determining house information in a second range according to the working position information; the position of the second range of the house information is within a first distance range from the working position information; determining house information in a third range according to the business district preference information; wherein the location of the third range of premise information is within a second distance range from the location of the business district preference information; and recommending house information according to the house information in the first range, the house information in the second range and the house information in the third range.
In a second aspect of the present invention, there is provided a house information recommending apparatus, including: the first acquisition module is used for acquiring price preference information of a client; the second acquisition module is used for acquiring the working position information of the client; the third acquisition module is used for acquiring business district preference information of the client; and the recommending module is used for recommending the house information according to the price preference information, the working position information and the business district preference information.
Optionally, the first obtaining module includes: the system comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring first price information of a client for renting a house in history; the second obtaining unit is used for obtaining second price information of historical clicking and/or searching and/or house collection of the client; and the third acquisition unit is used for calculating the price preference information according to the first price information and/or the second price information.
Optionally, the second obtaining module includes: the fourth acquisition unit is used for acquiring the daytime historical positioning information of the client; and the fifth acquisition unit is used for calculating the working position information according to the daytime historical positioning information of the client.
Optionally, the third obtaining unit includes: the sixth acquisition unit is used for acquiring the position information of the historic rented house of the client; the seventh acquisition unit is used for acquiring business circle information of historical search and/or collection and/or click of the client; and the eighth acquisition unit is used for calculating the preference information of the business district according to the position information of the rented house in the customer history and/or the business district information.
Optionally, the recommendation module includes: a first determination unit, configured to determine first range house information according to the price preference information; the second determining unit is used for determining house information in a second range according to the working position information; the position of the second range of the house information is within a first distance range from the working position information; the third determining unit is used for determining house information in a third range according to the business district preference information; wherein the location of the third range of premise information is within a second distance range from the location of the business district preference information; and the recommending unit is used for recommending the house information according to the house information in the first range, the house information in the second range and the house information in the third range.
In a third aspect of the present invention, there is provided an electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method of recommending premise information according to any of the first aspects.
In a fourth aspect of the present invention, there is provided a computer-readable storage medium, on which computer instructions are stored, which when executed by a processor, implement the house information recommendation method according to any one of the first aspect.
The technical scheme of the embodiment of the invention has the following advantages:
the embodiment of the invention provides a house information recommendation method, a house information recommendation device, electronic equipment and a computer readable storage medium, wherein the house information recommendation method comprises the following steps: acquiring price preference information of a client; acquiring the working position information of a client; acquiring business circle preference information of a client; and recommending house information according to the price preference information, the working position information and the business district preference information. The embodiment of the invention combines the price preference information, the working position information and the business district preference information, and solves the problems that the advertising efficiency of rentable and saleable house sources is low, the selectivity of customers is limited and more appropriate house source information cannot be provided for the customers due to single recommended house source in the prior art, so that the accuracy of providing the house sources for the customers is improved, the efficiency of selecting the house sources by the customers is improved, and the advertising of available house sources is promoted.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a house information recommendation method according to an embodiment of the present invention;
fig. 2 is another flowchart of a house information recommendation method according to an embodiment of the present invention;
fig. 3 is a block diagram of the structure of a house information recommending apparatus according to an embodiment of the present invention;
FIG. 4 is a block diagram of a first acquisition module according to an embodiment of the invention;
FIG. 5 is a block diagram of a second acquisition module according to an embodiment of the invention;
FIG. 6 is a block diagram of a third obtaining module according to an embodiment of the present invention;
FIG. 7 is a block diagram of a recommendation module according to an embodiment of the present invention;
fig. 8 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
According to an embodiment of the present invention, there is provided a premise information recommendation method, it should be noted that the steps shown in the flowchart of the drawings may be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that here.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
In this embodiment, a method for recommending house information is provided, which may be used in smart phones, portable tablet devices (PAD), Personal Digital Assistants (PDA), and the like, smart devices (electronic devices) having display, processing, and network connection functions, and fig. 1 and 2 are flowcharts of a method for recommending house information according to an embodiment of the present invention, and refer to fig. 1 and 2, where the flowchart includes the following steps:
step S11: price preference information of a customer is obtained. The price of the historical house renting of the client reflects the psychological price of the client for replacing the house renting to a certain extent, so in an optional embodiment, the price information of the historical house renting of the client is obtained, and the price preference information of the client is obtained according to the price information of the historical house renting of the client. The price of the historical click and/or search and/or house collection of the client also reflects the price demand of the client for renting houses to a certain extent, so in another alternative embodiment, the price information of the historical click and/or search and/or house collection of the client is obtained, and the price preference information of the client is obtained according to the price information of the historical click and/or search and/or house collection of the client. Those skilled in the art can use other methods in the prior art to obtain the price preference information of the customer according to the description of the embodiment.
Step S12: and acquiring the working position information of the client. For most people, the day of the working day, for example, 09:00 to 18:00 hours, will be on duty in the unit, so in an alternative embodiment, the customer day historical location information is obtained, and the working location information is obtained based on the customer day historical location information. Those skilled in the art should understand that the obtaining of the working location information of the client is not limited to the embodiment, and it is within the scope of the embodiment to obtain the working location information in other manners according to actual needs.
Step S13: and acquiring business circle preference information of the client. The customer's business district preference information may be embodied in a number of ways, for example, the customer may prefer to rent a business district near a house before, and therefore in an alternative embodiment, historical house-renting location information of the customer is obtained, wherein the historical house-renting location information may be the last house-renting location information, and the business district preference information is obtained according to the historical house-renting location information of the customer. In addition, the business turn information of the historical search and/or collection and/or click of the client also reflects the business turn preference information of the client to a certain extent, so in an optional embodiment, the business turn information of the historical search and/or collection and/or click of the client is obtained, and the business turn preference information is calculated according to the business turn information of the historical search and/or collection and/or click. Those skilled in the art can obtain the aforementioned business turn preference information in other manners in the prior art according to the description of the embodiment.
Step S14: and recommending house information according to the price preference information, the working position information and the business district preference information.
Through the steps, the acquired three ways of the price preference information, the working position information and the business district preference information of the client are combined to recommend the house resources to the client, and compared with the prior art that the house resources are recommended to the client only according to one condition such as the price preference of the client, the house resources are clear in arrangement and definite in purpose, the recommended house resources are more accurate and accord with the requirements of the client, the time for the client to select the house resources is shortened, the user experience is improved, and the propaganda of the available house resources is promoted.
The step S14 is related to recommending house information according to the price preference information, the work location information, and the business district preference information, and in an optional embodiment, different weight values are configured for the price preference information, the work location information, and the business district preference information, and the weight value of each information is a value greater than or equal to zero and less than 1, for example, the weight value of the business district preference information, the weight value of the work location information, and the weight value of the price preference information decrease in sequence. And recommending houses for the customers according to the three information and the respective weight values, so that house information is dynamically recommended according to price preference information, working position information and business district preference information. More specifically, a first recommendation list is obtained according to price preference information, a second recommendation list is obtained according to the working position information, a third recommendation list is obtained according to the business district preference information, and duplicate removal processing is performed to remove duplicate recommendation items under the condition that the first recommendation list, the second recommendation list and the third recommendation list cover the same house source; grouping the first recommendation list, the second recommendation list and the third recommendation list after the duplication removal respectively, for example, grouping every 5 recommendation items, and combining the groups of the first recommendation list, the second recommendation list and the third recommendation list according to the weight values configured for the price preference information, the work position information and the business district preference information to further obtain the recommendation lists.
In order to better match the customer's demand for the house source, in an alternative embodiment, house characteristic information, such as the orientation characteristic, floor characteristic, lighting characteristic, etc. of the house, is also considered on the basis of recommending the house information according to the price preference information, the work location information and the business district preference information.
The step S14 is related to recommending house information according to price preference information, work location information, and business turn preference information, and specifically, determining first range house information according to the obtained price preference information, where the price of the first range house information is within a threshold range, for example, the first customer searches for a house source in a price range of 1500-2500 yuan, which indicates that the required price of the first customer is within the range, the system recommends the house source information in the current city within the price range, and in addition, the system calculates the orientation feature preference of the first customer for the house according to that the house sources viewed by the first customer are in the south direction, and then recommends appropriate house source information according to the above requirements of the first customer and performs local ranking and scoring according to the above requirements of the first customer. Determining second-range house information according to the working position information, wherein the position of the second-range house information is within a first distance range from the working position information, the first distance can be the distance between N bus stations and the ground, and can also be a space distance, for example, according to a system positioning record, the working ground of a client A is positioned as 'Kongyang first house', the system acquires the commuting time between the subway stations from a subway commuting time maintenance module, recommends room source information in a 1-hour commuting circle according to the 'Kongyang first house' close to the subway station, and then performs local sequencing and scoring on the recommended room source information by combining the previous demand price and room characteristic demand of the client A. Determining house information in a third range according to the business district preference information; wherein the position of the house information in the third range is within a second distance range from the position of the preference information of the business circle, the second distance can be the distance between N stations of the bus or the space distance, such as the house source information near the youth road collected/viewed by the customer A, the system constructs an index module of the subways around the subways according to the topological relation of the subways, selects the subway line from 1 station/2 station of the subways to the youth road according to the communication relation of the subways, or recommends the subways from two stations to the youth road according to the transfer relation of the subways, if the communication relation of the youth road is sparse, the system can obtain the index relation of the peripheral grids of the geohash grids according to the urban core area and the peripheral network maintenance module, and calculates the business circle with close space distance according to the position of the youth road and recommends the house source of the peripheral business circle of the target business circle, the recommendation range is expanded, the diversity of house resources is ensured, and the selectivity of customers is increased; and according to the recommended house source information in the business circle, according to the price range selected by the customer A and the preference requirement on the room characteristics, carrying out local sequencing scoring on the recommended house source information.
And recommending house information according to the house information of the first range, the house information of the second range and the house information of the third range. The method comprises the steps of performing comprehensive ranking and scoring according to three recommended ranking and scoring house source information, performing scoring and ranking according to the sequence of business circle preference information of a client, working position information of the client and price preference information of the client, namely performing overall ranking and scoring according to house sources which are near young roads, have proper commuting time and meet the requirements in price, and forming a final recommendation list to be presented to the client. Of course, the sequence of the business district preference information, the working position information of the customer and the price preference information of the customer is not limited to this, and other sequences can also be realized for the purpose of recommending appropriate house resources to the customer.
In this embodiment, a house information recommending apparatus is further provided, and the apparatus is used to implement the foregoing embodiments and preferred embodiments, and the description already made is omitted. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
The present embodiment provides a house information recommending apparatus, as shown in fig. 3, including: a first obtaining module 31, configured to obtain price preference information of a customer; a second obtaining module 32, configured to obtain the working location information of the client; a third obtaining module 33, configured to obtain business district preference information of the customer; and the recommending module 34 is used for recommending the house information according to the price preference information, the working position information and the business district preference information.
Fig. 4 is a block diagram of a first obtaining module according to an embodiment of the present invention, and as shown in fig. 4, the first obtaining module 31 includes: a first obtaining unit 311, configured to obtain first price information of a customer's historical house renting; a second obtaining unit 312, configured to obtain second price information of a customer's historical click and/or search and/or house collection; a third obtaining unit 313, configured to calculate the price preference information according to the first price information and/or the second price information.
Fig. 5 is a block diagram of a second obtaining module according to an embodiment of the present invention, and as shown in fig. 5, the second obtaining module 32 includes: a fourth obtaining unit 321, configured to obtain historical daytime positioning information of the client; a fifth obtaining unit 322, configured to estimate the working location information according to the daytime historical positioning information of the customer.
Fig. 6 is a block diagram of a third obtaining module according to an embodiment of the present invention, and as shown in fig. 6, the third obtaining unit 33 includes: a sixth obtaining unit 331 configured to obtain client history rental house location information; a seventh obtaining unit 332, configured to obtain business turn information of historical search and/or collection and/or click of the client; an eighth obtaining unit 333, configured to calculate business district preference information according to the location information of the rented house and/or the business district information in the customer history.
Fig. 7 is a block diagram of a recommendation module according to an embodiment of the present invention, and as shown in fig. 7, the recommendation module 34 includes: a first determining unit 341 configured to determine first range house information according to the price preference information; a second determining unit 342 for determining second-range house information from the work position information; the position of the second range of the house information is within a first distance range from the working position information; a third determining unit 343, configured to determine third range room information according to the business turn preference information; the position of the house information in the third range is within a second distance range from the position of the preference information of the business district; a recommending unit 344 configured to recommend the house information according to the first range house information, the second range house information, and the third range house information.
The premise information recommendation device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC circuit, a processor and a memory executing one or more software or fixed programs, and/or other devices that can provide the above-mentioned functions.
Further functional descriptions of the modules are the same as those of the corresponding embodiments, and are not repeated herein.
An embodiment of the present invention further provides an electronic device, which includes the house information recommendation apparatus shown in fig. 3.
Referring to fig. 8, as shown in fig. 8, the electronic device may include: at least one processor 801, such as a CPU (Central Processing Unit), at least one communication interface 803, memory 804, at least one communication bus 802. Wherein a communication bus 802 is used to enable connective communication between these components. The communication interface 803 may include a Display (Display) and a Keyboard (Keyboard), and the optional communication interface 803 may also include a standard wired interface and a standard wireless interface. The Memory 804 may be a high-speed RAM (Random Access Memory) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The memory 804 may optionally be at least one memory device located remotely from the processor 801 as previously described. Wherein the processor 801 may be combined with the apparatus described in fig. 3, the memory 804 stores an application program, and the processor 801 calls the program code stored in the memory 804 for executing the steps of any of the above-mentioned house information recommending methods.
The communication bus 802 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The communication bus 802 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 8, but this is not intended to represent only one bus or type of bus.
The memory 804 may include a volatile memory (RAM), such as a random-access memory (RAM); the memory may also include a non-volatile memory (english: non-volatile memory), such as a flash memory (english: flash memory), a hard disk (english: hard disk drive, abbreviation: HDD), or a solid-state drive (english: SSD); the memory 804 may also comprise a combination of the above-described types of memory.
The processor 801 may be a Central Processing Unit (CPU), a Network Processor (NP), or a combination of a CPU and an NP.
The processor 801 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or a combination thereof. The aforementioned PLD may be a Complex Programmable Logic Device (CPLD), a field-programmable gate array (FPGA), a General Array Logic (GAL), or any combination thereof.
Optionally, the memory 804 is also used for storing program instructions. The processor 801 may call program instructions to implement the premise information recommendation method as shown in the embodiments of fig. 1 and 2 of the present application.
The embodiment of the invention also provides a non-transitory computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions can execute the house information recommendation method in any method embodiment. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard disk (Hard disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope defined by the appended claims.
Claims (12)
1. A house information recommendation method is characterized by comprising the following steps:
acquiring price preference information of a client;
acquiring the working position information of a client;
acquiring business circle preference information of a client;
and recommending house information according to the price preference information, the working position information and the business district preference information.
2. The method of claim 1, wherein obtaining price preference information for a customer comprises:
acquiring first price information of a client for renting a house historically;
acquiring second price information of historical clicks and/or searches and/or houses collected by the client;
and calculating the price preference information according to the first price information and/or the second price information.
3. The method of claim 1, wherein obtaining the work location information of the customer comprises:
acquiring daytime historical positioning information of a client;
and calculating the working position information according to the daytime historical positioning information of the client.
4. The method of claim 1, wherein obtaining business turn preference information for a customer comprises:
obtaining the position information of a historical rented house of a client;
acquiring business circle information of historical search and/or collection and/or click of a client;
and calculating the preference information of the business district according to the position information of the house rented by the customer history and/or the business district information.
5. The method of any of claims 1 to 4, wherein recommending premise information based on the price preference information, the work location information, and the business turn preference information comprises:
determining first range house information according to the price preference information;
determining house information in a second range according to the working position information; the position of the second range of the house information is within a first distance range from the working position information;
determining house information in a third range according to the business district preference information; wherein the location of the third range of premise information is within a second distance range from the location of the business district preference information;
and recommending house information according to the house information in the first range, the house information in the second range and the house information in the third range.
6. A house information recommending apparatus, characterized by comprising:
the first acquisition module is used for acquiring price preference information of a client;
the second acquisition module is used for acquiring the working position information of the client;
the third acquisition module is used for acquiring business district preference information of the client;
and the recommending module is used for recommending the house information according to the price preference information, the working position information and the business district preference information.
7. The house information recommending apparatus according to claim 6, wherein said first obtaining module comprises:
the system comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring first price information of a client for renting a house in history;
the second obtaining unit is used for obtaining second price information of historical clicking and/or searching and/or house collection of the client;
and the third acquisition unit is used for calculating the price preference information according to the first price information and/or the second price information.
8. The house information recommending apparatus according to claim 6, wherein said second obtaining module comprises:
the fourth acquisition unit is used for acquiring the daytime historical positioning information of the client;
and the fifth acquisition unit is used for calculating the working position information according to the daytime historical positioning information of the client.
9. The house information recommending apparatus according to claim 6, wherein said third obtaining unit comprises:
the sixth acquisition unit is used for acquiring the position information of the historic rented house of the client;
the seventh acquisition unit is used for acquiring business circle information of historical search and/or collection and/or click of the client;
and the eighth acquisition unit is used for calculating the preference information of the business district according to the position information of the rented house in the customer history and/or the business district information.
10. The premise information recommendation device according to any one of claims 6 to 9, wherein the recommendation module comprises:
a first determination unit, configured to determine first range house information according to the price preference information;
the second determining unit is used for determining house information in a second range according to the working position information; the position of the second range of the house information is within a first distance range from the working position information;
the third determining unit is used for determining house information in a third range according to the business district preference information; wherein the location of the third range of premise information is within a second distance range from the location of the business district preference information;
and the recommending unit is used for recommending the house information according to the house information in the first range, the house information in the second range and the house information in the third range.
11. An electronic device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the premise information recommendation method of any of claims 1-5.
12. A computer-readable storage medium having stored thereon computer instructions, characterized in that the instructions, when executed by a processor, implement the house information recommendation method of any of the preceding claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911227380.1A CN111080407A (en) | 2019-12-04 | 2019-12-04 | House information recommendation method and device, electronic equipment and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911227380.1A CN111080407A (en) | 2019-12-04 | 2019-12-04 | House information recommendation method and device, electronic equipment and readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111080407A true CN111080407A (en) | 2020-04-28 |
Family
ID=70312761
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911227380.1A Pending CN111080407A (en) | 2019-12-04 | 2019-12-04 | House information recommendation method and device, electronic equipment and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111080407A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111815394A (en) * | 2020-05-20 | 2020-10-23 | 北京嘀嘀无限科技发展有限公司 | Commodity scheme recommendation method for taxi hiring of online taxi appointment, electronic equipment and storage medium |
| CN112512030A (en) * | 2020-12-02 | 2021-03-16 | 上海哔哩哔哩科技有限公司 | Target object information determination method and device |
| CN113190702A (en) * | 2021-05-08 | 2021-07-30 | 北京百度网讯科技有限公司 | Method and apparatus for generating information |
| CN113554532A (en) * | 2021-06-16 | 2021-10-26 | 北京房江湖科技有限公司 | Broker list page sorting method, storage medium, and program product |
| CN115115479A (en) * | 2022-05-30 | 2022-09-27 | 北京五八信息技术有限公司 | Method and device for acquiring house lighting information, electronic equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108256024A (en) * | 2018-01-10 | 2018-07-06 | 链家网（北京）科技有限公司 | A kind of source of houses recommends method |
| CN108985876A (en) * | 2018-06-11 | 2018-12-11 | 平安科技（深圳）有限公司 | Information of real estate acquisition methods, device and storage medium, server |
| CN109345319A (en) * | 2018-10-31 | 2019-02-15 | 深圳市元征科技股份有限公司 | A kind of house intelligent recommendation method, apparatus, equipment and storage medium |
| CN109377329A (en) * | 2018-12-25 | 2019-02-22 | 北京时光荏苒科技有限公司 | A kind of source of houses recommended method, device, storage medium and electronic equipment |
| CN109658192A (en) * | 2018-12-20 | 2019-04-19 | 重庆锐云科技有限公司 | A kind of source of houses recommended method and server |
| CN109902224A (en) * | 2019-01-17 | 2019-06-18 | 平安城市建设科技(深圳)有限公司 | Source of houses recommended method, device, equipment and medium based on user behavior analysis |
| CN109902713A (en) * | 2019-01-17 | 2019-06-18 | 平安城市建设科技(深圳)有限公司 | Building recommended method, equipment, storage medium and device based on data analysis |
-
2019
- 2019-12-04 CN CN201911227380.1A patent/CN111080407A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108256024A (en) * | 2018-01-10 | 2018-07-06 | 链家网（北京）科技有限公司 | A kind of source of houses recommends method |
| CN108985876A (en) * | 2018-06-11 | 2018-12-11 | 平安科技（深圳）有限公司 | Information of real estate acquisition methods, device and storage medium, server |
| CN109345319A (en) * | 2018-10-31 | 2019-02-15 | 深圳市元征科技股份有限公司 | A kind of house intelligent recommendation method, apparatus, equipment and storage medium |
| CN109658192A (en) * | 2018-12-20 | 2019-04-19 | 重庆锐云科技有限公司 | A kind of source of houses recommended method and server |
| CN109377329A (en) * | 2018-12-25 | 2019-02-22 | 北京时光荏苒科技有限公司 | A kind of source of houses recommended method, device, storage medium and electronic equipment |
| CN109902224A (en) * | 2019-01-17 | 2019-06-18 | 平安城市建设科技(深圳)有限公司 | Source of houses recommended method, device, equipment and medium based on user behavior analysis |
| CN109902713A (en) * | 2019-01-17 | 2019-06-18 | 平安城市建设科技(深圳)有限公司 | Building recommended method, equipment, storage medium and device based on data analysis |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111815394A (en) * | 2020-05-20 | 2020-10-23 | 北京嘀嘀无限科技发展有限公司 | Commodity scheme recommendation method for taxi hiring of online taxi appointment, electronic equipment and storage medium |
| CN112512030A (en) * | 2020-12-02 | 2021-03-16 | 上海哔哩哔哩科技有限公司 | Target object information determination method and device |
| CN113190702A (en) * | 2021-05-08 | 2021-07-30 | 北京百度网讯科技有限公司 | Method and apparatus for generating information |
| CN113190702B (en) * | 2021-05-08 | 2023-07-25 | 北京百度网讯科技有限公司 | Method and device for generating information |
| CN113554532A (en) * | 2021-06-16 | 2021-10-26 | 北京房江湖科技有限公司 | Broker list page sorting method, storage medium, and program product |
| CN115115479A (en) * | 2022-05-30 | 2022-09-27 | 北京五八信息技术有限公司 | Method and device for acquiring house lighting information, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111080407A (en) | House information recommendation method and device, electronic equipment and readable storage medium | |
| CN107730313B (en) | Shop recommendation method and device based on recommendation reason | |
| CN104731917B (en) | A kind of recommendation method and device | |
| US20190236728A1 (en) | Method and apparatus for providing information | |
| CN111523968B (en) | Method and equipment for spelling bill | |
| CN103914536A (en) | Interest point recommending method and system for electronic maps | |
| PH12014501098B1 (en) | Method and server for searching for nearby user in social networking services | |
| CN111651685A (en) | Interest point obtaining method and device, electronic equipment and storage medium | |
| CN102231152B (en) | Searching method for precisely inquiring based on IP (Internet Protocol) address of mobile terminal | |
| JP6756744B2 (en) | Location information provision method and equipment | |
| CN106408347A (en) | Advertisement recommendation method, advertisement server and terminal device | |
| CN105224545A (en) | A kind of position recommend method and device | |
| CN110955838A (en) | House resource recommendation processing method and device, terminal and computer readable storage medium | |
| CN111259272B (en) | Search result ordering method and device | |
| CN110427574B (en) | Route similarity determination method, device, equipment and medium | |
| CN112749863A (en) | Keyword price adjusting method and device and electronic equipment | |
| CN108874805B (en) | Data processing method and device | |
| CN109003148B (en) | Advertisement pushing method, advertisement pushing device, server and readable storage medium | |
| CN110930101A (en) | Method, device, electronic equipment and readable medium for determining delivery time of order | |
| CN110555151A (en) | Search term determination method and device, electronic equipment and storage medium | |
| CN106651408B (en) | Data analysis method and device | |
| CN110175295B (en) | Advertisement space recommendation method, electronic device and computer readable storage medium | |
| US20170154373A1 (en) | System and method for price comparison | |
| CN111125556A (en) | Recommendation sorting method and system, electronic device and readable storage medium | |
| CN108256957A (en) | Vehicle source search result based on user's history behavior shows method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20200428 |