CN111639988A - Broker recommendation method, device, electronic equipment and storage medium - Google Patents

Broker recommendation method, device, electronic equipment and storage medium Download PDF

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CN111639988A
CN111639988A CN202010440128.5A CN202010440128A CN111639988A CN 111639988 A CN111639988 A CN 111639988A CN 202010440128 A CN202010440128 A CN 202010440128A CN 111639988 A CN111639988 A CN 111639988A
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CN111639988B (en
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陈明慧
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Beike Technology Co Ltd
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Abstract

The application provides a broker recommendation method, a broker recommendation device, an electronic device and a storage medium, wherein the method comprises the following steps: acquiring behavior information and attribute information of a user browsing a house source; acquiring property preference information of the house source of the user based on the behavior information and the property information of the house source browsed by the user; acquiring attribute information of house resources viewed by a broker; evaluating the viewing capability of the broker for the user based on the attribute information of the user viewed house feeds, the house feed attribute preference information of the user, and the attribute information of the house feeds viewed by the broker; recommending the broker with the largest viewing capacity value for the user. The method can improve the accuracy of recommending the brokers and the user experience.

Description

Broker recommendation method, device, electronic equipment and storage medium
Technical Field
The invention relates to the technical field of information processing, in particular to a broker recommendation method, a broker recommendation device, electronic equipment and a storage medium.
Background
After the user sees a satisfactory house source on the house finding APP, the user will usually contact the recommended house broker to take a reservation to see the house source. In a real house source scene, the following phenomena generally exist:
after the user is not satisfied with the house resources with the appointment, the user hopes that the broker can watch other house resources with the appointment;
the user can give up continuing to watch the house source under the situation of being carried with the house source for a plurality of times but not satisfying;
even if the user is in the case of an origin with a mood instrument, the user still hopes that the broker can make a decision after watching a plurality of origins;
under the condition, the accuracy rate of broker recommendation needs to be improved, and the broker recommended for the user is guaranteed to have a house source and be capable of watching the desired house source for the user, so that the watching rate is improved.
However, the current broker recommendation scheme is only to recommend brokers near the house resources for the user, and does not really combine and consider the viewing ability of the brokers and the house searching requirements of the user, so that the similarity between the house resources viewed by the brokers and the house resources expected by the user is low, the user is difficult to satisfy, sometimes, even the phenomenon that the user has to select other brokers to view is caused, the inaccurate scheme of the broker recommendation prolongs the viewing period, further improves the viewing cost, and the user experience is poor.
Disclosure of Invention
In view of this, the present application provides a broker recommending method, an apparatus, an electronic device, and a storage medium, which can improve accuracy of recommending a broker and user experience.
In order to solve the technical problem, the technical scheme of the application is realized as follows:
in one embodiment, there is provided a broker recommendation method, the method comprising:
acquiring behavior information and attribute information of a user browsing a house source;
acquiring property preference information of the house source of the user based on the behavior information and the property information of the house source browsed by the user;
acquiring attribute information of house resources viewed by a broker;
evaluating the viewing capability of the broker for the user based on the attribute information of the user viewed house feeds, the house feed attribute preference information of the user, and the attribute information of the house feeds viewed by the broker;
recommending the broker with the largest viewing capacity value for the user.
Wherein,
the behavior information of the user browsing the house resources comprises any combination of the following information:
searching information, forwarding information, saving information, clicking information and page staying time information;
the attribute information of the house source browsed by the user comprises any combination of the following information:
region information, price information, area information, house type information, orientation information, floor information, building age information, decoration information, elevator information, heating information, right information, type information, house source characteristic information.
Wherein said evaluating the ability of the broker to see for the user based on the attribute information of the user's viewed premises, the premises attribute preference information of the user, and the attribute information of the premises that the broker has taken a view comprises:
evaluating the viewing capability of the broker for the user based on the attribute information of the house source browsed by the user, the house source attribute preference information of the user and the attribute information of the house source viewed by the broker according to the following formula:
Figure BDA0002503776630000021
wherein v istRepresenting a visibility value for broker t; m is the number of attribute information, djIndicates the user's preference value for the jth property, dist (a)j，uj)2Representing the similarity between the property information of the house viewed by the user and the house viewed by the broker, ajValue vector u of j-th attribute information browsed by userjA value vector representing the jth attribute information viewed by the broker.
The acquiring of the property preference information of the house source of the user based on the behavior information and the property information of the house source browsed by the user comprises the following steps:
acquiring the property preference information of the house source of the user according to the following formula based on the behavior information and the property information of the house source browsed by the user:
Figure BDA0002503776630000031
wherein d isjRepresenting the preference value of the user for the jth house source attribute; m is the number of the properties of the house source, n is the number of the user behaviors, xijRepresenting the browsing times of the ith behavior of the user to the jth house source attribute,
Figure BDA0002503776630000032
the average of the number of times that n user rows represent the user browses the jth source attribute,
Figure BDA0002503776630000033
is represented as follows:
Figure BDA0002503776630000034
where | X | is the modulus of matrix X.
Wherein the method further comprises:
when a request of recommending brokers sent by the user through a terminal is received, recommending brokers for the user through the terminal;
or, periodically recommending brokers for the user.
In another embodiment, an embodiment of the present application is further provided to provide a broker recommendation apparatus, including: the system comprises a first acquisition unit, a second acquisition unit, a third acquisition unit, an evaluation unit and a recommendation unit;
the first acquisition unit is used for acquiring behavior information and attribute information of a user browsing a house source;
the second obtaining unit is used for obtaining the property preference information of the house source of the user based on the behavior information and the property information of the house source browsed by the user, which are obtained by the first obtaining unit;
the third obtaining unit is used for obtaining attribute information of the house resources seen by the broker;
the evaluation unit is configured to evaluate, based on the attribute information of the house source browsed by the user and acquired by the first acquisition unit, the house source attribute preference information of the user and acquired by the second acquisition unit, and the attribute information of the house source viewed by the broker and acquired by the third acquisition unit, a viewing capability of the broker for the user;
and the recommending unit is used for recommending the broker with the largest watching capacity value evaluated by the evaluating unit for the user.
Wherein,
the behavior information of the user browsing the house resources comprises any combination of the following information:
searching information, forwarding information, saving information, clicking information and page staying time information;
the attribute information of the house source browsed by the user comprises any combination of the following information:
region information, price information, area information, house type information, orientation information, floor information, building age information, decoration information, elevator information, heating information, right information, type information, house source characteristic information.
Wherein,
the evaluation unit is specifically configured to evaluate, based on the attribute information of the house resources browsed by the user, the house resource attribute preference information of the user, and the attribute information of the house resources viewed by the broker, the viewing capability of the broker for the user according to the following formula:
Figure BDA0002503776630000041
wherein v istRepresenting a visibility value for broker t; m is the number of attribute information, djIndicates the user's preference value for the jth property, dist (a)j，uj)2Representing the similarity between the property information of the house viewed by the user and the house viewed by the broker, ajValue vector u of j-th attribute information browsed by userjRepresenting broker beltsAnd the value vector of the j-th viewed attribute information.
The second obtaining unit is specifically configured to obtain, based on the behavior information and attribute information of the user browsing the house source, the attribute preference information of the house source of the user according to the following formula:
Figure BDA0002503776630000042
wherein d isjRepresenting the preference value of the user for the jth house source attribute; m is the number of the properties of the house source, n is the number of the user behaviors, xijRepresenting the browsing times of the ith behavior of the user to the jth house source attribute,
Figure BDA0002503776630000043
the average of the number of times that n user rows represent the user browses the jth source attribute,
Figure BDA0002503776630000044
is represented as follows:
Figure BDA0002503776630000045
where | X | is the modulus of matrix X.
Wherein the apparatus further comprises: a receiving unit;
the receiving unit is used for receiving a request of recommending brokers, which is sent by a user through a terminal;
the recommending unit is further used for recommending brokers for the user through the terminal when the receiving unit receives a request of recommending brokers sent by the user through the terminal; or, periodically recommending brokers for the user.
In another embodiment, an electronic device is provided that includes a memory, a processor, and a computer program stored on the memory and executable on the processor that, when executed, performs the steps of the broker recommendation method.
In another embodiment, a computer readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, performs the steps of the broker recommendation method.
As can be seen from the above technical solutions, in the above embodiments, the viewing capability of the broker is evaluated for the user by integrating the behavior information and the attribute information of the house source browsed by the user and the attribute information of the house source viewed by the broker, so as to recommend the broker with the largest viewing capability value for the user. According to the scheme, the accuracy of the broker recommendation is improved, the watching cost and the watching period are reduced, and the user experience is improved.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
FIG. 1 is a schematic diagram of a broker recommendation process in an embodiment of the application;
FIG. 2 is a schematic diagram of an apparatus for implementing the above technique in an embodiment of the present application;
fig. 3 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. 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 application.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements explicitly listed, but may include other steps or elements not explicitly listed or inherent to such process, method, article, or apparatus.
The technical solution of the present invention will be described in detail with specific examples. Several of the following embodiments may be combined with each other and some details of the same or similar concepts or processes may not be repeated in some embodiments.
The embodiment of the application provides a broker recommendation method, which is applied to a broker recommendation device, and can be referred to as a recommendation device for short.
The recommendation device can be applied to the APP server for watching the house and can also be deployed independently, and the embodiment of the application does not limit the APP server.
The broker recommendation process is described in detail below in conjunction with the figures.
Referring to fig. 1, fig. 1 is a schematic diagram of a broker recommendation process in an embodiment of the present application. The method comprises the following specific steps:
step 101, acquiring behavior information and attribute information of a user browsing a house source.
According to the method and the device, the current positioning information of the user can be acquired to acquire the information of the urban area where the user is located currently, or the information of the destination set by the user is acquired to determine that the user is going to search the urban area information of the house source, then the house source information in the urban area is automatically acquired from the system database, and meanwhile the behavior information of the user is automatically acquired.
The behavior information of the user browsing the house resources may include any combination of the following information, but is not limited to the following behavior information:
search information, forward information, save information, click information, and page dwell time information.
Searching information, recording the times of searching attribute information, wherein the searched attribute information is house type information, area information and price information;
forwarding information, recording attribute information of all attributes corresponding to the forwarded house source;
storing information, recording attribute information of all attributes corresponding to the stored house source;
click information, recording attribute information of the clicked house source, such as area information, house type information and price information;
and page stay time information, and recording the duration of browsing attribute information.
The attribute information of the user browsing the house source may include any combination of the following information, but is not limited to the attribute information given below:
region information, price information, area information, house type information, orientation information, floor information, building age information, decoration information, elevator information, heating information, right information, type information, house source characteristic information.
The meaning of each house source attribute, and the specific quantification mode are given below:
such as the hai lake area of Beijing, the sunny area, etc.; in specific implementation, a type value is set for each region in advance to quantify region information, such as setting the hai lake region to be 2, setting the sun ward region to be 5, and the like;
the price information refers to the expected house selling price marked by the house source, such as 500 (ten thousand) and the like;
the area information refers to the actual area of the house source, such as 100 (square meters);
the house type information refers to actual house types of house sources, such as one-room-one-hall, two-room-one-hall, three-room-one-hall and the like, and in specific implementation, a type value is set for each house type in advance to quantify the house type information, such as one-room-one-hall setting 1, two-room-one-hall setting 2 and three-room-one-hall setting 3.
The orientation information refers to the orientation of the house source, such as the south direction, the southeast direction, the northwest direction, and the like, and in a specific implementation, an orientation value is set for each orientation in advance to quantify the orientation information, such as setting the south direction to 1, setting the northwest direction to 2, and the like.
The floor information refers to the floor where the house source is located, namely the specific number of floors;
the building age information refers to the construction period displayed by the house book of the house source, and the construction period of the house source can be converted from the current time, such as 1998 or 22 years.
The decoration information refers to decoration conditions of a house source, such as finish decoration, simplified decoration, blanks and the like, and during specific implementation, a device value can be set to quantify the decoration information, such as 11 for finish decoration, 12 for simplified decoration, 13 for blanks and the like;
the elevator information indicates whether an elevator exists in a room source, and specific numerical values are set for quantifying the elevator information according to the existence of the elevator, such as 1 and 2, and can also be 1 and 0;
the heating information indicates whether the room source has heating or not, and can be further subdivided, whether the heating is collective heating or self-heating, and the like; different values are set for different conditions, such as no heating is 1, collective heating is 2, self heating is 3, and the like;
the ownership information indicates whether the ownership of the house source exists or not, and whether the ownership information quantifies the ownership of the house source or not is determined by respectively setting different values;
the type information refers to ownership of the house source, such as public houses, commodity houses, business and residential dual-purpose houses, and different values are set respectively for quantification;
the house source characteristic information refers to information with characteristics of house sources, such as near subways, study rooms, VR house watching and the like, and different values are set respectively for quantification.
The attribute information of the house source browsed by the user can be represented by using a matrix A, rows in the matrix A represent a set of house sources, and each column corresponds to one attribute information of the house source.
The behavior information of the house source browsed by the user can be represented by using a matrix X, each row of the matrix X represents a behavior, each column corresponds to a house source attribute, and each value of the matrix X represents the number of times that the house source browsed by the user has the house source attribute information.
Taking the number m of the house source attributes as 13 and the number n of the user behaviors as 5 as an example:
e.g. row 1, column 4X of the matrix X14The number of times of searching house type by user, the 3 rd row and the 9 th column X of the matrix X39Indicating the number of times the user has saved the attribute information of having an elevator in the house.
That is to say, whether the corresponding value is the browsed house source has the attribute information or not, and what is the specific content of the value corresponding to the attribute information does not concern, for example, the attribute information of the area information, as long as there is an item of the area attribute, and what is the area does not concern.
And 102, acquiring the property preference information of the house source of the user based on the behavior information and the property information of the house source browsed by the user.
Acquiring the property preference information of the house source of the user according to the following formula based on the behavior information and the property information of the house source browsed by the user:
Figure BDA0002503776630000081
wherein d isjRepresenting the preference value of the user for the jth house source attribute; m is the number of the properties of the house source, n is the number of the user behaviors, xijRepresenting the browsing times of the ith behavior of the user to the jth house source attribute,
Figure BDA0002503776630000082
the average of the number of times that n user rows represent the user browses the jth source attribute,
Figure BDA0002503776630000083
is represented as follows:
Figure BDA0002503776630000091
where | X | is the modulus of matrix X.
And step 103, acquiring attribute information of the house resources watched by the broker.
In the embodiment of the application, the house resources seen by the broker and the attribute information corresponding to the house resources are stored in the system;
here the attribute information obtained for the broker is matched in name and number with the attribute information obtained for the user.
If the acquired attribute information of the user is the combination of the 13 pieces of attribute information, the attribute information acquired by the broker is also the combination of the 13 pieces of attribute information;
if the acquired attribute information of the user is area information, price information, area information, or house type information, the attribute information acquired for the broker is also area information, price information, area information, or house type information.
During specific implementation, the attribute information of the house resources which are watched can be recorded through broker input information, which broker takes to watch which set of house resources can be also marked in the APP, and when the attribute information of the house resources which are watched by the broker is required to be obtained, the house resources of the broker are obtained and marked, and then the corresponding house resource information is obtained.
The attribute information of the house resources taken by the broker can be represented by a matrix U, wherein each row represents one house resource and each column corresponds to the attribute information of one house resource.
And 104, evaluating the watching capacity of the broker for the user based on the attribute information of the house source browsed by the user, the house source attribute preference information of the user and the attribute information of the house source watched by the broker.
And obtaining the viewing capability of the corresponding broker by determining the similarity between the attribute information of the browsed house sources and the attribute information of the house sources viewed by the broker and performing weighted summation on the preference information of the corresponding attribute information by the user.
Evaluating the viewing capability of the broker for the user based on the attribute information of the house source browsed by the user, the house source attribute preference information of the user and the attribute information of the house source viewed by the broker according to the following formula:
Figure BDA0002503776630000101
wherein v istRepresenting a visibility value for broker t; m is the number of attribute information, djIndicates the user's preference value for the jth property, dist (a)j，uj)2Representing the similarity between the property information of the house viewed by the user and the house viewed by the broker, ajValue vector u of j-th attribute information browsed by userjA value vector representing the jth attribute information viewed by the broker.
To ajAnd ujWhen the similarity is calculated, the similarity calculation method used is not limited, and may be, for example, an euclidean distance or a cosine similarity calculation method.
And 105, recommending the broker with the largest watching capacity value for the user.
In specific implementation, the broker with the largest viewing ability value can be recommended for the user, whether the broker with the largest viewing ability value is convenient to serve the user in actual conditions or not can be considered, if the broker with the largest viewing ability value is inconvenient to serve the user, the broker with the largest viewing ability value can be selected again to be recommended, and the rest can be done in sequence, so that the most appropriate broker is recommended for the user.
In the embodiment of the present application, the broker recommended to the user may have two cases to trigger the recommendation of the broker, or may be a combination of the following two cases:
the first method comprises the following steps: when a request of recommending brokers sent by a user through a terminal is received, acquiring and recommending the broker with the largest watching capacity value aiming at the user;
second, brokers are periodically recommended to the user.
The recommendation mode can be short message recommendation, mail recommendation, WeChat recommendation, house-watching APP recommendation and the like, or combined recommendation, and the specific implementation mode of the recommendation is not limited in the embodiment of the application.
In the embodiment of the application, a broker with the maximum viewing ability value may be periodically determined for a specified user, and may be directly recommended when recommendation is needed, or when a broker needs to be recommended, relevant attribute information of the user and the broker may be obtained, the viewing ability value of the broker may be evaluated, and the broker with the maximum viewing ability value may be recommended to the user, which is not limited.
In the embodiment of the application, the viewing capacity of the broker is evaluated for the user by integrating the behavior information and the attribute information of the house source browsed by the user and the attribute information of the house source viewed by the broker, and then the broker with the largest viewing capacity value is recommended for the user. According to the scheme, the accuracy of the broker recommendation is improved, the watching cost and the watching period are reduced, and the user experience is improved.
Based on the same inventive concept, the embodiment of the application also provides a broker recommending device. Referring to fig. 1, fig. 2, and fig. 2 are schematic structural diagrams of an apparatus applying the above-described technology in an embodiment of the present application. The device comprises: a first acquisition unit 201, a second acquisition unit 202, a third acquisition unit 203, an evaluation unit 204, and a recommendation unit 205;
a first obtaining unit 201, configured to obtain behavior information and attribute information of a user browsing a house source;
a second obtaining unit 202, configured to obtain property preference information of the house source of the user based on the behavior information and the property information of the house source browsed by the user, which are obtained by the first obtaining unit 201;
a third obtaining unit 203, configured to obtain attribute information of the house resources viewed by the broker;
an evaluating unit 204, configured to evaluate, based on the attribute information of the house source browsed by the user and acquired by the first acquiring unit 201, the house source attribute preference information of the user and acquired by the second acquiring unit 202, and the attribute information of the house source that the broker has taken a look at, acquired by the third acquiring unit 203, the ability of the broker to take a look at for the user;
and the recommending unit 205 is configured to recommend, to the user, the broker with the largest watching capacity value evaluated by the evaluating unit 204.
Preferably, the first and second electrodes are formed of a metal,
the behavior information of the user browsing the house resources comprises any combination of the following information:
searching information, forwarding information, saving information, clicking information and page staying time information;
the attribute information of the house source browsed by the user comprises any combination of the following information:
region information, price information, area information, house type information, orientation information, floor information, building age information, decoration information, elevator information, heating information, right information, type information, house source characteristic information.
Preferably, the first and second electrodes are formed of a metal,
the evaluation unit 204 is specifically configured to evaluate, based on the attribute information of the house source browsed by the user, the house source attribute preference information of the user, and the attribute information of the house source watched by the broker, a watching capacity of the broker for the user according to the following formula:
Figure BDA0002503776630000111
wherein v istRepresenting a visibility value for broker t; m is the number of attribute information, djIndicates the user's preference value for the jth property, dist (a)j，uj)2Representing the similarity between the property information of the house viewed by the user and the house viewed by the broker, ajValue vector u of j-th attribute information browsed by userjA value vector representing the jth attribute information viewed by the broker.
Preferably, the second obtaining unit 202 is specifically configured to obtain, based on the behavior information and attribute information of the user browsing the house source, the attribute preference information of the house source of the user according to the following formula:
Figure BDA0002503776630000121
wherein d isjRepresenting the preference value of the user for the jth house source attribute; m is the number of the properties of the house source, n is the number of the user behaviors, xijRepresenting the browsing times of the ith behavior of the user to the jth house source attribute,
Figure BDA0002503776630000122
the average of the number of times that n user rows represent the user browses the jth source attribute,
Figure BDA0002503776630000123
is represented as follows:
Figure BDA0002503776630000124
where | X | is the modulus of matrix X.
Preferably, the apparatus further comprises: a receiving unit 206;
a receiving unit 206, configured to receive a request of recommending a broker, where the request is sent by a user through a terminal;
the recommending unit 205 is further configured to recommend brokers for the user through the terminal when the receiving unit 206 receives a request of recommending brokers sent by the user through the terminal; or, periodically recommending brokers for the user.
The units of the above embodiments may be integrated into one body, or may be separately deployed; may be combined into one unit or further divided into a plurality of sub-units.
In another embodiment, there is also provided an electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the broker recommendation method when executing the program.
In another embodiment, a computer-readable storage medium is also provided having stored thereon computer instructions that, when executed by a processor, may implement the steps in the broker recommendation method.
Fig. 3 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention. As shown in fig. 3, the electronic device may include: a Processor (Processor)310, a communication Interface (Communications Interface)320, a Memory (Memory)330 and a communication bus 340, wherein the Processor 310, the communication Interface 320 and the Memory 330 communicate with each other via the communication bus 340. The processor 310 may call logic instructions in the memory 330 to perform the following method:
acquiring behavior information and attribute information of a user browsing a house source;
acquiring property preference information of the house source of the user based on the behavior information and the property information of the house source browsed by the user;
acquiring attribute information of house resources viewed by a broker;
evaluating the viewing capability of the broker for the user based on the attribute information of the user viewed house feeds, the house feed attribute preference information of the user, and the attribute information of the house feeds viewed by the broker;
recommending the broker with the largest viewing capacity value for the user.
In addition, the logic instructions in the memory 330 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (10)

1. A broker recommendation method, the method comprising:
acquiring behavior information and attribute information of a user browsing a house source;
acquiring property preference information of the house source of the user based on the behavior information and the property information of the house source browsed by the user;
acquiring attribute information of house resources viewed by a broker;
evaluating the viewing capability of the broker for the user based on the attribute information of the user viewed house feeds, the house feed attribute preference information of the user, and the attribute information of the house feeds viewed by the broker;
recommending the broker with the largest viewing capacity value for the user.
2. The method of claim 1,
the behavior information of the user browsing the house resources comprises any combination of the following information:
searching information, forwarding information, saving information, clicking information and page staying time information;
the attribute information of the house source browsed by the user comprises any combination of the following information:
region information, price information, area information, house type information, orientation information, floor information, building age information, decoration information, elevator information, heating information, right information, type information, house source characteristic information.
3. The method of claim 1, wherein evaluating the broker's ability to see for the user based on the user's browsing of property information of the premises, the user's premises property preference information, and the broker's viewed premises property information comprises:
evaluating the viewing capability of the broker for the user based on the attribute information of the house source browsed by the user, the house source attribute preference information of the user and the attribute information of the house source viewed by the broker according to the following formula:
Figure FDA0002503776620000011
wherein v istRepresenting a visibility value for broker t; m is the number of attribute information, djIndicates the user's preference value for the jth property, dist (a)j，uj)2Representing the similarity between the property information of the house viewed by the user and the house viewed by the broker, ajValue vector u of j-th attribute information browsed by userjA value vector representing the jth attribute information viewed by the broker.
4. The method according to any one of claims 1 to 3, wherein the obtaining of the property preference information of the house source of the user based on the behavior information and the property information of the house source browsed by the user comprises:
acquiring the property preference information of the house source of the user according to the following formula based on the behavior information and the property information of the house source browsed by the user:
Figure FDA0002503776620000021
wherein d isjRepresenting the preference value of the user for the jth house source attribute; m is the number of the properties of the house source, n is the number of the user behaviors, xijRepresenting the browsing times of the ith behavior of the user to the jth house source attribute,
Figure FDA0002503776620000022
the average of the number of times that n user rows represent the user browses the jth source attribute,
Figure FDA0002503776620000023
is represented as follows:
Figure FDA0002503776620000024
where | X | is the modulus of matrix X.
5. A broker recommendation apparatus, the apparatus comprising: the system comprises a first acquisition unit, a second acquisition unit, a third acquisition unit, an evaluation unit and a recommendation unit;
the first acquisition unit is used for acquiring behavior information and attribute information of a user browsing a house source;
the second obtaining unit is used for obtaining the property preference information of the house source of the user based on the behavior information and the property information of the house source browsed by the user, which are obtained by the first obtaining unit;
the third obtaining unit is used for obtaining attribute information of the house resources seen by the broker;
the evaluation unit is configured to evaluate, based on the attribute information of the house source browsed by the user and acquired by the first acquisition unit, the house source attribute preference information of the user and acquired by the second acquisition unit, and the attribute information of the house source viewed by the broker and acquired by the third acquisition unit, a viewing capability of the broker for the user;
and the recommending unit is used for recommending the broker with the largest watching capacity value evaluated by the evaluating unit for the user.
6. The apparatus of claim 5,
the behavior information of the user browsing the house resources comprises any combination of the following information:
searching information, forwarding information, saving information, clicking information and page staying time information;
the attribute information of the house source browsed by the user comprises any combination of the following information:
region information, price information, area information, house type information, orientation information, floor information, building age information, decoration information, elevator information, heating information, right information, type information, house source characteristic information.
7. The apparatus of claim 5,
the evaluation unit is specifically configured to evaluate, based on the attribute information of the house resources browsed by the user, the house resource attribute preference information of the user, and the attribute information of the house resources viewed by the broker, the viewing capability of the broker for the user according to the following formula:
Figure FDA0002503776620000031
wherein v istRepresenting a visibility value for broker t; m is the number of attribute information, djIndicates the user's preference value for the jth property, dist (a)j，uj)2Representing the similarity between the property information of the house viewed by the user and the house viewed by the broker, ajValue vector u of j-th attribute information browsed by userjA value vector representing the jth attribute information viewed by the broker.
8. The apparatus according to any one of claims 5 to 7,
the second obtaining unit is specifically configured to obtain the behavior information and the attribute information according to the information such as the number of the users browsing the house resourcesThe following formula obtains the property preference information of the house source of the user:
Figure FDA0002503776620000032
wherein d isjRepresenting the preference value of the user for the jth house source attribute; m is the number of the properties of the house source, n is the number of the user behaviors, xijRepresenting the browsing times of the ith behavior of the user to the jth house source attribute,
Figure FDA0002503776620000033
the average of the number of times that n user rows represent the user browses the jth source attribute,
Figure FDA0002503776620000034
is represented as follows:
Figure FDA0002503776620000035
where | X | is the modulus of matrix X.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-4 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out the method of any one of claims 1 to 4.
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112233265A (en) * 2020-09-29 2021-01-15 深圳思为科技有限公司 Electronic sign-in method and related device
CN112330387A (en) * 2020-09-29 2021-02-05 重庆锐云科技有限公司 Virtual broker applied to house-watching software
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
CN112734461A (en) * 2020-12-30 2021-04-30 贝壳技术有限公司 Processing method and device of prompter
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
CN113763029A (en) * 2021-07-20 2021-12-07 北京房江湖科技有限公司 Client information recommendation method and device

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106339818A (en) * 2016-08-30 2017-01-18 李壮志 Real estate intermediary service system and client and agent matching method
CN107784066A (en) * 2017-08-25 2018-03-09 上海壹账通金融科技有限公司 Information recommendation method, device, server and storage medium
CN108053105A (en) * 2017-12-06 2018-05-18 成都初唐网络科技股份有限公司 Traveller's distribution method and device
CN108288179A (en) * 2018-01-25 2018-07-17 链家网（北京）科技有限公司 A kind of user preference source of houses computational methods and system
CN108376354A (en) * 2018-01-10 2018-08-07 链家网（北京）科技有限公司 A kind of recommendation method and device based on network graph structure
CN108510321A (en) * 2018-03-23 2018-09-07 北京焦点新干线信息技术有限公司 A kind of construction method and device of house property user portrait
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
CN110955838A (en) * 2019-12-04 2020-04-03 青梧桐有限责任公司 House resource recommendation processing method and device, terminal and computer readable storage medium
CN110990542A (en) * 2019-10-11 2020-04-10 北京华跃博弈科技有限公司 Client requirement matching system of real estate agency service platform
CN110992124A (en) * 2019-10-31 2020-04-10 贝壳技术有限公司 House resource recommendation method and system
CN111091415A (en) * 2019-12-02 2020-05-01 贝壳技术有限公司 Method and system for recommending broker

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106339818A (en) * 2016-08-30 2017-01-18 李壮志 Real estate intermediary service system and client and agent matching method
CN107784066A (en) * 2017-08-25 2018-03-09 上海壹账通金融科技有限公司 Information recommendation method, device, server and storage medium
CN108053105A (en) * 2017-12-06 2018-05-18 成都初唐网络科技股份有限公司 Traveller's distribution method and device
CN108376354A (en) * 2018-01-10 2018-08-07 链家网（北京）科技有限公司 A kind of recommendation method and device based on network graph structure
CN108288179A (en) * 2018-01-25 2018-07-17 链家网（北京）科技有限公司 A kind of user preference source of houses computational methods and system
CN108510321A (en) * 2018-03-23 2018-09-07 北京焦点新干线信息技术有限公司 A kind of construction method and device of house property user portrait
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
CN110990542A (en) * 2019-10-11 2020-04-10 北京华跃博弈科技有限公司 Client requirement matching system of real estate agency service platform
CN110992124A (en) * 2019-10-31 2020-04-10 贝壳技术有限公司 House resource recommendation method and system
CN111091415A (en) * 2019-12-02 2020-05-01 贝壳技术有限公司 Method and system for recommending broker
CN110955838A (en) * 2019-12-04 2020-04-03 青梧桐有限责任公司 House resource recommendation processing method and device, terminal and computer readable storage medium

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112233265A (en) * 2020-09-29 2021-01-15 深圳思为科技有限公司 Electronic sign-in method and related device
CN112330387A (en) * 2020-09-29 2021-02-05 重庆锐云科技有限公司 Virtual broker applied to house-watching software
CN112330387B (en) * 2020-09-29 2023-07-18 重庆锐云科技有限公司 Virtual broker applied to house watching software
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
CN112734461A (en) * 2020-12-30 2021-04-30 贝壳技术有限公司 Processing method and device of prompter
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
CN113763029A (en) * 2021-07-20 2021-12-07 北京房江湖科技有限公司 Client information recommendation method and device

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