CN110990542A - Client requirement matching system of real estate agency service platform - Google Patents

Client requirement matching system of real estate agency service platform Download PDF

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CN110990542A
CN110990542A CN201910964609.3A CN201910964609A CN110990542A CN 110990542 A CN110990542 A CN 110990542A CN 201910964609 A CN201910964609 A CN 201910964609A CN 110990542 A CN110990542 A CN 110990542A
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祝德兆
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Beijing Huayue Game Technology Co Ltd
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Abstract

The invention relates to a client requirement matching system of a real estate agency service platform. The system comprises: a customer premises requirement end; a mediating house providing end; a matching platform; the client house demand end is used for providing a plurality of house demand information and expected purchase prices of corresponding demands to the matching platform; the intermediary house providing end is used for sending house information for renting and selling to the matching platform; the matching platform comprises an area classification module, a demand matching module, a price matching module and an area section house type matching module, and is used for determining house information matched with the demand end of the customer house and sending the house information matched with the demand end of the customer house to the demand end of the customer house. By the system disclosed by the invention, matched house information can be determined based on a plurality of house requirements, so that a user can quickly determine a favorite house source, further house transaction can be quickly facilitated, the time of the user is saved, and the user experience is improved.

Description

Client requirement matching system of real estate agency service platform
Technical Field
The invention relates to the technical field of computers, in particular to a client requirement matching system of a real estate agency service platform.
Background
At present, the second-hand house trading market is rapidly developed, and the trading scale is continuously expanded. Because the second-hand house transaction procedure is relatively complex and the risk is high, the real estate agency service platform is also accepted and used by more and more people, and the real estate agency service platform is also increased.
In the prior art, when a client searches through a webpage or application providing house intermediary service, the house can only be sorted through a single index, so that the user cannot accurately find house information meeting all requirements, and further the user needs to spend a large amount of time for finding a favorite house source, thereby wasting the user time, and even possibly missing the house source matched with the user source, so that the user cannot realize house transaction, and the user experience is influenced.
Disclosure of Invention
The invention provides a customer demand matching system of a house property intermediary service platform, which is used for rapidly promoting house transaction, saving user time and improving user experience.
The invention provides a client requirement matching system of a real estate agency service platform, which comprises: a customer premises requirement end; a mediating house providing end; a matching platform;
the client house demand end is used for providing a plurality of house demand information and expected purchase prices of corresponding demands to the matching platform;
the intermediary house providing end is used for sending house information for renting and selling to the matching platform;
the matching platform comprises: the system comprises an area classification module, a demand matching module, a price matching module and an area section house type matching module, and is used for determining house information matched with a customer house demand end according to a plurality of house demand information provided by the customer house demand end and an expected purchase price of a corresponding demand, and sending the house information matched with the customer house demand end to the customer house demand end.
The invention has the beneficial effects that: the matched house information can be determined based on multiple house requirements, so that a user can quickly determine a favorite house source, house transaction can be quickly facilitated, the user time is saved, and the user experience is improved.
In one embodiment, the requirement matching module comprises: a type judgment module; a matching module; an information push module;
the type judgment module is used for receiving a request of a client house demand end user for logging in an account and judging the type of the user according to the request; sending the judged user type to a matching module; wherein the user type comprises any one of a client and a broker;
the matching module is used for acquiring information of a first preset type corresponding to a client when the user type is the client; generating retrieval conditions of the broker users according to the acquired information of the first preset type; searching a database storing broker information according to the generated retrieval condition of the broker to obtain information of the broker matched with the client; sending the information of the client and the information of the broker matched with the client to the information pushing module;
and the information pushing module is used for sending the information of the broker matched with the client to the client when receiving the information of the client and the information of the broker matched with the client, which are sent by the matching module.
The beneficial effect of this embodiment lies in: the house source information is not directly displayed to the client, but the information of the broker matched with the client information is sent to the client, the experience of the client cannot be reduced due to the fact that the broker is in butt joint with the client, the risk of house source information leakage is reduced due to the fact that the house source information does not need to be directly displayed on a user interface, and the safety of the house source information is protected on the basis that the experience degree of the client is not influenced.
In one embodiment of the present invention,
the type judging module is used for judging whether the user is a client or a broker according to the account type identifier when receiving a request of logging in the account by the user, and sending a judgment result to the matching module;
the account type identification is generated based on a registration type selected when the user registers, and the selectable registration types comprise a client and a broker.
In one embodiment of the present invention,
the matching module is further used for acquiring information of a second preset type corresponding to the broker when the user type is the broker; generating a retrieval condition of the client according to the acquired information of the second preset type; searching a database storing customer information according to the generated retrieval condition of the customer to obtain information of the customer matched with the broker; sending the information of the broker and the information of the clients matched with the broker to the information pushing module;
the information pushing module is further used for sending the information of the client matched with the broker to the broker when receiving the information of the broker and the information of the client matched with the broker sent by the matching module;
the first preset type of information corresponding to the client comprises at least one of the following information:
positioning information, personal information filled in when an account is registered, keyword information submitted in retrieval, screening condition information corresponding to screening operation and historical behavior information;
the second preset type of information corresponding to the broker includes at least one of the following information:
the service area of the broker, the working years of the broker, the number of deals, the contact information, the rating of the customer, the sex and the age.
The beneficial effect of this embodiment lies in: when the information of the broker and the information of the customers matched with the broker, which are sent by the matching module, are received, the information pushing module can send the information of the customers matched with the broker to the broker, so that the broker can actively search the users matched with the broker, and channels of potential customers mined by the broker are expanded.
In one embodiment of the present invention,
the matching module is used for acquiring one or more items of information in positioning information of a user, personal information filled in when an account is registered, keyword information submitted in retrieval, screening condition information corresponding to screening operation and historical behavior information when the user type is a client; and generating a retrieval formula related to the broker information according to the acquired one or more items of information, and retrieving the broker information database according to the retrieval formula to acquire the matched broker information.
In one embodiment of the present invention,
the matching module is used for generating a retrieval keyword according to the information of the first preset type corresponding to the client; when the retrieval keywords are multiple, determining the priorities of the retrieval keywords, and sequencing the retrieval keywords based on the priorities of the retrieval keywords to form a retrieval formula related to broker information, wherein the retrieval keywords with higher priorities are ranked more ahead; and searching the broker information database according to the searching mode.
In one embodiment of the present invention,
the matching module is also used for removing the keyword with the lowest priority in the search formula to form a new search formula when the broker information is not searched after the broker information database is searched according to the search formula; and searching the broker information database according to the new searching mode.
The beneficial effect of this embodiment lies in: when broker information is not searched after the broker information database is retrieved according to the retrieval formula, removing the keyword with the lowest priority in the retrieval formula to form a new retrieval formula; and retrieving the broker information database according to the new retrieval mode, thereby avoiding the situation that the broker information cannot be searched.
In one embodiment of the present invention,
the matching module is used for retrieving the local broker information database according to a retrieval formula when the broker information database is a local database; when the broker information database is a remote database, encrypting the search formula according to a preset encryption algorithm to form an encrypted search formula; and sending a retrieval request to the remote broker information database according to the encrypted retrieval formula, and receiving a retrieval result fed back by the remote broker information database, wherein an encryption algorithm agreed with the local area in advance is stored in the remote broker database.
The beneficial effect of this embodiment lies in: when the broker information database is a remote database, the search formula can be encrypted according to a preset encryption algorithm, so that an encrypted search formula is formed; and the retrieval information is prevented from being stolen.
In one embodiment of the present invention,
the function of encrypting the retrieval formula according to a preset encryption algorithm in the matching module is realized based on the following steps:
acquiring the priority of each keyword; determining an encryption grade corresponding to each keyword according to the priority of each keyword, wherein each encryption grade corresponds to a different encryption algorithm, and the higher the encryption grade is, the higher the decryption difficulty after encryption is; encrypting each keyword according to an encryption algorithm corresponding to each keyword, and combining the encrypted keywords to form an encrypted retrieval formula;
wherein the encryption level is determined based on:
performing analog encryption on a preset encryption object according to each encryption algorithm to form a plurality of encrypted encryption objects; deciphering the plurality of encrypted objects to determine the deciphering difficulty of each encrypted object; and determining the encryption grade corresponding to each encryption algorithm according to different decoding difficulties of the encrypted objects, wherein the higher the decoding difficulty of the encrypted objects is, the higher the encryption grade of the corresponding encryption algorithm is.
The beneficial effect of this embodiment lies in: the encryption grade corresponding to each keyword is determined according to the priority of each keyword, so that the keywords with different priorities correspond to different encryption algorithms, the retrieval formula is encrypted by various different encryption modes, the decryption difficulty of the retrieval formula is increased, and the security of the retrieval formula is further improved.
In one embodiment of the present invention,
the matching module is used for matching the received signal with the reference signal,
determining the relevancy of the broker and each keyword in the search formula; acquiring the priority of each keyword related to the broker, and calculating the correlation between the broker and the retrieval formula according to the correlation between the broker and each keyword in the retrieval formula and the priority of each keyword related to the broker;
determining the matching degree of the broker and the client according to the service area, the gender and the age of the broker;
determining the score of the broker according to the working years, the transaction times and the customer evaluation level of the broker, wherein the higher the years, the more the transaction times and the higher the customer evaluation level are, the higher the finally obtained score is;
carrying out weighted summation calculation on the correlation degree of the broker and the retrieval formula, the matching degree of the broker and the clients and the score of the broker to obtain a comprehensive score of the broker;
the brokers matched with the clients are ranked according to the comprehensive scores of the brokers, and the ranked results are sent to the information pushing module;
the matching module obtains the broker comprehensive score based on the following modes:
firstly, obtaining the retrieval matching degree, wherein the specific steps are as follows:
a1, acquiring broker related information description, performing word segmentation processing on the broker related information description to obtain a plurality of word segmentation words, performing word stop filtering processing on the word segmentation words, and forming a broker keyword set;
a2, acquiring each keyword in the search formula, and calculating the matching degree of the broker and the search formula;
Figure BDA0002230066490000061
wherein, P1 is the matching degree between broker and search formula, S is the total number of keywords in search formula, AiBroker feature vector corresponding to ith keyword in search formulaThe broker feature vector is a value of N feature indicators of the keyword in broker description, where the feature indicators include the number of times that the keyword appears in a participle word of the broker, the number of times that the keyword word appears in all broker keyword sets, whether the keyword appears in a first sentence of the broker description, whether the keyword appears in a last sentence of the broker description, λ is a preset feature coefficient vector, that is, a coefficient corresponding to each feature indicator in the broker feature vector corresponding to the keyword, and c is a preset constant parameter;
then, acquiring the basic information matching degree of the client and the broker;
Figure BDA0002230066490000062
wherein P2 is the matching degree between the broker and the client, Dj is the set formed by the administrative division of the broker service area, Dy is the set formed by the administrative division of the area where the client intends to the house source, xb is whether the client is the same as the broker, Yj is the age of the broker, Yy is the age of the client, Sj is the numerical value of the education level of the broker, and Sy is the numerical value of the education level of the client;
then, determining a broker capability score, wherein determining the broker capability score comprises the steps of;
step B1, acquiring the numerical values of K ability indexes of the broker, wherein the ability indexes include: the working years, the times of bargaining, the client evaluation, the customs capacity, the working enthusiasm and the professional knowledge capacity of the broker;
step B2, determining the ability score of the broker;
Figure BDA0002230066490000071
wherein P3 is the broker's competency score, μjScore factor, F, which is the preset jth capability index of the brokerjNumeralization of jth capability index of brokerThe value j ═ 1, 2, 3 … K;
finally, determining the comprehensive score of the broker;
P＝(arcsin(P1)*P1+arcsin(P2)*P2)2+(arcsin(P3)*P3+arcsin(P2)*P2)2+(arcsin(P3)*P3+arcsin(P1)*P1)2
wherein P is the comprehensive score of the broker.
The matching module realizes the function of determining the priority of a plurality of search keywords and the function of sequencing by the following modes:
step B1, randomly extracting basic information of L brokers from the matching system of the house property intermediary service platform client and the broker;
step B2, determining the non-information-containing degree of the search keyword;
Figure BDA0002230066490000072
the method comprises the steps that Fh is the non-information-containing degree of a search keyword, lg is the number of basic information of a broker related to the search keyword in basic information of L brokers extracted at random, and hg is the number of basic information of the broker including the search keyword in the number of basic information of the broker related to the search keyword, namely the number of basic information of the broker including the search keyword in the basic information of the broker corresponding to lg;
step B3, determining the non-irrelevant information content of the search keyword;
Figure BDA0002230066490000081
wh is the amount of non-irrelevant information of the search keyword, Lg is the amount of basic information of brokers containing the search keyword in the basic information of L brokers extracted at random;
step B4, determining the weight coefficient of the keyword;
Figure BDA0002230066490000082
wherein, Qz is the weight coefficient of the keyword, Ca is the first correction coefficient of the preset weight, and Cb is the second correction coefficient of the preset weight;
and step B5, obtaining the weight coefficients of all the search keywords, and sequencing the search keywords from large to small according to the weight coefficients to form a keyword priority vector, wherein the priority of the search keywords arranged in the front in the keyword priority vector is higher.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1A is a functional block diagram of an embodiment of a customer requirement matching system of a property broker service platform according to the present invention;
FIG. 1B is a functional block diagram of an embodiment of a matching system of clients and brokers based on a real estate agency service platform according to the present invention;
FIG. 1C is a flowchart illustrating a matching method between a client and a broker on a real estate agency service platform according to an embodiment of the present invention;
fig. 2 is a flowchart of a matching method between a client and a broker in a real estate agency service platform according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
FIG. 1A is a schematic diagram of the devices comprising the customer requirement matching system of the property broker service platform, as shown in FIG. 1A; the invention relates to a client requirement matching system of a real estate agency service platform, which is only divided in function in the embodiment shown in fig. 1A and can be described as shown in fig. 1A: a customer house demand side 1; an intermediate house providing terminal 2; a matching platform 3;
the customer house demand end 1 is used for providing a plurality of house demand information and expected purchase prices of corresponding demands to the matching platform 3;
the intermediary house providing terminal 2 is used for sending house information for renting and selling to the matching platform 3;
the matching platform 3 comprises: the system comprises an area classification module, a demand matching module, a price matching module and an area section house type matching module, and is used for determining house information matched with a customer house demand end 1 according to a plurality of pieces of house demand information provided by the customer house demand end 1 and expected purchase prices of corresponding demands, and sending the house information matched with the customer house demand end 1 to the customer house demand end 1.
In this embodiment, the area classification module is configured to classify the house information according to an area where the house information is located; the demand matching module is used for matching corresponding brokers according to the demands of users (namely clients) corresponding to the client house demand end, and the price matching module is used for matching corresponding house information according to the expected purchase price of the users; and the regional section house type matching module is used for matching the house information of the response according to the house type expected by the user.
The invention has the beneficial effects that: the matched house information can be determined based on multiple house requirements, so that a user can quickly determine a favorite house source, house transaction can be quickly facilitated, the user time is saved, and the user experience is improved.
As shown in FIG. 1B, FIG. 1B is a schematic diagram of functional modules in a demand matching module; the invention relates to a client requirement matching system of a real estate agency service platform, which is only divided in function in the embodiment shown in fig. 1B and can be described as shown in fig. 1B: a type judgment module 110; a matching module 120; an information push module 130; the type determining module 110 is configured to determine a user type according to the login account request, the matching module 120 is configured to obtain information of a broker matched with a client, and the information pushing module 130 is configured to send the information of the broker matched with the client to the client.
In an embodiment, the type determining module 110 is configured to receive a request from a user to log in an account, and determine a type of the user according to the request; sending the determined user type to the matching module 120; wherein the user type comprises any one of a client and a broker; when determining the user type, the type determining module 110 determines whether the user is a client or a broker according to the account type identifier, and sends the determination result to the matching module 120. For example, when a user registers, a drop-down list for the user to select a registration type is provided, the drop-down list includes a client and a broker, when the registration type selected by the user is the client, the account type is identified as the client, and when the registration type selected by the user is the broker, the account type is identified as the broker. Wherein different types of accounts provide different types of functionality.
The matching module 120 is configured to, when the user type is a customer, obtain information of a first preset type corresponding to the customer; the first preset type of information corresponding to the client comprises one or more items of information of positioning information of the user, user information filled in when an account is registered, keyword information submitted in retrieval, screening condition information corresponding to screening operation, historical behavior information and the like; generating retrieval conditions of the broker users according to the acquired information of the first preset type; searching a database storing broker information according to the generated retrieval condition of the broker to obtain information of the broker matched with the client; and sends the information of the customer and the information of the broker matched with the customer to the information pushing module 130.
The information pushing module 130 is configured to, when receiving the information of the customer and the information of the broker matched with the customer, sent by the matching module 120, send the information of the broker matched with the customer to the customer.
The invention has the beneficial effects that: the house source information is not directly displayed to the client, but the information of the broker matched with the client information is sent to the client, the experience of the client cannot be reduced due to the fact that the broker is in butt joint with the client, the risk of house source information leakage is reduced due to the fact that the house source information does not need to be directly displayed on a user interface, and the safety of the house source information is protected on the basis that the experience degree of the client is not influenced.
In one embodiment of the present invention,
the type determining module 110 is configured to, when receiving a request for a user to log in an account, determine whether the user is a client or a broker according to an account type identifier, and send a determination result to the matching module 120; the account type identification is generated based on a registration type selected when the user registers, and the selectable registration types comprise a client and a broker. For example, when a user registers, a drop-down list for the user to select a registration type is provided, the drop-down list includes a client and a broker, when the registration type selected by the user is the client, the account type is identified as the client, and when the registration type selected by the user is the broker, the account type is identified as the broker. Wherein different types of accounts provide different types of functionality.
In one embodiment of the present invention,
the matching module 120 is further configured to, when the user type is a broker, obtain information of a second preset type corresponding to the broker; the second preset type of information corresponding to the broker comprises one or more items of information of the service area of the broker, the working years of the broker, the number of deals, a contact way, a customer evaluation level, gender, age and the like; generating a retrieval condition of the client according to the acquired information of the second preset type; searching a database storing customer information according to the generated retrieval condition of the customer to obtain information of the customer matched with the broker; and send the information of the broker and the information of the customer matched with the broker to the information pushing module 130; the information pushing module 130 is further configured to, when receiving that the matching module 120 sends the information of the broker and the information of the customer matching with the broker, send the information of the customer matching with the broker to the broker.
The beneficial effect of this embodiment lies in: when receiving the information of the broker and the information of the customer matched with the broker, which are sent by the matching module 120, the information pushing module 130 can send the information of the customer matched with the broker to the broker, so that the broker can actively find the user matched with the broker, and the channel of potential customers mined by the broker is expanded.
In one embodiment of the present invention,
the matching module 120 is configured to, when the user type is a client, obtain one or more pieces of information of positioning information of the user, user information filled in when an account is registered, keyword information submitted during retrieval, screening condition information corresponding to a screening operation, and historical behavior information; and generating a retrieval formula related to the broker information according to the acquired one or more items of information, and retrieving the broker information database according to the retrieval formula to acquire the matched broker information. For example, when a user logs in, it is determined whether the user is a client or a broker, and when the user is a client, the intention (selling, renting, buying, renting) of the user needs to be determined, so that the current positioning information of the user can be acquired, and personal information after the user logs in, such as the age, sex and income of the user. Historical behavior data of the user can be acquired, the historical behavior data can be historical browsing records, historical retrieval records and the like of the user, so that user preference, user intention, browsed house source information and the like can be acquired according to the historical browsing records of the user, a retrieval formula related to broker information is generated according to the information, and a broker information database is retrieved according to the retrieval formula, so that broker information matched with the user preference or intention house source is acquired.
In one embodiment of the present invention,
the matching module 120 is used for matching the first pre-stage data according to the first pre-stage data corresponding to the clientSetting type information to generate a search keyword; when the retrieval keywords are multiple, determining the priorities of the retrieval keywords, and sequencing the retrieval keywords based on the priorities of the retrieval keywords to form a retrieval formula related to broker information, wherein the retrieval keywords with higher priorities are ranked more ahead; and searching the broker information database according to the searching mode. For example, the keywords generated according to the first preset type of information corresponding to the customer are: chang-ping district, shopping room, two houses, less than 300 ten thousand and more than 60m2The age of the room is less than 5 years and faces south. The keywords are sorted from large to small according to the priority: house purchase, Chang's plain area, less than 300 ten thousand, two houses, more than 60m2South facing and the age of the house is less than 5 years. Therefore, the search formula for ranking the search keywords based on their priorities to form broker information correlation is: house purchase-Chang Ping district-less than 300 ten thousand-two houses-more than 60m2South-facing-age less than 5 years. The broker information database is then retrieved according to the retrieval formula.
In one embodiment of the present invention,
the matching module 120 is further configured to, when broker information is not searched after the broker information database is retrieved according to the retrieval formula, remove the keyword with the lowest priority in the retrieval formula to form a new retrieval formula; and searching the broker information database according to the new searching mode. For example, the search formula formed by sorting the search keywords according to the priority is: house purchase-Chang Ping district-less than 300 ten thousand-two houses-more than 60m2South-facing-age less than 5 years. When searching according to the search formula, a house meeting all the search conditions needs to be screened from the database, and then a corresponding broker is determined according to the house meeting all the search conditions. However, since there are many search conditions set in the search formula, there is a high possibility that there is no house meeting the search conditions in the search database, and therefore, in this embodiment, when broker information is not searched after the broker information database is searched according to the search formula, the keyword "age of house is less than 5 years" with the lowest priority in the search formula is removed, thereby forming a new searchThe retrieval type house purchase-Chang ping district-less than 300 ten thousand-two houses-more than 60m2And in the south, retrieving according to the retrieval formula, if the broker information is searched, sending the broker information to the information pushing module 130, and if the broker information is not searched, continuously removing the keyword with the lowest priority to form a new retrieval formula for retrieval until the broker information is searched or no keyword which can be removed in the retrieval formula exists.
The beneficial effect of this embodiment lies in: when broker information is not searched after the broker information database is retrieved according to the retrieval formula, removing the keyword with the lowest priority in the retrieval formula to form a new retrieval formula; and retrieving the broker information database according to the new retrieval mode, thereby avoiding the situation that the broker information cannot be searched.
In one embodiment of the present invention,
the matching module 120 is configured to, when the broker information database is a local database, retrieve the local broker information database according to a retrieval formula; when the broker information database is a remote database, encrypting the search formula according to a preset encryption algorithm to form an encrypted search formula; and sending a retrieval request to the remote broker information database according to the encrypted retrieval formula, and receiving a retrieval result fed back by the remote broker information database, wherein an encryption algorithm agreed with the local area in advance is stored in the remote broker database.
The beneficial effect of this embodiment lies in: when the broker information database is a remote database, the search formula can be encrypted according to a preset encryption algorithm, so that an encrypted search formula is formed; and the retrieval information is prevented from being stolen.
In one embodiment of the present invention,
the function of encrypting the search expression according to a preset encryption algorithm in the matching module 120 is implemented based on the following steps:
acquiring the priority of each keyword; determining an encryption grade corresponding to each keyword according to the priority of each keyword, wherein each encryption grade corresponds to a different encryption algorithm, and the higher the encryption grade is, the higher the decryption difficulty after encryption is; encrypting each keyword according to an encryption algorithm corresponding to each keyword, and combining the encrypted keywords to form an encrypted retrieval formula;
wherein the encryption level is determined based on:
performing analog encryption on a preset encryption object according to each encryption algorithm to form a plurality of encrypted encryption objects; deciphering the plurality of encrypted objects to determine the deciphering difficulty of each encrypted object; and determining the encryption grade corresponding to each encryption algorithm according to different decoding difficulties of the encrypted objects, wherein the higher the decoding difficulty of the encrypted objects is, the higher the encryption grade of the corresponding encryption algorithm is.
The beneficial effect of this embodiment lies in: the encryption grade corresponding to each keyword is determined according to the priority of each keyword, so that the keywords with different priorities correspond to different encryption algorithms, the retrieval formula is encrypted by various different encryption modes, the decryption difficulty of the retrieval formula is increased, and the security of the retrieval formula is further improved.
In one embodiment of the present invention,
the matching module 120 is configured to perform,
determining the relevancy of the broker and each keyword in the search formula; acquiring the priority of each keyword related to the broker, and calculating the correlation between the broker and the retrieval formula according to the correlation between the broker and each keyword in the retrieval formula and the priority of each keyword related to the broker;
determining the matching degree of the broker and the user according to the service area, the gender and the age of the broker;
determining the score of the broker according to the working years, the transaction times and the customer evaluation level of the broker, wherein the higher the years, the more the transaction times and the higher the customer evaluation level are, the higher the finally obtained score is;
carrying out weighted summation calculation on the correlation degree of the broker and the retrieval formula, the matching degree of the broker and the user and the score of the broker to obtain the comprehensive score of the broker;
and ranking the brokers matched with the clients according to the comprehensive scores of the brokers, and sending the ranked results to the information pushing module 130.
The matching module 130 obtains the broker composite score based on the following calculation method:
firstly, obtaining the retrieval matching degree, wherein the specific steps are as follows:
a1, acquiring broker related information description, performing word segmentation processing on the broker related information description to obtain a plurality of word segmentation words, performing word stop filtering processing on the word segmentation words, and forming a broker keyword set;
a2, acquiring each keyword in the search formula, and calculating the matching degree of the broker and the search formula;
Figure BDA0002230066490000151
wherein, P1 is the matching degree between broker and search formula, S is the total number of keywords in search formula, AiRetrieving a broker feature vector corresponding to an ith keyword in a formula, wherein the broker feature vector is a value of N feature indexes of the keyword in broker description, the feature indexes comprise the times of occurrence of the keyword in participle words of the broker, the times of occurrence of the keyword in all broker keyword sets, whether the keyword occurs in a first sentence of the broker description, whether the keyword occurs in a last sentence of the broker description, lambda is a preset feature coefficient vector, namely a coefficient corresponding to each feature index in the broker feature vector corresponding to the keyword, and c is a preset constant parameter;
then, acquiring the basic information matching degree of the client and the broker;
Figure BDA0002230066490000161
wherein P2 is the matching degree between the broker and the client, Dj is the set formed by the administrative division of the broker service area, Dy is the set formed by the administrative division of the area where the client intends to the house source, xb is whether the client is the same as the broker, Yj is the age of the broker, Yy is the age of the client, Sj is the numerical value of the education level of the broker, and Sy is the numerical value of the education level of the client;
then, determining a broker capability score, wherein determining the broker capability score comprises the steps of;
step B1, acquiring the numerical values of K ability indexes of the broker, wherein the ability indexes include: the working years, the times of bargaining, the client evaluation, the customs capacity, the working enthusiasm and the professional knowledge capacity of the broker;
step B2, determining the ability score of the broker;
Figure BDA0002230066490000162
wherein P3 is the broker's competency score, μjScore factor, F, which is the preset jth capability index of the brokerjNumerically assigning j to the jth ability index of the broker, where j is 1, 2, 3 … K;
finally, determining the comprehensive score of the broker;
P＝(arcsin(P1)*P1+arcsin(P2)*P2)2+(arcsin(P3)*P3+arcsin(P2)*P2)2+(arcsin(P3)*P3+arcsin(P1)*P1)2
wherein P is the comprehensive score of the broker.
The invention also provides a matching method of the client and the broker of the house property intermediary service platform, which is used for introducing the implementation flows of some main functions in the system and specifically comprises the following steps:
as shown in fig. 1C, the matching method of the real estate agency service platform client and broker can be implemented as the following steps S11-S13:
in step S11, when a first preset trigger event is received, obtaining information of a user corresponding to the first preset trigger event;
in step S12, acquiring information of brokers matching the information of the user;
in step S13, information of the broker that matches the information of the user is sent to the user.
In this embodiment, when a first preset trigger event is received, information of a user corresponding to the first preset trigger event is acquired; acquiring information of brokers matched with the information of the users; and sending information of the broker matched with the information of the user to the user.
The first preset trigger event may be an account login event, a retrieval event and a screening event of the user. The information of the broker matched with the information of the user may be positioning information of the user, user information filled in when the account is registered, keywords input during retrieval, and filtering conditions and historical behavior data corresponding to filtering operations.
The invention has the beneficial effects that: when a first preset trigger event is received, acquiring user information corresponding to the first preset trigger event; acquiring information of brokers matched with the information of the users; and the house source information is protected on the basis that the user experience degree is not influenced.
In one embodiment, the first preset trigger event includes at least one of the following events:
the method comprises the steps that account login events, retrieval events and screening events of a user are carried out;
step S11 may be implemented as the following steps:
and acquiring positioning information of the user, user information filled in when the account is registered, keywords input in retrieval, screening conditions corresponding to screening operation and historical behavior data.
The beneficial effect of this embodiment lies in: when the first preset trigger event is an account login event, positioning information of a user, user information filled in when the account is registered and historical behavior data can be acquired, so that the corresponding broker can be matched without user retrieval, and user operation is simplified.
In this embodiment, the first preset trigger event includes at least one of the following events: account login events, retrieval events and screening events of the user. The following describes the processing mechanism of the server in detail by taking the above three events as examples respectively:
example 1
When a user logs in, the server detects an account login event, and can acquire information of the user after the account login, wherein the information can include current positioning information of the user, and user information filled in when the account is registered, such as age, gender and income of the user. Historical behavior data of the user can be obtained, the historical behavior data can be historical browsing records, historical retrieval records and the like of the user, so that the favorite and the intention of the user can be obtained according to the historical browsing records of the user, broker information matched with the favorite or the intention of the user can be obtained, and the broker information matched with the user information can be sent to the user.
Example two
When a user searches, the server detects a search event, can acquire a keyword input by the user during searching, can acquire an intention house source of the user based on the keyword, and further acquire broker information matched with the intention house source of the user, such as a broker in charge of an area where the intention house source of the user is located. The information of the broker matching the user information is then sent to the user.
Example three
The front-end page of the server is provided with various screening conditions, for example, user requirements (such as selling, renting, purchasing and renting), house source addresses, price intervals, house areas, orientation, house ages and the like.
In one embodiment, as shown in FIG. 2, the above step S12 can be implemented as the following steps S21-S24:
in step S21, determining a requirement of the user according to the user information corresponding to the first preset trigger event;
in step S22, generating a user matching condition parameter according to the user requirement;
in step S23, retrieving a broker database according to the user matching condition parameters;
in step S24, broker information in the retrieval result is acquired as broker information that matches the user information.
In this embodiment, the user demand includes a selling demand, a renting demand, a purchasing demand, and a renting demand. And if the request is a purchase request or a lease request, the user request further comprises a house source address, a price interval, a house area, an orientation, a house age and the like, then a user matching condition parameter is generated based on the requests, the user matching condition parameter is used as a searching condition to search the broker database, and then the broker information in the searching result is obtained as the broker information matched with the user information.
In one embodiment, the above step S13 may be implemented as the following steps A1-A4:
in step a1, determining the number of brokers in the retrieval result;
in step a2, when the number of the dealers is one, sending information of the broker matched with the information of the user to the user;
in step a3, when the number of brokers is plural, ranking the plural brokers;
in step A4, the sorted results are sent to the user.
In one embodiment, the above step A3 may be implemented as the following steps B1-B2 or B3-B4:
in step B1, scoring the plurality of brokers in accordance with the broker information;
in step B2, sorting the plurality of brokers in descending order according to the scoring result;
in step B3, calculating matching degrees of the plurality of brokers and users corresponding to the first preset trigger event according to the broker information;
in step B4, sorting the plurality of brokers in descending order according to the matching degree of the broker and the user corresponding to the first preset trigger event.
For example, broker information includes the broker's serving area, the broker's age of employment, number of deals, contact details, customer rating, gender, age, and the like.
The broker may be scored based on broker information, for example, the broker may be scored based on information such as the age of the job, the number of times of the transaction, and the rating level of the customer, where the higher the age, the greater the number of times of the transaction, and the higher the rating level of the customer, the higher the resulting score, and then the brokers may be sorted in descending order according to the scoring result, so that the broker with the highest score is ranked at the top.
The matching degree of the broker and the user may also be calculated, for example, the smaller the age difference between the broker and the user is, the higher the matching degree is, the closer the service area of the broker is to the house address of the user, the higher the matching degree is, and then the brokers are sorted in descending order according to the matching degree, so that the broker with the highest matching degree with the user is ranked at the forefront. And the user screening is convenient.
The beneficial effect of this embodiment lies in: the brokers can be sorted in descending order based on the broker scores or matching degrees, so that the broker with the highest score or the highest matching degree with the users is ranked in the top, and the screening speed of the users is increased.
In one embodiment, the method may also be implemented as the following steps C1-C3:
in step C1, when a second preset trigger event is received, acquiring information of a broker corresponding to the second preset trigger event;
in step C2, obtaining information of users matching the information of the broker;
in step C3, information of the user matching the information of the broker is sent to the broker.
In this embodiment, when a second preset trigger event is received, information of a broker corresponding to the second preset trigger event is acquired; acquiring information of a user matched with the information of the broker; sending information of the users matched with the information of the broker to the broker.
The second preset trigger event may be a registration event of the broker, a retrieval event of the broker, or a filtering event of the broker. And then based on the events, acquiring a house selling address, a renting address or an intention house source and a user matched with the broker service area, the retrieval keyword or the screening condition.
The beneficial effect of this embodiment lies in: when a second preset trigger event is received, acquiring information of a broker corresponding to the second preset trigger event; acquiring information of a user matched with the information of the broker; and sending the information of the users matched with the information of the broker to the broker, so that the broker can actively find the users matched with the broker, and a channel for the broker to mine potential customers is expanded.
The matching module realizes the function of determining the priority of a plurality of search keywords and the function of sequencing by the following modes:
step B1, randomly extracting basic information of L brokers from the matching system of the house property intermediary service platform client and the broker;
step B2, determining the non-information-containing degree of the search keyword;
Figure BDA0002230066490000211
the method comprises the steps that Fh is the non-information-containing degree of a search keyword, lg is the number of basic information of a broker related to the search keyword in basic information of L brokers extracted at random, and hg is the number of basic information of the broker including the search keyword in the number of basic information of the broker related to the search keyword, namely the number of basic information of the broker including the search keyword in the basic information of the broker corresponding to lg;
when the quantity of the basic information of the broker related to the search keyword in the L pieces of basic information of the broker extracted at random is determined, and the basic information of the broker contains the keyword, the basic information of the broker is related to the search keyword
Meanwhile, a sentence of a certain basic information contains a keyword, and a sentence in another broker basic information contains a sentence which is completely the same as the sentence containing the keyword and is only different from the keyword, the basic information is determined as broker related to the search keyword, for example, the keyword is "boy", the basic information of broker a contains the sentence containing the keyword, the broker is boy, broker B contains the sentence, the broker is woman, and other words are the same except the keyword, and the basic information of broker B is related to the search keyword.
Step B3, determining the non-irrelevant information content of the search keyword;
Figure BDA0002230066490000212
wh is the amount of non-irrelevant information of the search keyword, Lg is the amount of basic information of brokers containing the search keyword in the basic information of L brokers extracted at random;
step B4, determining the weight coefficient of the keyword;
Figure BDA0002230066490000221
wherein, Qz is the weight coefficient of the keyword, Ca is the first correction coefficient of the preset weight, and Cb is the second correction coefficient of the preset weight;
wherein the preset values of Ca and Cb are 0 to 1;
and step B5, obtaining the weight coefficients of all the search keywords, and sequencing the search keywords from large to small according to the weight coefficients to form a keyword priority vector, wherein the priority of the search keywords arranged in the front in the keyword priority vector is higher.
The beneficial effect of this embodiment lies in: by using the technology, the search keywords can be sequenced according to different content of information entropy in search, so that the priority of the search keywords in the priority vector of the finally obtained keywords is higher, and the search keywords with higher keyword priority are matched firstly in search.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (10)

1. A real estate agency service platform customer requirement matching system, the system comprising: a customer premises requirement end; a mediating house providing end; a matching platform;
the client house demand end is used for providing a plurality of house demand information and expected purchase prices of corresponding demands to the matching platform;
the intermediary house providing end is used for sending house information for renting and selling to the matching platform;
the matching platform comprises: the system comprises an area classification module, a demand matching module, a price matching module and an area section house type matching module, and is used for determining house information matched with a customer house demand end according to a plurality of house demand information provided by the customer house demand end and an expected purchase price of a corresponding demand, and sending the house information matched with the customer house demand end to the customer house demand end.
2. The system of claim 1, wherein the requirement matching module comprises: a type judgment module; a matching module; an information push module;
the type judgment module is used for receiving a request of a client house demand end user for logging in an account and judging the type of the user according to the request; sending the judged user type to a matching module; wherein the user type comprises any one of a client and a broker;
the matching module is used for acquiring information of a first preset type corresponding to a client when the user type is the client; generating retrieval conditions of the broker users according to the acquired information of the first preset type; searching a database storing broker information according to the generated retrieval condition of the broker to obtain information of the broker matched with the client; sending the information of the client and the information of the broker matched with the client to the information pushing module;
and the information pushing module is used for sending the information of the broker matched with the client to the client when receiving the information of the client and the information of the broker matched with the client, which are sent by the matching module.
3. The system of claim 2,
the matching module is further used for acquiring information of a second preset type corresponding to the broker when the user type is the broker; generating a retrieval condition of the client according to the acquired information of the second preset type; searching a database storing customer information according to the generated retrieval condition of the customer to obtain information of the customer matched with the broker; sending the information of the broker and the information of the clients matched with the broker to the information pushing module;
the information pushing module is further used for sending the information of the client matched with the broker to the broker when receiving the information of the broker and the information of the client matched with the broker sent by the matching module;
the first preset type of information corresponding to the client comprises at least one of the following information:
positioning information, personal information filled in when an account is registered, keyword information submitted in retrieval, screening condition information corresponding to screening operation and historical behavior information;
the second preset type of information corresponding to the broker includes at least one of the following information:
the service area of the broker, the working years of the broker, the number of deals, the contact information, the rating of the customer, the sex and the age.
4. The system of claim 3,
the matching module is used for acquiring one or more items of information in positioning information of a user, personal information filled in when an account is registered, keyword information submitted in retrieval, screening condition information corresponding to screening operation and historical behavior information when the user type is a client; and generating a retrieval formula related to the broker information according to the acquired one or more items of information, and retrieving the broker information database according to the retrieval formula to acquire the matched broker information.
5. The system of claim 4,
the matching module is used for generating a retrieval keyword according to the information of the first preset type corresponding to the client; when the retrieval keywords are multiple, determining the priorities of the retrieval keywords, and sequencing the retrieval keywords based on the priorities of the retrieval keywords to form a retrieval formula related to broker information, wherein the retrieval keywords with higher priorities are ranked more ahead; and searching the broker information database according to the searching mode.
6. The system of claim 4 or 5,
the matching module is also used for removing the keyword with the lowest priority in the search formula to form a new search formula when the broker information is not searched after the broker information database is searched according to the search formula; and searching the broker information database according to the new searching mode.
7. The system of any one of claims 4 to 6,
the matching module is used for retrieving the local broker information database according to a retrieval formula when the broker information database is a local database; when the broker information database is a remote database, encrypting the search formula according to a preset encryption algorithm to form an encrypted search formula; and sending a retrieval request to the remote broker information database according to the encrypted retrieval formula, and receiving a retrieval result fed back by the remote broker information database, wherein an encryption algorithm agreed with the local area in advance is stored in the remote broker database.
8. The system of any one of claims 4 to 6,
the function of encrypting the retrieval formula according to a preset encryption algorithm in the matching module is realized based on the following steps:
acquiring the priority of each keyword; determining an encryption grade corresponding to each keyword according to the priority of each keyword, wherein each encryption grade corresponds to a different encryption algorithm, and the higher the encryption grade is, the higher the decryption difficulty after encryption is; encrypting each keyword according to an encryption algorithm corresponding to each keyword, and combining the encrypted keywords to form an encrypted retrieval formula;
wherein the encryption level is determined based on:
performing analog encryption on a preset encryption object according to each encryption algorithm to form a plurality of encrypted encryption objects; deciphering the plurality of encrypted objects to determine the deciphering difficulty of each encrypted object; and determining the encryption grade corresponding to each encryption algorithm according to different decoding difficulties of the encrypted objects, wherein the higher the decoding difficulty of the encrypted objects is, the higher the encryption grade of the corresponding encryption algorithm is.
9. The system according to any one of claims 2-8,
the matching module is used for matching the received signal with the reference signal,
determining the relevancy of the broker and each keyword in the search formula; acquiring the priority of each keyword related to the broker, and calculating the correlation between the broker and the retrieval formula according to the correlation between the broker and each keyword in the retrieval formula and the priority of each keyword related to the broker;
determining the matching degree of the broker and the client according to the service area, the gender and the age of the broker;
determining the score of the broker according to the working years, the transaction times and the customer evaluation level of the broker, wherein the higher the years, the more the transaction times and the higher the customer evaluation level are, the higher the finally obtained score is;
carrying out weighted summation calculation on the correlation degree of the broker and the retrieval formula, the matching degree of the broker and the clients and the score of the broker to obtain a comprehensive score of the broker;
the brokers matched with the clients are ranked according to the comprehensive scores of the brokers, and the ranked results are sent to the information pushing module;
the matching module obtains the broker comprehensive score based on the following modes:
firstly, obtaining the retrieval matching degree, wherein the specific steps are as follows:
a1, acquiring broker related information description, performing word segmentation processing on the broker related information description to obtain a plurality of word segmentation words, performing word stop filtering processing on the word segmentation words, and forming a broker keyword set;
a2, acquiring each keyword in the search formula, and calculating the matching degree of the broker and the search formula;
Figure FDA0002230066480000041
wherein, P1 is the matching degree between broker and search formula, and S is the key in search formulaTotal number of words, AiRetrieving a broker feature vector corresponding to an ith keyword in a formula, wherein the broker feature vector is a value of N feature indexes of the keyword in broker description, the feature indexes comprise the times of occurrence of the keyword in participle words of the broker, the times of occurrence of the keyword in all broker keyword sets, whether the keyword occurs in a first sentence of the broker description, whether the keyword occurs in a last sentence of the broker description, lambda is a preset feature coefficient vector, namely a coefficient corresponding to each feature index in the broker feature vector corresponding to the keyword, and c is a preset constant parameter;
then, acquiring the basic information matching degree of the client and the broker;
Figure FDA0002230066480000051
wherein P2 is the matching degree between the broker and the client, Dj is the set formed by the administrative division of the broker service area, Dy is the set formed by the administrative division of the area where the client intends to the house source, xb is whether the client is the same as the broker, Yj is the age of the broker, Yy is the age of the client, Sj is the numerical value of the education level of the broker, and Sy is the numerical value of the education level of the client;
then, determining a broker capability score, wherein determining the broker capability score comprises the steps of;
step B1, acquiring the numerical values of K ability indexes of the broker, wherein the ability indexes include: the working years, the times of bargaining, the client evaluation, the customs capacity, the working enthusiasm and the professional knowledge capacity of the broker;
step B2, determining the ability score of the broker;
Figure FDA0002230066480000052
wherein P3 is the broker's competency score, μjAs a pre-arranged brokerThe score coefficient of the jth ability index, FjNumerically assigning j to the jth ability index of the broker, where j is 1, 2, 3 … K;
finally, determining the comprehensive score of the broker;
P＝(arcsin(P1)*P1+arcsin(P2)*P2)2+(arcsin(P3)*P3+arcsin(P2)*P2)2+(arcsin(P3)*P3+arcsin(P1)*P1)2
wherein P is the comprehensive score of the broker.
10. The system of claim 5,
the matching module realizes the function of determining the priority of a plurality of search keywords and the function of sequencing by the following modes:
step B1, randomly extracting basic information of L brokers from the matching system of the house property intermediary service platform client and the broker;
step B2, determining the non-information-containing degree of the search keyword;
Figure FDA0002230066480000061
the method comprises the steps that Fh is the non-information-containing degree of a search keyword, lg is the number of basic information of a broker related to the search keyword in basic information of L brokers extracted at random, and hg is the number of basic information of the broker including the search keyword in the number of basic information of the broker related to the search keyword, namely the number of basic information of the broker including the search keyword in the basic information of the broker corresponding to lg;
step B3, determining the non-irrelevant information content of the search keyword;
Figure FDA0002230066480000062
wh is the amount of non-irrelevant information of the search keyword, Lg is the amount of basic information of brokers containing the search keyword in the basic information of L brokers extracted at random;
step B4, determining the weight coefficient of the keyword;
Figure FDA0002230066480000063
wherein, Qz is the weight coefficient of the keyword, Ca is the first correction coefficient of the preset weight, and Cb is the second correction coefficient of the preset weight;
and step B5, obtaining the weight coefficients of all the search keywords, and sequencing the search keywords from large to small according to the weight coefficients to form a keyword priority vector, wherein the priority of the search keywords arranged in the front in the keyword priority vector is higher.
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