CN113344660A

CN113344660A - House source information processing method and device, electronic equipment and storage medium

Info

Publication number: CN113344660A
Application number: CN202110591905.0A
Authority: CN
Inventors: 陈美强
Original assignee: Shenzhen Qianhai Fang Geek Network Technology Co ltd
Current assignee: Shenzhen Qianhai Fang Geek Network Technology Co ltd
Priority date: 2021-05-28
Filing date: 2021-05-28
Publication date: 2021-09-03

Abstract

The embodiment of the application provides a method and a device for processing house source information, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring a plurality of user behavior records aiming at published house source information; sequencing the plurality of user behavior records according to the sequence of the trigger time from first to last to obtain a user behavior record sequence; calculating the behavior density parameter of each user behavior triggered by the user of each user role according to the user behavior records and the user roles to which the user from which the user behavior records belong; obtaining dynamic scores of target house resources indicated by the published house resource information according to the first adjusting factor and the second adjusting factor of each scoring item and the basic scores corresponding to each scoring item; calculating to obtain a comprehensive score of the target house source according to the dynamic score of the target house source and the static score of the target house source; and processing the published house source information according to the comprehensive score of the target house source. The scheme ensures the reliability of the obtained processing result.

Description

House source information processing method and device, electronic equipment and storage medium

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for processing house source information, an electronic device, and a storage medium.

Background

In the house resource trading platform, generally, the score of a house resource is calculated according to the static information of the house resource, such as the information introduction (position, layout, area, price, etc.) of the house resource, and then the house resource information is processed according to the score of the house resource, so that the problem of low reliability of the processing result exists.

Disclosure of Invention

Embodiments of the present application provide a method and an apparatus for processing house source information, an electronic device, and a storage medium, so that a problem of low reliability of a processing result in a related art can be solved at least to a certain extent.

Other features and advantages of the present application will be apparent from the following detailed description, or may be learned by practice of the application.

According to an aspect of an embodiment of the present application, there is provided a method for processing house source information, including: acquiring a plurality of user behavior records aiming at published house source information; the user behavior record indicates the user behavior triggered by the published house source information and the corresponding trigger time; sequencing the plurality of user behavior records according to the sequence of the trigger time from first to last to obtain a user behavior record sequence, wherein the user behavior record sequence is used for determining a first adjustment factor of a scoring item corresponding to each user behavior record; calculating the behavior density parameter of each user behavior triggered by the user of each user role according to the user behavior records and the user roles to which the user from which the user behavior records belong; the behavior density parameter is used for determining a second adjustment factor of the scoring item corresponding to each user behavior record; obtaining dynamic scores of target house resources indicated by the published house resource information according to the first adjusting factor and the second adjusting factor of each scoring item and the basic scores corresponding to each scoring item; calculating to obtain a comprehensive score of the target house source according to the dynamic score of the target house source and the static score of the target house source; the static score is determined according to the static information of the target house source; and processing the published house source information according to the comprehensive score of the target house source.

According to an aspect of an embodiment of the present application, there is provided a processing apparatus for house source information, including: the user behavior record acquisition module is used for acquiring a plurality of user behavior records aiming at the published house source information; the user behavior record indicates the user behavior triggered by the published house source information and the corresponding trigger time; the user behavior record sequence determining module is used for sequencing the plurality of user behavior records according to the sequence of the trigger time from first to last to obtain a user behavior record sequence, and the user behavior record sequence is used for determining a first adjusting factor of a scoring item corresponding to each user behavior record; the behavior density parameter calculation module is used for calculating the behavior density parameters of the user behaviors triggered by the user of each user role according to the user behavior records and the user roles to which the user from which the user behavior records belong; the behavior density parameter is used for determining a second adjustment factor of the scoring item corresponding to each user behavior record; the dynamic score calculation module is used for obtaining the dynamic score of the target house source indicated by the published house source information according to the first adjustment factor and the second adjustment factor of each scoring item and the basic score corresponding to each scoring item; the comprehensive score determining module is used for calculating and obtaining the comprehensive score of the target house source according to the dynamic score of the target house source and the static score of the target house source; the static score is determined according to the static information of the target house source; and the processing module is used for processing the published house source information according to the comprehensive score of the target house source.

According to an aspect of an embodiment of the present application, there is provided an electronic device including: a processor; a memory having computer readable instructions stored thereon which, when executed by the processor, implement the method as described above.

According to an aspect of embodiments of the present application, there is provided a computer-readable storage medium having stored thereon computer-readable instructions which, when executed by a processor, implement a method as described above.

According to the scheme, the dynamic score of the target house source is calculated according to the user behavior record aiming at the published house source information, and then the comprehensive score of the target house source is calculated according to the dynamic score and the static score calculated according to the static information of the target house source. The user behavior records dynamically updated along with time reflect the attention degree of the published house source information, so that the scheme of the application is equivalent to determine the comprehensive score of the house source by combining the dynamic score under the dynamic dimension reflecting the attention degree condition of the house source and the static score under the static dimension, and compared with the method of scoring only according to the static dimension of the static information of the target house source, the method has higher reliability and accuracy of the obtained comprehensive score; in addition, dynamic user behavior records are mainly adopted, the influence of static information on the score is weakened, and the quality of the house resources can be reflected more comprehensively by the calculated comprehensive score.

In addition, the comprehensive score of the target house source is calculated by combining the static information and the dynamic user behavior record in the time dimension, and the influence of the static information on the score is weakened by mainly utilizing the dynamic user behavior record; the Bayesian probability superposition mode is adopted to calculate the comprehensive score of the target house source, the different user behavior records have independence, and the different user behavior records can be mutually adjudicated, so that even if defect data exists in the process of calculating the comprehensive score, the influence of the defect data on the comprehensive score can be weakened according to the newly added user behavior record, and the accuracy of the calculated comprehensive score can be ensured on the basis of the existence of the defect data. On the basis, the published house source information is processed according to the comprehensive score with high accuracy and high reliability, and the reliability and the accuracy of the processing result of the published house source information can be ensured.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:

fig. 1 shows a schematic diagram of an exemplary system architecture to which the technical solution of the embodiments of the present application can be applied.

Fig. 2 is a flowchart illustrating a method for processing house source information according to an embodiment of the present application.

Fig. 3 is a flow chart illustrating steps prior to step 240 according to one embodiment of the present application.

Fig. 4 is a flow chart illustrating steps prior to step 240 according to another embodiment of the present application.

Fig. 5 is a flow chart illustrating steps prior to step 240 according to another embodiment of the present application.

FIG. 6 is a flow diagram illustrating steps prior to step 250 according to one embodiment of the present application.

Fig. 7 is a block diagram of a processing device of house source information according to an embodiment of the present application.

FIG. 8 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the subject matter of the present application can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the application.

The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.

The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.

As shown in fig. 1, the system architecture may include a terminal device 101, a network 102, and a server 103. Network 102 is the medium used to provide, among other things, a communication link between terminal device 101 and server 102. Network 102 may include various connection types, such as wired communication links, wireless communication links, and so forth.

The terminal device 101 may be one or more of a smartphone, a tablet, a laptop computer, and a desktop computer. It should be understood that the numbers of the terminal device 101, the network 102, and the server 103 shown in fig. 1 are merely illustrative, and for example, the server may be a single server, a server cluster composed of a plurality of servers, or the like.

The terminal device 101 may run a client program for displaying published house source information, and a user interface of the client program provides a control for user interaction, for example, a forwarding control (for example, a forwarding friend circle control, a forwarding friend control) for the user to perform published house source information, a collection control for collecting published house source information, a dialing control for dialing an owner's phone or dialing a house source broker's phone, an appointment control for making an appointment for house source access, a control for editing house source information, and the like, which are not specifically limited herein. Thus, a user, such as a broker, owner, purchaser, etc., may trigger user behavior for the displayed published source information via a control in a user interface displayed by terminal device 101.

After detecting the triggering operation of the control in the page where the published house source information is located, the client correspondingly generates a user behavior record, wherein the user behavior record indicates the user behavior triggered by the user and the triggering time, and further indicates the user identification information triggering the user behavior. In particular embodiments, the triggered user behavior may be identified according to the triggered control, and thus, the user behavior record may include control information (e.g., position information of the control in the page, identification information of the control, etc.) of the triggered control, and each control is used to indicate a user behavior, and thus, the triggered user behavior may be identified according to the control information in the user behavior record.

In the scheme of the application, after the client generates the user behavior record, the user behavior is reported to the server 103, so that after the server 103 receives the user behavior records reported by a plurality of clients, the user behavior classification is performed according to the published house source information to which the user behavior record is directed, a user behavior record set corresponding to each published house source information is obtained, the comprehensive score of each house source can be calculated according to the method of the application, and the published house source information corresponding to the house source is processed.

It should be noted that the processing method for providing the house source information according to the present application is generally executed by the server 103, and accordingly, the processing device for the house source information is generally disposed in the server 103. However, in other embodiments of the present application, the terminal device 101 and the server 103 may interact to implement the solution of the present application, or the terminal device 101 with processing capability may implement the solution of the present application.

The implementation details of the technical solution of the embodiment of the present application are set forth in detail below:

fig. 2 shows a flow diagram of a method of processing house source information according to an embodiment of the present application. Referring to fig. 2, the processing method of the house source information at least includes steps 210 to 260, which are described in detail as follows:

step 210, acquiring a plurality of user behavior records aiming at published house source information; the user behavior record indicates the user behavior triggered for the published house source information and the corresponding trigger time.

The published house source information is information introduction of a house source published on a page, and may include a geographical position, price information, house layout information, a house property certificate number of the house source, building information of a cell in which the house source is located, owner information, furniture matching information, matching facility information around the house source, property information corresponding to the house source, a house source video or a house source photo, and the like, and is not specifically limited herein.

The user behavior may be forwarding (forwarding friend circle, forwarding friend, forwarding group, forwarding to other social platform, etc.), collecting, editing, dialing owner's phone, reserving to watch house, watching house for confirmation, etc., which is not specifically limited herein. In a specific embodiment, the user behavior may be identified according to the triggered control, and it can be understood that, if the triggered control is different in the interactive interface, the corresponding user behavior is also different.

The server collects user behavior records facing a plurality of clients, and then classifies the user behavior records according to the identifiers of the published house source information to which the user behavior records are directed to obtain a user behavior record set corresponding to each published house source information, wherein the user behavior record set comprises a plurality of user behavior records.

The user behavior triggered by the published house source information can reflect the attention degree of the user to the target house source indicated by the published house source information or the value evaluation of the user to the target house source indicated by the published house source information, so that the user behavior record aiming at the published house source information can reflect the quality of the corresponding target house source to a certain extent. Based on the point, the inventor proposes a scheme of the application, that is, a target house source indicated by published house source information is scored in combination with a dynamic user behavior record of a user for the published house source information.

Step 220, sequencing the plurality of user behavior records according to the sequence of the triggering time from first to last to obtain a user behavior record sequence, wherein the user behavior record sequence is used for determining a first adjustment factor of the scoring item corresponding to each user behavior record.

The first adjusting factor is an adjusting factor determined by the ranking of the user behavior sequences in the user behavior record sequence.

In the scheme of the application, each user behavior record uniquely corresponds to one scoring item, and the number of the set scoring items can be set according to actual needs. In some embodiments of the present application, the scoring items may be related to user roles to which users belong and triggered user behaviors, for example, if the user roles and the user behaviors to which users from which two user behavior records belong are the same, the scoring items corresponding to the two user behavior records are the same.

In some embodiments of the present application, the scoring items corresponding to the user behavior records may be determined according to the user behavior and the user role, that is: determining a scoring item corresponding to the user behavior record according to the user behavior indicated by the user behavior record and the user role to which the user from which the user behavior record belongs, wherein the scoring item is related to the user behavior and the user role to which the user belongs; the user roles include house broker, owner and house buyer.

In some embodiments of the present application, a first mapping relationship among a user role, a user behavior, and a rating item is pre-established, and on this basis, after a user behavior (referred to as a target user behavior for convenience of description) indicated by a user behavior record and a user role (referred to as a target user role for convenience of description) to which a user from which the user behavior record belongs are determined, a rating item associated with the target user behavior and the target user role at the same time is determined in the first mapping relationship, and then the rating item associated with the target user behavior and the target user role at the same time is determined to be a rating item corresponding to the user behavior record.

In other embodiments, the user roles may also be more granular divisions, such as a house broker further divided into a primary house broker, a secondary house broker, a tertiary house broker, etc., with the level of the house broker directly related to the expertise of the house broker. In contrast, the higher the specialty the more accurate the evaluation of the quality (or value) of the house will be by the house broker, so that for user actions triggered for the same published house information, the user actions triggered by the higher specialty the house broker may set the first adjustment factor for the corresponding score to be greater than the lower specialty.

In some embodiments of the present application, the first adjustment factor for each score may be determined according to the following process: acquiring adjustment strategy information, wherein the adjustment strategy information comprises adjustment strategies corresponding to all scoring items, and the adjustment strategies indicate the reference user behavior record sequence segments of the corresponding scoring items and corresponding adjustment factors; according to the reference user behavior record sequence segment in the adjustment strategy, sequence segment matching is carried out in the user behavior record sequence; and if the reference user behavior record sequence segment is matched in the user behavior record sequence, determining the adjustment factor in the adjustment strategy from which the reference user behavior record sequence segment is matched as a first adjustment factor of the scoring item indicated by the adjustment strategy.

Sequence segment matching refers to detecting whether a sequence segment matching a reference user behavior record sequence segment exists in a user behavior sequence segment. The reference user behavior sequence segment can be set according to actual needs. In some embodiments of the present application, if the sequence of the user behavior records in the two user behavior sequence segments is the same, the user behavior indicated by the user behavior records is the same, and the user roles to which the users from which the user behavior records belong are the same, it is considered that the two user behavior sequence segments are matched.

The user behavior record is generated by the client when detecting that the user triggers the published house source information, so that the user behavior record indicates the user identifier corresponding to the user triggering the user behavior, and the user role to which the user belongs can be determined according to the user identifier and the portrait information of the user. The user's pictorial information indicates the user role to which the user belongs.

In this embodiment, the adjustment policy is equivalent to indicating a mapping relationship between the reference user behavior record sequence segment and the first adjustment factor corresponding to the score item.

In other embodiments of the present application, the specified conditions and adjustment factors of the score items may also be preset. And if the specified condition of the scoring item is determined to be met according to the user behavior record sequence, determining the adjustment factor set for the scoring item as a first adjustment factor of the scoring item. The specified condition may be that the number of the specified user behavior records that continuously appear reaches a set number, or may be one or more second specified user behavior records in which the specified user behavior triggered by the specified user role exists before the first specified user behavior record, and may be specifically set according to actual needs.

Step 230, calculating a behavior density parameter of each user behavior triggered by the user of each user role according to the user behavior records and the user roles to which the user from which the user behavior records belong; and the behavior density parameter is used for determining a second adjusting factor of the scoring item corresponding to each user behavior record.

The behavior density parameter is used for reflecting the intensity of the user behavior. The degree of intensity of the user behavior may be the degree of intensity in time or the degree of intensity in the information exposure. The intensity in time can be calculated according to the number of user behaviors and the release time of the released house source information; the degree of intensity in the information exposure can be calculated according to the number of user behaviors and the exposure of the published house source information.

As described above, users with different user roles have different accuracy of value evaluation on the target source and/or attention on the target source for the same user behavior, and therefore, in the solution of the present application, the user behavior is further divided according to the user roles, for example, for a user behavior of a forwarding friend, the user behavior may be further divided into: the house source broker forwards friends, the house buyer forwards friends and the owner forwards friends.

On the basis, a plurality of user behavior records of the published house source information are classified according to the user roles of the users from which the user behaviors are derived and the user behaviors, the user behavior records of the same user behaviors under the same user roles are classified into one class, the number of the user behavior records corresponding to each user behavior under each user role is obtained through corresponding statistics, and then, the behavior density parameter corresponding to each user behavior under each user role is obtained through calculation according to the publishing duration or exposure of the published house source information.

The second adjustment factor is an adjustment factor calculated according to the user behavior density parameter. In some embodiments of the present application, a second mapping relationship between the behavior density parameter of each user behavior under each user role and the second adjustment factor of the corresponding score item may be preset, and on this basis, after determining the behavior density parameter of the user behavior under one user role, the second adjustment factor of the score item associated with the user role and the user behavior is determined according to the corresponding second mapping relationship.

Since the behavior density parameter reflects the density of the user behavior triggered by the published house source information, it can be understood that, if the density of a user behavior or a class of user behaviors is higher, it indicates that the attention of the user to the target house source indicated by the published house source information is higher, and thus, the quality or the popularity of the target house source is reflected on the side. Therefore, in some embodiments of the present application, the second adjustment factor is positively correlated to the corresponding behavior density parameter, and the larger the behavior density parameter is, the larger the corresponding second adjustment factor is.

And step 240, obtaining a dynamic score of the target house source indicated by the published house source information according to the first adjusting factor and the second adjusting factor of each scoring item and the basic score corresponding to each scoring item.

The basic score may be a score initially set according to an empirical value, or may be determined by training and tuning positive and negative feedback of the sample on the basis of the initially set score.

The dynamic scoring refers to scoring obtained by calculation according to the user behavior record of the released house source information corresponding to the house source. It can be understood that the dynamic score is related to the user behavior triggered by the published house source information corresponding to the house source, and as time goes on, the user behavior for the published house source information increases, and accordingly, the above process of step 210 and step 240 needs to be repeated to update and calculate the dynamic score of the target house source corresponding to the published house source information. That is to say, the dynamic score of the published house source information calculated according to the scheme is related to time, accurately reflects the change of the attention degree of the published house source information in the time dimension, and simultaneously reflects the aging value of the published house source information.

In some embodiments of the present application, step 240 may comprise: determining a scoring coefficient of each scoring item according to the first adjusting factor and the second adjusting factor of each scoring item; and performing weighted calculation according to the scoring coefficient of each scoring item and the basic score corresponding to each scoring item to obtain the dynamic score of the target house source indicated by the published house source information.

In some embodiments of the present application, a first adjustment factor corresponding to the scoring item and a second adjustment factor corresponding to the scoring item may be added, and a result obtained by the addition may be used as a scoring coefficient of the scoring item. In another embodiment of the present application, the first adjustment factor and the second adjustment factor may be multiplied, and the obtained result is used as a scoring coefficient of the scoring item.

In the process of weighting calculation, the scoring coefficients of the scoring items are used as weighting coefficients, the basic scoring of all the scoring items is weighted, and the obtained weighting calculation result is the dynamic scoring of the target house source indicated by the published house source information. The weighting calculation may be a weighted sum or a weighted average.

Step 250, calculating to obtain a comprehensive score of the target house source according to the dynamic score of the target house source and the static score of the target house source; the static score is determined according to static information of the target house source.

The static information of the target house source refers to objective description information of the target house source and the periphery of the target house source, and may be information that the geographical position of the house source described in the published house source information, price information, house layout information, house source property certificate number, building information (information such as building height, building matching, building distance, greening, and the like) of the cell where the house source is located, owner information, furniture matching information, matching facility information (for example, shopping mall, hospital, school, stadium, museum, subway station, bus station, and the like) around the house source, property information (for example, property company) corresponding to the house source, and the like, are basically unchanged. The foregoing is, of course, merely exemplary and is not to be construed as limiting the scope of the invention.

In some embodiments of the present application, a static scoring rule may be preset, and then the static scoring of the target house source may be calculated by combining with the static information of the target house source.

In some embodiments of the present application, the static score of the target house source may be calculated as follows: acquiring static information of the target house source, wherein the static information comprises at least one of basic information of the target house source and peripheral supporting facility information of the target house source; and determining the static score of the target house source according to the static information of the target house source and a preset static scoring rule.

The basic information of the target house source may include the geographical location of the listed house source, price information (e.g., unit price), house layout information (e.g., house layout, house area, etc.), house property certificate number of the house source, building information (e.g., building height, building matching, building distance, greening, etc.) of a cell in which the house source is located, owner information, furniture matching information, property information corresponding to the house source, etc.

The information of the peripheral supporting facilities of the target house source includes information of a mall, a hospital, a school, a stadium, a museum, a subway station, a bus station, etc. around the target house source, and a distance between the supporting facilities and the target house source.

In some embodiments of the present application, the static information of the target house source may further include house source heat rate information in the cell where the target house source is located, which may be a volume of the house source in the cell where the target house source is located within a unit time (for example, one month), or a historical volume of the deals, and the like.

The preset static scoring rule refers to a scoring rule set for static scoring. In some embodiments of the present application, the preset static scoring rules may include scoring rules for a plurality of static scoring items. The static scoring items comprise price scoring items, house layout scoring items, district environment scoring items, property scoring items, peripheral supporting facility scoring items and the like. On the basis, according to the static information of the target house source and the scoring rules under a plurality of static scoring items, the score of the target house source under each static scoring item can be determined, and the static score of the target house source can be correspondingly determined by integrating the scores of the target house source under each static scoring item.

After obtaining the dynamic score of the target house source and the static score of the target house source, calculating the composite score of the target house source according to the set mapping relationship between the composite score and the dynamic score and the static score, for example, adding the static score and the dynamic score, in other embodiments, determining the composite score of the target house source by combining the dynamic score and the static score in other manners.

And step 260, processing the published house source information according to the comprehensive score of the target house source.

In some embodiments of the present application, the pushing of the published house source information may be performed according to the composite score of the target house source. Step 260 further comprises: carrying out house source screening according to the comprehensive scores of all house sources in the house source set, and determining house sources to be pushed; and pushing the published house source information of the house source to be pushed.

The house sources in the set of house sources are candidate push house sources. The house source screening can be house source sorting and screening, and can also be house source screening according to a set score threshold value. In the process of screening according to the house source sorting, firstly, sorting the house sources in the house source set according to the sequence of the comprehensive scores from high to low, and setting a number of house sources in the front of the screening sorting as the house sources to be pushed. And the house source with the comprehensive score larger than the set score threshold value can be used as the house source to be pushed. The number of the screened room sources to be pushed can be one or more.

And the comprehensive score of the target house source is calculated by combining the static information and the dynamic user behavior records in the time dimension, although the comprehensive score is constrained by the user behavior records, because the user behavior records are continuously increased, the influence of each user behavior record on the comprehensive score changes along with the change of time, which is equivalent to calculating the comprehensive score of the target house source by adopting a Bayesian probability superposition mode, different user behavior records have independence, and different user behavior records can be mutually verified, even if defect data exists in the process of calculating the comprehensive score, the influence of the defect data on the comprehensive score can be weakened according to the newly increased user behavior records, so that the accuracy of the calculated comprehensive score can be ensured on the basis of the existence of the defect data. On the basis, the published house source information is processed according to the comprehensive score with high accuracy and high reliability, and the reliability and the accuracy of the processing result of the published house source information can be ensured.

In some embodiments of the present application, the scoring term comprises a first scoring term; the user behavior comprises information propagation behavior attributed to a propagation type; in this embodiment, before step 240, as shown in fig. 3, the method further includes:

step 310, acquiring propagation weight information and behavior density parameters of information propagation behaviors triggered by users of each user role; the propagation weight information indicates a propagation weight associated with each user role and each information propagation behavior.

The propagation weight refers to a weight set for the information propagation behavior. The propagation weight is used for representing the contribution degree of the corresponding information propagation behavior to the propagation of the published house source information. In this embodiment, since there is a difference in the degree of contribution of the information propagation behavior of the users of different roles to the propagation of the published house source information, the propagation weight is set in combination with the user role and the information propagation behavior, that is, the propagation weight is associated with both the user role and the information propagation behavior.

The information dissemination behavior may include forwarding behavior (e.g., forwarding circles of friends, forwarding groups, forwarding other social platforms, etc.), commenting on published house source information, and so on.

And step 320, performing weighted calculation according to the propagation weight associated with each user role and each information propagation behavior and the behavior density parameter of each information propagation behavior triggered by the user of each user role to obtain the behavior density parameter corresponding to the propagation type.

In the embodiment of the present application, the behavior density parameter is weighted according to the information propagation behavior of the propagation type. And taking the propagation weight associated with each user role and each information propagation behavior as a weighting coefficient, and weighting the behavior density parameters of the information propagation behaviors triggered by the users of each user role.

Step 330, determining a second adjustment factor of the first scoring item according to the behavior density parameter corresponding to the propagation type.

In some embodiments of the present application, a mapping relationship between the behavior density parameter corresponding to the propagation type and the second adjustment factor may be preset, so that, after determining the behavior density parameter corresponding to the propagation type (for convenience of description, referred to as a first target behavior density parameter), the second adjustment factor associated with the first target behavior density parameter is used as the second adjustment factor of the first score item.

For example, if the propagation weights corresponding to each user role and each forwarding behavior, and the calculated behavior density parameter are as shown in table 1 below.

TABLE 1

User roles	Forwarding behavior	Propagation weights	Behavioral Density parameter
				House resource broker	Forwarding friends	K1	L1
House buyer	Forwarding friend circle	K2	L2
				House resource broker	Forwarding friend circle	K3	L3
House buyer	Forwarding groups	K4	L4

Then, according to step 320, the behavior density parameter corresponding to the propagation type K1 × L1+ K2 × L2+ K3 × L3+ K4 × L4 can be calculated.

In the scheme in this embodiment, it is equivalent to integrating the behavior density parameters related to the information propagation behavior to obtain parameters that integrally reflect the density of all the information propagation behaviors, that is, the behavior density parameters corresponding to the propagation type; compared with the method that the second adjusting factor is respectively determined for each information propagation behavior, the second adjusting factor of the first scoring item is determined based on the behavior density parameter corresponding to the propagation type, and the data processing amount is reduced.

In some embodiments of the present application, the scoring term comprises a second scoring term; the user behavior comprises an information maintenance behavior attributed to an information maintenance type; as shown in fig. 4, before step 240, the method further includes:

step 410, obtaining maintenance weight information, and obtaining behavior density parameters of each information maintenance behavior triggered by the user of each user role; the maintenance weight information indicates a maintenance weight associated with each user role and each information maintenance action.

The information maintenance behavior refers to a behavior of maintaining the published house source information, such as editing the published house source information (uploading house source video, house source pictures, modifying house source description, modifying house source unit price, and the like), making a call to an owner, making a call to a house source broker, and the like.

The maintenance weight is a weight set for the information maintenance action. The maintenance weight is used for representing the contribution degree of the corresponding information maintenance behavior to the attention degree of the published house source information. Because the information maintenance behaviors of users with different roles also have different contribution degrees to the attention degree of the published house source information, the maintenance weight is set in combination with the user role and the information maintenance behavior, namely the maintenance weight is associated with the user role and the information maintenance behavior at the same time.

And step 420, performing weighted calculation according to the maintenance weight associated with each user role and each information maintenance behavior and the behavior density parameter of each information maintenance behavior triggered by the user of each user role to obtain the behavior density parameter corresponding to the information maintenance type.

The weighting calculation performed in step 420 may refer to the process of step 320 in the above embodiment, and is not described herein again.

And 430, determining a second adjustment factor of the second scoring item according to the behavior density parameter corresponding to the information maintenance type.

In some embodiments of the present application, a mapping relationship between the behavior density parameter corresponding to the information maintenance type and the second adjustment factor may be preset, so that, after determining the behavior density parameter corresponding to the information maintenance type (for convenience of description, referred to as a second target behavior density parameter), the second adjustment factor associated with the second target behavior density parameter is used as the second adjustment factor of the second score item.

In the solution in this embodiment, it is equivalent to integrating the behavior density parameters related to the information maintenance behaviors, and obtaining a parameter that integrally reflects the behavior density of all the information maintenance behaviors, that is, a behavior density parameter corresponding to the information maintenance type. Compared with the method that the second adjusting factor is respectively determined for each information maintenance action, the second adjusting factor of the second scoring item is determined based on the action density parameter corresponding to the maintenance type, and the data processing amount is reduced.

In some embodiments of the present application, the scoring term comprises a third scoring term; the user behavior comprises an access behavior attributed to an access type; as shown in fig. 5, before step 240, the method further includes:

step 510, obtaining access weight information, and obtaining behavior density parameters of each access behavior triggered by a user of each user role; the access weight information indicates an access weight associated with each user role and each access behavior.

The access weight is used for representing the contribution degree of the corresponding information propagation behavior to the attention degree of the published house source information, and the value of the target house source indicated by the published house source information can be reflected from the side face. In this embodiment, since there is a difference in the degree of contribution of the access behaviors of the users with different roles to the attention of the published house source information, the access weight is set in combination with the user role and the access behavior, that is, the access weight is associated with both the user role and the access behavior.

The access behavior may be an access behavior for published house source information, that is, a behavior of browsing published house source information, or may be a house-viewing behavior, for example, if a control for reserving house-viewing or a control for house-viewing confirmation is provided in an interface of published house source information, whether the house-viewing behavior exists may be determined according to a triggered condition of the control for reserving house-viewing or the control for house-viewing confirmation. Specifically, the access behavior includes, for example, an access behavior of the premise broker, an active access behavior of a house buyer, and an access behavior after a passive access of the house buyer, where the passive access of the house buyer may be a behavior of accessing published house source information through a shared link, or a house-watching behavior recommended by the premise broker to watch a house. In a specific embodiment, the calculation of the behavior density parameter corresponding to each access behavior may be calculated by counting the number of visitors or the number of visitors.

And step 520, performing weighted calculation according to the access weight associated with each user role and each access behavior and the behavior density parameter of each access behavior triggered by the user of each user role to obtain the behavior density parameter corresponding to the access type. The weighting calculation performed in step 520 may refer to the process of step 320 in the above embodiment, and is not described herein again.

Step 530, determining a second adjustment factor of the third scoring item according to the behavior density parameter corresponding to the access type.

In some embodiments of the present application, a mapping relationship between the behavior density parameter corresponding to the access type and the second adjustment factor may be preset, so that, after determining the behavior density parameter corresponding to the access type (referred to as a third target behavior density parameter for convenience of description), the second adjustment factor associated with the third target behavior density parameter is used as the second adjustment factor of the third score item.

In the solution in this embodiment, it is equivalent to integrating the behavior density parameters related to the access behaviors, and obtaining a parameter that integrally reflects the behavior density of all the access behaviors, that is, a behavior density parameter corresponding to the access type. Compared with the method that the second adjusting factor is respectively determined for each access behavior, the second adjusting factor of the third scoring item is determined based on the behavior density parameter corresponding to the access type, and the data processing amount is reduced.

In the embodiments corresponding to fig. 3 to fig. 5, the user behaviors are classified, and the corresponding classifications include an information propagation behavior, an information maintenance behavior, and an access behavior, in other embodiments, the user behaviors may also be classified according to other classification principles, and then the second adjustment factor and the first adjustment factor of the score item corresponding to each type of user behavior are calculated correspondingly, for example, the information propagation behavior and the access behavior may be further divided more finely. Therefore, the classification of the user behavior in the embodiments corresponding to fig. 3 to 5 cannot be regarded as a limitation to the scope of the application.

In some embodiments of the present application, prior to step 250, as shown in fig. 6, the method further comprises:

step 610, obtaining price information of a reference house source corresponding to the target house source, where the reference house source corresponding to the target house source includes other house sources in the cell where the target house source is located and house sources in other cells that belong to similar types to the target house source.

In some embodiments of the present application, for the determination of the house sources in other cells that belong to the same type as the target house source, a distance range may be set, that is, the house sources of similar types in the cell whose distance from the cell where the target house source is located does not exceed the set distance threshold may be used as the reference house source corresponding to the target house source.

In some embodiments of the present application, assets of a similar type as the target asset may be determined from asset tags, such as house type tags, floor tags, orientation tags, floor age tags, academic position room tags, and the like, in one or more dimensions.

If all the house sources are tags in one dimension, two house sources with the same house source tag can be regarded as house sources of similar types. And if the house source labels comprise labels in at least two dimensions, determining two house sources of which the number of the same house source labels exceeds a set threshold value as house sources of similar types. The reference house source corresponding to the target house source can be one or more.

And step 620, determining a static adjustment factor according to the price information of the reference house source corresponding to the target house source and the price information of the target house source.

In some embodiments of the present application, the price information in step 610 may include unit price information, such as unit price per square meter. And then determining a static adjusting factor according to the unit price of the reference house source corresponding to the target house source and the unit price of the target house source.

In some embodiments of the present application, a unit price difference calculation may be performed for each of the target source and the reference source of the target source, and a static adjustment factor may be determined based on the unit price difference.

In some embodiments, the mapping relationship between the unit price difference value and the static adjustment factor is preset, so that after the unit price difference value between the target house source and the reference house source is determined, the static adjustment factor corresponding to the unit price difference value is determined according to the mapping relationship between the target house source and the reference house source. In some embodiments, in the case that the unit price difference is the unit price of the reference house source-the unit price of the target house source, the unit price difference is positively correlated with the static adjustment factor, and the static adjustment factor is larger when the unit price of the target house source is lower than the unit price of the reference house source.

Step 630, adjusting the static score of the target house source according to the static adjustment factor.

In some embodiments of the present application, in a case that a reference house of a target house is multiple, an average unit price in a cell where the target house is located (referred to as a first average unit price for convenience of description) and an average unit price of houses belonging to the same type as the target house in other cells (referred to as a second average unit price for convenience of description) may be calculated first, then a first unit price difference between the first average unit price and the unit price of the target house, a second unit price difference between the second average unit price and the unit price of the target house are determined, and a static adjustment factor corresponding to the first unit price difference and a static adjustment factor corresponding to the second unit price difference are determined; on the basis, the static adjustment factor corresponding to the first unit price difference value and the static adjustment factor corresponding to the second unit price difference value are determined to be calculated to obtain a total static adjustment factor, for example, the result of adding or multiplying the two static adjustment factors is used as the total static adjustment factor, and then the static score of the target house source is adjusted according to the total static adjustment factor.

In other embodiments, the static score of the target house source may be adjusted according to the static adjustment factor corresponding to the first unit price difference and the static adjustment factor corresponding to the second unit price difference.

In some embodiments of the present application, after step 250, the method further comprises: and determining the expected transaction period of the target house source according to the comprehensive score of the target house source.

In the scheme, the comprehensive score of the target house source is combined with the dynamic score and the static score, the dynamic score of the target house source reflects the attention heat degree of the target house source to a certain extent, the static score of the target house source reflects the objective evaluation of the target house source, and the attention heat degree of the house source and the objective evaluation of the house source are important factors influencing the transaction period of the house source, so that the obtained comprehensive score can reflect the transaction period of the house source to a certain extent by combining the dynamic score and the static score. In view of this, the expected performance period of the target property may be determined by the composite score of the target property.

In some embodiments of the present application, a mapping relationship between the composite score and the expected transaction period may be set, for example, the composite score is set to be within a first score range, and the corresponding expected transaction period is within one week; and setting the comprehensive score to be within a second score range, wherein the corresponding expected transaction period is within one month, and the like, wherein the comprehensive score in the first score range is higher than the comprehensive score in the second score range.

In some embodiments of the present application, the pushing of the published house source information may also be performed according to the expected transaction period of the determined target house source, for example, the published house source information with a shorter expected transaction period is preferentially pushed.

In some embodiments of the present application, prior to step 260, the method further comprises: acquiring house source black swan event information; and if the house source black swan event information is related to the target house source, adjusting the comprehensive score of the target house source according to the black swan coefficient corresponding to the house source black swan event information.

The house source black swan event information is used for indicating black swan events related to house sources, and the black swan events are events which are extremely unlikely to occur but actually occur. The black swan events related to house resources, such as the withdrawal of entrustment of owners, the change of house purchasing policy (e.g. house purchasing restriction, etc.), the change of market conditions (e.g. the house resources restricted from being sold on a certain floor, etc.), are, of course, the above are only exemplary examples, and other unexpected emergencies that may affect the house resource transaction may also be regarded as the black swan events related to house resources.

In some embodiments of the present application, the black swan coefficient may be multiplied by the composite score of the target house source to obtain the adjusted composite score of the target house source. The black swan coefficient corresponding to the house source black swan event information can be preset or determined after further adjustment on the basis of the preset.

In the scheme of this embodiment, the comprehensive score of the related target house source is adjusted in time according to the house source black swan event information, so that the published house source information of the target house source can be processed in time according to the comprehensive score of the house source, for example, if the comprehensive score of the target house source is lower than a set threshold value after adjustment according to the black swan coefficient, the published house source information can be cancelled in time.

The following describes embodiments of the apparatus of the present application, which can be used to execute the method for pushing a house source in the above embodiments of the present application. For details that are not disclosed in the embodiments of the apparatus of the present application, please refer to the embodiments of the house source pushing method described above in the present application.

Fig. 7 shows a block diagram of a processing device of house source information according to an embodiment of the present application. Referring to fig. 7, a processing apparatus of house source information according to an embodiment of the present application includes: a user behavior record obtaining module 710, configured to obtain a plurality of user behavior records for the published house source information; the user behavior record indicates the user behavior triggered by the published house source information and the corresponding trigger time; a user behavior record sequence determining module 720, configured to sequence the plurality of user behavior records according to a sequence from first to last of the trigger time to obtain a user behavior record sequence, where the user behavior record sequence is used to determine a first adjustment factor of a score item corresponding to each user behavior record; a behavior density parameter calculation module 730, configured to calculate, according to the multiple user behavior records and the user roles to which the users from which the user behavior records belong, a behavior density parameter of each user behavior triggered by the user of each user role; the behavior density parameter is used for determining a second adjustment factor of the scoring item corresponding to each user behavior record; the dynamic score calculating module 740 is configured to obtain a dynamic score of a target house source indicated by the published house source information according to the first adjustment factor and the second adjustment factor of each scoring item and a basic score corresponding to each scoring item; a comprehensive score determining module 750, configured to calculate a comprehensive score of the target room source according to the dynamic score of the target room source and the static score of the target room source; the static score is determined according to the static information of the target house source; and the processing module 760 is configured to process the published house source information according to the comprehensive score of the target house source.

In some embodiments of the present application, the processing device of the house source information further includes: the scoring item determining module is used for determining a scoring item corresponding to the user behavior record according to the user behavior indicated by the user behavior record and the user role to which the user from which the user behavior record belongs, wherein the scoring item is related to the user behavior and the user role to which the user belongs; the user roles include house broker, owner and house buyer.

In some embodiments of the present application, the scoring term comprises a first scoring term; the user behavior comprises information propagation behavior attributed to a propagation type; the processing device of the house source information further comprises: the propagation weight information acquisition module is used for acquiring propagation weight information and acquiring behavior density parameters of information propagation behaviors triggered by users of each user role; the propagation weight information indicates a propagation weight associated with each user role and each information propagation behavior; the first behavior density parameter determining module is used for carrying out weighting calculation according to the propagation weight associated with each user role and each information propagation behavior and the behavior density parameter of each information propagation behavior triggered by the user of each user role to obtain the behavior density parameter corresponding to the propagation type; and the first determining module is used for determining a second adjusting factor of the first scoring item according to the behavior density parameter corresponding to the propagation type.

In some embodiments of the present application, the scoring term comprises a second scoring term; the user behavior comprises an information maintenance behavior attributed to an information maintenance type; the processing device of the house source information further comprises: the maintenance weight information acquisition module is used for acquiring maintenance weight information and acquiring behavior density parameters of information maintenance behaviors triggered by the user of each user role; the maintenance weight information indicates a maintenance weight associated with each user role and each information maintenance action; the second behavior density parameter determining module is used for performing weighted calculation according to the maintenance weight associated with each user role and each information maintenance behavior and the behavior density parameter of each information maintenance behavior triggered by the user of each user role to obtain the behavior density parameter corresponding to the information maintenance type; and the second determining module is used for determining a second adjusting factor of the second scoring item according to the behavior density parameter corresponding to the information maintenance type.

In some embodiments of the present application, the scoring term comprises a third scoring term; the user behavior comprises an access behavior attributed to an access type; the processing device of the house source information further comprises: the access weight information acquisition module is used for acquiring access weight information and acquiring behavior density parameters of each access behavior triggered by the user of each user role; the access weight information indicates an access weight associated with each user role and each access behavior; the third behavior density parameter determining module is used for performing weighted calculation according to the access weight associated with each user role and each access behavior and the behavior density parameter of each access behavior triggered by the user of each user role to obtain the behavior density parameter corresponding to the access type; and the third determining module is used for determining a second adjusting factor of the third scoring item according to the behavior density parameter corresponding to the access type.

In some embodiments of the present application, the second adjustment factor is positively correlated to the corresponding behavior density parameter.

In some embodiments of the present application, the processing device of the house source information further includes: the adjustment strategy information acquisition module is used for acquiring adjustment strategy information, the adjustment strategy information comprises adjustment strategies corresponding to all scoring items, and the adjustment strategies indicate the reference user behavior record sequence segments of the corresponding scoring items and corresponding adjustment factors; a sequence segment matching module, configured to perform sequence segment matching in the user behavior record sequence according to a reference user behavior record sequence segment in the adjustment policy; and the first adjusting factor determining module is used for determining the adjusting factor matched to the source adjusting strategy of the reference user behavior record sequence segment as the first adjusting factor of the scoring item indicated by the adjusting strategy if the reference user behavior record sequence segment is matched in the user behavior record sequence.

In some embodiments of the present application, the processing device of the house source information further includes: a static information obtaining module, configured to obtain static information of the target room source, where the static information includes at least one of basic information of the target room source and peripheral supporting facility information of the target room source; and the static scoring determination module is used for determining the static scoring of the target house source according to the static information of the target house source and a preset static scoring rule.

In some embodiments of the present application, the processing device of the house source information further includes: a price information obtaining module, configured to obtain price information of a reference house source corresponding to the target house source, where the reference house source corresponding to the target house source includes other house sources in a cell where the target house source is located and house sources in other cells that are similar to the target house source in type; the static adjusting factor determining module is used for determining a static adjusting factor according to the price information of the reference house source corresponding to the target house source and the price information of the target house source; and the static scoring adjusting module is used for adjusting the static scoring of the target house source according to the static adjusting factor.

In some embodiments of the present application, the processing device of the house source information further includes: the event information acquisition module is used for acquiring house source black swan event information; and the comprehensive score adjusting module is used for adjusting the comprehensive score of the target house source according to the black swan coefficient corresponding to the house source black swan event information if the house source black swan event information is related to the target house source.

In some embodiments of the present application, the processing device of the house source information further includes: and the expected transaction period determining module is used for determining the expected transaction period of the target house source according to the comprehensive score of the target house source.

In some embodiments of the present application, the processing module comprises: the system comprises a room source to be pushed determining unit, a room source collecting unit and a room source selecting unit, wherein the room source to be pushed determining unit is used for carrying out room source screening according to comprehensive scores of all room sources in a room source set and determining the room sources to be pushed; and the pushing unit is used for pushing the published house source information of the house source to be pushed.

It should be noted that the computer system 800 of the electronic device shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.

As shown in fig. 8, a computer system 800 includes a Central Processing Unit (CPU)801, which can perform various appropriate actions and processes, such as performing the methods in the above-described embodiments, according to a program stored in a Read-Only Memory (ROM) 802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data necessary for system operation are also stored. The CPU801, ROM802, and RAM 803 are connected to each other via a bus 804. An Input/Output (I/O) interface 805 is also connected to bus 804.

The following components are connected to the I/O interface 805: an input portion 806 including a keyboard, a mouse, and the like; an output section 807 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage portion 808 including a hard disk and the like; and a communication section 809 including a Network interface card such as a LAN (Local Area Network) card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. A drive 810 is also connected to the I/O interface 805 as necessary. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as necessary, so that a computer program read out therefrom is mounted on the storage section 808 as necessary.

In particular, according to embodiments of the application, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 809 and/or installed from the removable medium 811. When the computer program is executed by the Central Processing Unit (CPU)801, various functions defined in the system of the present application are executed.

It should be noted that the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM), a flash Memory, an optical fiber, a portable Compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.

As another aspect, the present application also provides a computer-readable storage medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable storage medium carries computer readable instructions which, when executed by a processor, implement the method of any of the embodiments described above.

According to an aspect of the present application, there is also provided an electronic device, including: a processor; a memory having computer readable instructions stored thereon which, when executed by the processor, implement the method of any of the above embodiments.

According to an aspect of an embodiment of the present application, there is provided a computer program product or a computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the method of any of the above embodiments.

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present application.

Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains.

It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims

1. A method for processing house source information is characterized by comprising the following steps:

acquiring a plurality of user behavior records aiming at published house source information; the user behavior record indicates the user behavior triggered by the published house source information and the corresponding trigger time;

sequencing the plurality of user behavior records according to the sequence of the trigger time from first to last to obtain a user behavior record sequence, wherein the user behavior record sequence is used for determining a first adjustment factor of a scoring item corresponding to each user behavior record;

calculating the behavior density parameter of each user behavior triggered by the user of each user role according to the user behavior records and the user roles to which the user from which the user behavior records belong; the behavior density parameter is used for determining a second adjustment factor of the scoring item corresponding to each user behavior record;

obtaining dynamic scores of target house resources indicated by the published house resource information according to the first adjusting factor and the second adjusting factor of each scoring item and the basic scores corresponding to each scoring item;

calculating to obtain a comprehensive score of the target house source according to the dynamic score of the target house source and the static score of the target house source; the static score is determined according to the static information of the target house source;

and processing the published house source information according to the comprehensive score of the target house source.

2. The method according to claim 1, wherein before obtaining the dynamic score of the target room source indicated by the published room source information according to the first adjustment factor and the second adjustment factor of each scoring item and the basic score corresponding to each scoring item, the method further comprises:

determining a scoring item corresponding to the user behavior record according to the user behavior indicated by the user behavior record and the user role to which the user from which the user behavior record belongs, wherein the scoring item is related to the user behavior and the user role to which the user belongs; the user roles include house broker, owner and house buyer.

3. The method of claim 1, wherein the scoring term comprises a first scoring term; the user behavior comprises information propagation behavior attributed to a propagation type;

before obtaining the dynamic score of the target house source indicated by the published house source information according to the first adjustment factor and the second adjustment factor of each scoring item and the basic score corresponding to each scoring item, the method further includes:

acquiring propagation weight information and behavior density parameters of information propagation behaviors triggered by users of each user role; the propagation weight information indicates a propagation weight associated with each user role and each information propagation behavior;

carrying out weighted calculation according to the propagation weight associated with each user role and each information propagation behavior and the behavior density parameter of each information propagation behavior triggered by the user of each user role to obtain the behavior density parameter corresponding to the propagation type;

and determining a second adjusting factor of the first scoring item according to the behavior density parameter corresponding to the propagation type.

4. The method of claim 1, wherein the scoring term comprises a second scoring term; the user behavior comprises an information maintenance behavior attributed to an information maintenance type;

obtaining maintenance weight information and behavior density parameters of information maintenance behaviors triggered by users of each user role; the maintenance weight information indicates a maintenance weight associated with each user role and each information maintenance action;

performing weighted calculation according to the maintenance weight associated with each user role and each information maintenance action and the action density parameters of each information maintenance action triggered by the user of each user role to obtain the action density parameters corresponding to the information maintenance type;

and determining a second adjusting factor of the second scoring item according to the behavior density parameter corresponding to the information maintenance type.

5. The method of claim 1, wherein the scoring term comprises a third scoring term; the user behavior comprises an access behavior attributed to an access type;

acquiring access weight information and acquiring behavior density parameters of each access behavior triggered by a user of each user role; the access weight information indicates an access weight associated with each user role and each access behavior;

carrying out weighted calculation according to the access weight associated with each user role and each access behavior and the behavior density parameter of each access behavior triggered by the user of each user role to obtain the behavior density parameter corresponding to the access type;

and determining a second adjusting factor of the third scoring item according to the behavior density parameter corresponding to the access type.

6. The method of any one of claims 1-5, wherein the second adjustment factor is positively correlated to the corresponding behavior density parameter.

7. The method according to claim 1, wherein before obtaining the dynamic score of the target room source indicated by the published room source information according to the first adjustment factor and the second adjustment factor of each scoring item and the basic score corresponding to each scoring item, the method further comprises:

acquiring adjustment strategy information, wherein the adjustment strategy information comprises adjustment strategies corresponding to all scoring items, and the adjustment strategies indicate the reference user behavior record sequence segments of the corresponding scoring items and corresponding adjustment factors;

according to the reference user behavior record sequence segment in the adjustment strategy, sequence segment matching is carried out in the user behavior record sequence;

and if the reference user behavior record sequence segment is matched in the user behavior record sequence, determining the adjustment factor in the adjustment strategy from which the reference user behavior record sequence segment is matched as a first adjustment factor of the scoring item indicated by the adjustment strategy.

8. The method of claim 1, wherein before calculating the composite score of the target origin according to the dynamic score of the target origin and the static score of the target origin, the method further comprises:

acquiring static information of the target house source, wherein the static information comprises at least one of basic information of the target house source and peripheral supporting facility information of the target house source;

and determining the static score of the target house source according to the static information of the target house source and a preset static scoring rule.

9. The method according to claim 1 or 8, wherein before calculating the composite score of the target house source according to the dynamic score of the target house source and the static score of the target house source, the method further comprises:

acquiring price information of a reference house source corresponding to the target house source, wherein the reference house source corresponding to the target house source comprises other house sources in a cell where the target house source is located and house sources which belong to similar types with the target house source in other cells;

determining a static adjusting factor according to the price information of the reference house source corresponding to the target house source and the price information of the target house source;

and adjusting the static score of the target house source according to the static adjusting factor.

10. The method of claim 1, wherein before processing the published source information according to the composite score of the target source, the method further comprises:

acquiring house source black swan event information;

and if the house source black swan event information is related to the target house source, adjusting the comprehensive score of the target house source according to the black swan coefficient corresponding to the house source black swan event information.

11. The method of claim 1, wherein after calculating the composite score of the target origin according to the dynamic score of the target origin and the static score of the target origin, the method further comprises:

and determining the expected transaction period of the target house source according to the comprehensive score of the target house source.

12. The method according to claim 1, wherein the processing the published house source information according to the composite score of the target house source comprises:

carrying out house source screening according to the comprehensive scores of all house sources in the house source set, and determining house sources to be pushed;

and pushing the published house source information of the house source to be pushed.

13. A device for processing house source information, comprising:

the user behavior record acquisition module is used for acquiring a plurality of user behavior records aiming at the published house source information; the user behavior record indicates the user behavior triggered by the published house source information and the corresponding trigger time;

the user behavior record sequence determining module is used for sequencing the plurality of user behavior records according to the sequence of the trigger time from first to last to obtain a user behavior record sequence, and the user behavior record sequence is used for determining a first adjusting factor of a scoring item corresponding to each user behavior record;

the behavior density parameter calculation module is used for calculating the behavior density parameters of the user behaviors triggered by the user of each user role according to the user behavior records and the user roles to which the user from which the user behavior records belong; the behavior density parameter is used for determining a second adjustment factor of the scoring item corresponding to each user behavior record;

the dynamic score calculation module is used for obtaining the dynamic score of the target house source indicated by the published house source information according to the first adjustment factor and the second adjustment factor of each scoring item and the basic score corresponding to each scoring item;

the comprehensive score determining module is used for calculating and obtaining the comprehensive score of the target house source according to the dynamic score of the target house source and the static score of the target house source; the static score is determined according to the static information of the target house source;

and the processing module is used for processing the published house source information according to the comprehensive score of the target house source.

14. An electronic device, comprising:

a processor;

a memory having computer-readable instructions stored thereon which, when executed by the processor, implement the method of any of claims 1-12.

15. A computer readable storage medium having computer readable instructions stored thereon which, when executed by a processor, implement the method of any one of claims 1-12.