CN108734393A - Matching process, user equipment, storage medium and the device of information of real estate - Google Patents
Matching process, user equipment, storage medium and the device of information of real estate Download PDFInfo
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Abstract
The invention discloses the matching process of information of real estate, user equipment, storage medium and devices.Self-built housing source information and third party's information of real estate are obtained in the present invention, it is other that self-built Attribute class is extracted from self-built information of real estate, the first attributes match degree between self-built information of real estate and third party's information of real estate is not calculated based on each self-built Attribute class, judge the first attributes match degree whether in the first matching degree section, when the first attributes match degree is in the first matching degree section, attribute data corresponding with self-built attribute classification in self-built information of real estate is regarded as into unreliable attribute data.The first attributes match degree is set in the present invention to filter out unreliable attribute data from self-built information of real estate, so that business personnel can directly audit unreliable attribute data, reduce the data volume for waiting for manual examination and verification, review efficiency is improved, also just solves the technical problem that review efficiency is relatively low existing for existing information of real estate audit mode.
Description
Technical field
The present invention relates to the matching process of data processing field more particularly to information of real estate, user equipment, storage medium and
Device.
Background technology
As more and more house property medium companies are active in real estate as the go-between of real estate's sales and house lease
Field, house property medium company in order to preferably provide with the relevant intermediary sevices of house property, need to grasp as much as possible complete and accurate
True information of real estate, wherein information of real estate includes cell name, cell longitude and latitude, source of houses picture, source of houses configuration, source of houses price
And developer's information etc..
However, the scale of construction due to information of real estate is larger, need to consume larger financial resources in the collection link of information of real estate
And human cost, in addition to house property medium company itself carry out on the spot other than adopt work to obtain outside self-built housing source information, more meetings
Introducing third party's information of real estate, will be in combination with the self-built source of houses to overcome the insufficient defect of information content existing for self-built information of real estate
Information is supported with third party's information of real estate to provide data for house property medium company.
But third party's information of real estate comes from various channels, source is more and hard to tell whether it is true or false, for house property medium company
Speech, third party's information of real estate is due to the more difficult direct use there are certain mistake, and self-built information of real estate is due to by the spot
The mode adopted outside is obtained has higher confidence level compared with third party's information of real estate, so, in order to ensure the accurate of information of real estate
Degree will proofread all informations of real estate grasped by way of manual examination and verification.But judged in a manner of manual examination and verification
Apparent falsehood existing for difference and the two between self-built information of real estate and third party's information of real estate, in review efficiency and accurately
All there is a problem of on degree larger.
So, it is believed that there are the relatively low technical problems of review efficiency for existing information of real estate audit mode.
The above is only used to facilitate the understanding of the technical scheme, and is not represented and is recognized that the above is existing skill
Art.
Invention content
The main purpose of the present invention is to provide the matching process of information of real estate, user equipment, storage medium and device, purports
Solving the technical problem that review efficiency is relatively low existing for existing information of real estate audit mode.
To achieve the above object, the present invention provides a kind of matching process of information of real estate, the match party of the information of real estate
Method includes the following steps：
Obtain self-built housing source information and third party's information of real estate；
It is other that self-built Attribute class is extracted from the self-built information of real estate, the self-built attribute classification is the self-built source of houses letter
The attribute classification of each attribute data in breath；
First between the self-built information of real estate and third party's information of real estate is not calculated based on each self-built Attribute class
Attributes match degree；
The first attributes match degree is judged whether in the first matching degree section, at the first attributes match degree
When in first matching degree section, by attribute data corresponding with the self-built attribute classification in the self-built information of real estate
Regard as unreliable attribute data.
Preferably, described that the self-built information of real estate and third party's information of real estate are not calculated based on each self-built Attribute class
Between the first attributes match degree, including：
It is not right respectively with each self-built Attribute class between the self-built information of real estate and third party's information of real estate to calculate
Each objective attribute target attribute matching degree answered；
Determine default weight coefficient not corresponding with each self-built Attribute class, and based on the default weight coefficient to the mesh
Mark attributes match degree is weighted, to obtain the first attributes match degree.
Preferably, described that the self-built information of real estate and third party's information of real estate are not calculated based on each self-built Attribute class
Between the first attributes match degree, including：
Each self-built Attribute class traversed in the self-built information of real estate is other, and the first attribute is chosen from each self-built Attribute class is not middle
Classification；
The first attribute data corresponding with the first attribute classification is extracted from the self-built information of real estate；
The second attribute data corresponding with the first attribute classification is inquired in third party's information of real estate；
When inquiring the second attribute data corresponding with the first attribute classification from third party's information of real estate,
Calculate the first attributes match degree between first attribute data and second attribute data.
Preferably, the first attribute classification is cell longitude and latitude；
It is described that the second attribute number corresponding with the first attribute classification is being inquired from third party's information of real estate
According to when, calculate the first attributes match degree between first attribute data and second attribute data, including：
When inquiring the second attribute data corresponding with the cell longitude and latitude from third party's information of real estate,
Corresponding longitude and latitude matching degree computation rule is inquired according to the cell longitude and latitude in each matching degree computation rule；
It is calculated between first attribute data and second attribute data based on the longitude and latitude matching degree computation rule
Longitude and latitude difference, and corresponding first attributes match is determined according to the longitude and latitude difference in the first default mapping relations
Degree, the first default mapping relations include the correspondence of longitude and latitude difference and attributes match degree.
Preferably, described that the second attribute corresponding with the first attribute classification is inquired in third party's information of real estate
After data, the matching process of the information of real estate further includes：
The second attribute data corresponding with the first attribute classification is not being inquired from third party's information of real estate
When, it calls and presets map datum API to obtain third attribute data corresponding with the first attribute classification；
Calculate the second attributes match degree between first attribute data and the third attribute data；
When the second attributes match degree is in first matching degree section, by the self-built information of real estate with
The corresponding attribute data of the first attribute classification regards as unreliable attribute data.
Preferably, described that the second attribute corresponding with the first attribute classification is inquired in third party's information of real estate
After data, the matching process of the information of real estate further includes：
The second attribute data corresponding with the first attribute classification is not being inquired from third party's information of real estate
When, corresponding cell ID, inquiry and the cell are determined according to the first attribute classification in the second default mapping relations
Corresponding second attribute classification is identified, the second default mapping relations include the cell ID, the first attribute classification
With the correspondence between the second attribute classification；
The 4th attribute data corresponding with the second attribute classification is inquired in third party's information of real estate；
When inquiring four attribute data corresponding with the second attribute classification from third party's information of real estate,
Calculate the third attributes match degree between first attribute data and the 4th attribute data；
When the third attributes match degree is in first matching degree section, by the self-built information of real estate with
The corresponding attribute data of the first attribute classification regards as unreliable attribute data.
Preferably, the first attribute classification is cell area boundary, and the cell area boundary is by continuous longitude and latitude
The closed polygon that coordinate points are constituted is spent, the second attribute classification is latitude and longitude coordinates point；
Correspondingly, described to be inquired from third party's information of real estate and the second attribute classification the corresponding 4th
When attribute data, the third attributes match degree between first attribute data and the 4th attribute data is calculated, including：
When being inquired from third party's information of real estate with corresponding four attribute data of latitude and longitude coordinates point,
Detect whether the latitude and longitude coordinates point that the 4th attribute data indicates is located at the cell area that first attribute data indicates
On the inside of the boundary on boundary, corresponding third attributes match degree is determined according to testing result.
In addition, to achieve the above object, the present invention also proposes a kind of user equipment, the user equipment include memory,
Processor and the matcher for being stored in the information of real estate that can be run on the memory and on the processor, the source of houses
The matcher of information is arranged for carrying out the step of matching process of information of real estate as described above.
In addition, to achieve the above object, the present invention also proposes a kind of storage medium, and the source of houses is stored on the storage medium
The matcher of the matcher of information, the information of real estate realizes information of real estate as described above when being executed by processor
The step of matching process.
In addition, to achieve the above object, the present invention also proposes a kind of coalignment of information of real estate, the information of real estate
Coalignment includes：Data obtaining module, category determination module, matching degree computing module and data assert module；
Described information acquisition module, for obtaining self-built housing source information and third party's information of real estate；
The category determination module, for other, the self-built category that extracts self-built Attribute class from the self-built information of real estate
Property classification be the self-built information of real estate in each attribute data attribute classification；
The matching degree computing module does not calculate the self-built information of real estate and described the for being based on each self-built Attribute class
The first attributes match degree between tripartite's information of real estate；
The data assert module, for judging the first attributes match degree whether in the first matching degree section,
When the first attributes match degree is in first matching degree section, by the self-built information of real estate with it is described self-built
The corresponding attribute data of attribute classification regards as unreliable attribute data.
Information matches can be carried out to self-built information of real estate and third party's information of real estate in the present invention, to calculate the two
Between matching degree, and set the first attributes match degree to filter out unreliable attribute data from self-built information of real estate so that industry
Business personnel can directly audit unreliable attribute data, than business personnel by way of manual examination and verification directly check and correction
All informations of real estate grasped, this embodiment reduces the data volumes for waiting for manual examination and verification, improve review efficiency, also just solve
The relatively low technical problem of review efficiency existing for existing information of real estate audit mode.
Description of the drawings
Fig. 1 is the user device architecture schematic diagram for the hardware running environment that the embodiment of the present invention is related to；
Fig. 2 is the flow diagram of the matching process first embodiment of information of real estate of the present invention；
Fig. 3 is the flow diagram of the matching process second embodiment of information of real estate of the present invention；
Fig. 4 is the flow diagram of the matching process 3rd embodiment of information of real estate of the present invention；
Fig. 5 is the flow diagram of the matching process fourth embodiment of information of real estate of the present invention；
Fig. 6 is the structure diagram of the coalignment first embodiment of information of real estate of the present invention.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific implementation mode
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
Referring to Fig.1, Fig. 1 is the user device architecture schematic diagram for the hardware running environment that the embodiment of the present invention is related to.
As shown in Figure 1, the user equipment may include：Processor 1001, such as CPU, communication bus 1002, user interface
1003, network interface 1004, memory 1005.Wherein, communication bus 1002 is for realizing the connection communication between these components.
User interface 1003 may include display screen (Display), optional user interface 1003 can also include standard wireline interface,
Wireless interface, the wireline interface for user interface 1003 can be USB interface in the present invention.Network interface 1004 optionally may be used
To include standard wireline interface and wireless interface (such as WI-FI interfaces).Memory 1005 can be high-speed RAM memory, also may be used
To be stable memory (non-volatile memory), such as magnetic disk storage.Memory 1005 optionally can also be
Independently of the storage device of aforementioned processor 1001.
It will be understood by those skilled in the art that structure shown in Fig. 1 does not constitute the restriction to user equipment, can wrap
It includes than illustrating more or fewer components, either combines certain components or different components arrangement.
As shown in Figure 1, as may include that operating system, network are logical in a kind of memory 1005 of computer storage media
The matcher of letter module, Subscriber Interface Module SIM and information of real estate.
In user equipment shown in Fig. 1, network interface 1004 is mainly used for connecting background server, is taken with the backstage
Device be engaged in into row data communication；User interface 1003 is mainly used for connecting peripheral hardware；The user equipment is called by processor 1001
The matcher of the information of real estate stored in memory 1005, and execute the match party of information of real estate provided in an embodiment of the present invention
Method.
Based on above-mentioned hardware configuration, the embodiment of the matching process of information of real estate of the present invention is proposed.
It is the flow diagram of the matching process first embodiment of information of real estate of the present invention with reference to Fig. 2, Fig. 2.
In the first embodiment, the matching process of the information of real estate includes the following steps：
Step S10：Obtain self-built housing source information and third party's information of real estate；
It is understood that the executive agent of the present embodiment is user equipment, which can be service server, a
Other electronic equipments such as people's computer.It is adopted in view of house property medium corporate entity can carry out the outer on the spot of information of real estate to get
Self-built information of real estate, although the self-built information of real estate accuracy rate that the mode that this kind acquires on the spot is got is higher, but number
According to measuring, smaller and cost is higher, so, it is heterogeneous that house property medium company will obtain source while collecting self-built information of real estate
Third party's information of real estate.Wherein, third party's information of real estate refers to the room provided by third party in addition to self-built information of real estate
Source information, still, it is contemplated that there are a variety of attribute classifications for information of real estate, for example, common attribute classification has cell name, cell
Longitude and latitude, source of houses picture, source of houses configuration, source of houses price and developer's information etc., however, third party's source of houses that third party provides
There may be the differences in attribute classification with self-built information of real estate for information, for example, it is small to have recorded certain in possible self-built information of real estate
The cell longitude and latitude and developer's information in area still only have recorded the cell longitude and latitude of the cell in third party's information of real estate
Developer's information of the cell is not recorded.
Step S20：It is other that self-built Attribute class is extracted from the self-built information of real estate, the self-built attribute classification be it is described from
The attribute classification of each attribute data in the source information that builds a house；
It should be understood that since there may be certain differences with third party's information of real estate for self-built information of real estate, for example,
The attribute classification that self-built information of real estate may be recorded with third party's information of real estate when recording the house property of A cells has differences, i.e.,
Make to be the attribute classification such as developer's information all recorded simultaneously, it is also possible to which there are self-built informations of real estate and third party's source of houses to believe
The developer's information recorded in breath is different, moreover, it is even possible, self-built information of real estate record has A cells, third party's source of houses letter
There is no the source of houses of A cells to record in breath.In order to audit and integrate self-built information of real estate and third party's information of real estate, the existing source of houses
Signal auditing mode carries out mostly in a manner of manual examination and verification, and still, the review efficiency of this kind of mode and accuracy are all extremely low,
The present embodiment will provide a kind of mode audited automatically, with the room in the self-built information of real estate of Auto-matching and third party's information of real estate
Source information, to filter out the unreliable attribute data in self-built information of real estate so that business personnel need to only audit self-built source of houses letter
Unreliable attribute data in breath, reduces pending data volume, to improve review efficiency.
In the concrete realization, can first from self-built information of real estate extract A cells self-built attribute classification, for example, it is described from
It can be " cell longitude and latitude " to build attribute classification, corresponding with self-built attribute classification " the cell longitude and latitude " in self-built information of real estate
The longitude and latitude numerical value of attribute data, that is, A cells can be " 48 ° of 51'11.39 " N, 2 ° of 20'56.95 " E ".
Step S30：Based on each self-built Attribute class do not calculate the self-built information of real estate and third party's information of real estate it
Between the first attributes match degree；
It should be understood that if all record has the cell longitude and latitude of A cells in self-built information of real estate and third party's information of real estate
Degree, then can by " attribute data corresponding with A cell longitudes and latitudes in self-built information of real estate " with it is " in third party's information of real estate small with A
The corresponding attribute data of area's longitude and latitude " is matched, to obtain the first attributes match degree.For the detailed process of matching operation,
The matching degree of two longitude and latitude numerical value can be calculated, for example, the attribute data in self-built information of real estate be " 48 ° of 51'11.39 " N, 2 °
The attribute data of 20'56.95 " E ", third party's information of real estate are that " 49 ° of 51'11.39 " N, 3 ° of 20'56.95 " E ", can be with self-built housing
Subject to latitude and longitude coordinates in source information, the latitude and longitude coordinates recorded in third party's information of real estate are in self-built information of real estate
Latitude and longitude coordinates, then the matching degree of two longitude and latitude numerical value is higher, if the latitude and longitude coordinates in self-built information of real estate and the
The latitude and longitude coordinates of tripartite's information of real estate are equal, then the matching degree of two longitude and latitude numerical value reaches highest, are 100%.
In the concrete realization, can be to calculate in self-built information of real estate for the conversion mode of the matching degree of longitude and latitude numerical value
Latitude and longitude coordinates and third party's information of real estate in the distance between latitude and longitude coordinates, for example, " 48 ° of 51'11.39 " N, 2 °
" E " is that " 1 ° of N, 1 ° of E ", calculated distance are with differences of " the 49 ° of 51'11.39 " N, 3 ° of 20'56.95 " between E " to 20'56.95The rule of correspondence of longitude and latitude distance and matching degree can be pre-established, specifically, distance x is 0<In the range of x≤1
90% is corresponded to degree, distance x is 1<Matching degree in the range of x≤2 corresponds to 70% etc..Since calculated distance isUnderstand that the matching degree of corresponding two longitude and latitude numerical value is 70%.
Certainly, the present embodiment is not intended to limit the rule of correspondence of longitude and latitude distance and matching degree；Simultaneously as in information of real estate
Attribute classification it is numerous, for finally calculate the first attributes match degree got can multiple attribute classifications calculate separately out
The weighted average of matching degree.
Step S40：The first attributes match degree is judged whether in the first matching degree section, in first attribute
It, will be corresponding with the self-built attribute classification in the self-built information of real estate when matching degree is in first matching degree section
Attribute data regards as unreliable attribute data.
It is understood that in order to simplify expression, the present embodiment can directly by with longitude and latitude apart from corresponding matching degree
70% regards as the first attributes match degree.
It should be understood that in order to improve review efficiency, it is unreliable in self-built information of real estate that the present embodiment will filter out
Attribute data, to reduce the data volume for waiting for manual examination and verification.So the present embodiment by the attribute data in self-built information of real estate into
Row classification, can be divided into three kinds of information, reliable attribute data, unreliable attribute data and wrong community data.For attribute
The mode classification of data can set three matching degree sections to classify, for example, the first matching degree section be " 0.5≤y≤
0.7 ", unreliable attribute data is corresponding with the first matching degree section, to indicate that the attribute data may be correct；Second matching degree area
Between be " 0≤y<0.5 " (y indicates matching degree), wrong community data are corresponding with the second matching degree section, to indicate the attribute data
Misregistration；Third matching degree section is " 0.7<Y≤1 ", reliable attribute data is corresponding with third matching degree section, to indicate this
Attribute data is identified as correctly.Since the first attributes match degree is 70%, then the first attributes match degree is in the first matching degree
In section, show that the attribute data in self-built information of real estate is that " 48 ° of 51'11.39 " N, 2 ° of 20'56.95 " E " are unreliable category
Property data.
It is understood that by information of real estate is classified in this present embodiment, can be screened from information of real estate automatically
Go out unreliable attribute data so that business personnel directly can carry out manual examination and verification to unreliable attribute data, without extraly
It has audited wrong community data to be audited with reliable attribute data, has also just reduced the data volume for waiting for manual examination and verification, Jin Erti
High review efficiency.Wherein, the wrong community data in self-built information of real estate, which can be screened out directly, does not use the partial data,
Just need not additionally it audit.
Further, the step S30 can also include：Calculate the self-built information of real estate and third party's source of houses
Each objective attribute target attribute matching degree not corresponding with each self-built Attribute class between information；Determination is not corresponding with each self-built Attribute class
Default weight coefficient, and the objective attribute target attribute matching degree is weighted based on the default weight coefficient, to obtain
First attributes match degree.
In the concrete realization, since the attribute classification of information of real estate is there are a variety of, can come in combination with multiple attribute classifications
The first attributes match degree is calculated, preferably to judge the accuracy of attribute data, because can get for the self-built source of houses
The globality assessment of multiple attribute datas in information.If specifically, calculated objective attribute target attribute corresponding with cell longitude and latitude
Matching degree is 0.7, and the corresponding objective attribute target attribute matching degree of source of houses price is 0.5 and objective attribute target attribute corresponding with developer's information
Matching degree is 0.5, and obtains each default weight coefficient not corresponding with each self-built Attribute class, if each default weight coefficient is respectively
0.5,0.25 and 0.25, then 0.7*0.5+0.5*0.25+0.5*0.25=0.6 can be calculated, the first attributes match degree is 0.6.
Than its first matching degree section, it may be determined that the first attributes match degree 0.6 is in the first matching degree section " 0.5≤y≤0.7 ",
Then it is believed that attribute data corresponding with cell longitude and latitude, source of houses price and developer's information is unreliable attribute data.
It is understood that the default weight coefficient will be based on by preset matching degree calculation formula to the target
Attributes match degree is weighted, wherein the preset matching degree calculation formula is as follows：
Y=x1*q1+x2*q2+x3*q3,
Wherein, Y is the first attributes match degree, and x1, x2 and x3 are indicated and the not corresponding each mesh of each self-built Attribute class
Attributes match degree is marked, q1, q2 and q3 indicate default weight coefficient not corresponding with each self-built Attribute class.
Information matches can be carried out to self-built information of real estate and third party's information of real estate in the present embodiment, to calculate the two
Between matching degree, and set the first attributes match degree to filter out unreliable attribute data from self-built information of real estate so that
Business personnel can directly audit unreliable attribute data, than business personnel's direct check and correction by way of manual examination and verification
All informations of real estate grasped, this embodiment reduces the data volumes for waiting for manual examination and verification, improve review efficiency, also just solve
The relatively low technical problem of review efficiency existing for existing information of real estate audit mode.
It is the flow diagram of the matching process second embodiment of information of real estate of the present invention with reference to Fig. 3, Fig. 3, based on above-mentioned
First embodiment shown in Fig. 2 proposes the second embodiment of the matching process of information of real estate of the present invention.
In a second embodiment, the step S30 may include：
Step S301：Each self-built Attribute class traversed in the self-built information of real estate is other, from the not middle choosing of each self-built Attribute class
Take the first attribute classification；
It is understood that for classification of the same race attribute data contrastingly, the present embodiment will be first from the self-built source of houses
The first attribute classification is determined in multiple attribute classifications in information, for example, the first attribute classification can be " cell longitude and latitude ".
Step S302：The first attribute number corresponding with the first attribute classification is extracted from the self-built information of real estate
According to；
Step S303：The second attribute number corresponding with the first attribute classification is inquired in third party's information of real estate
According to；
It should be understood that if the first attribute data corresponding with " cell longitude and latitude " recorded in self-built information of real estate is
" latitude and longitude coordinates point A ", the first attribute data corresponding with " cell longitude and latitude " recorded in third party's information of real estate are " longitude and latitude
Spend coordinate points B ".Certainly, for the ease of comparing, the longitude and latitude got from self-built information of real estate and third party's information of real estate is sat
Punctuate is the latitude and longitude coordinates point of same cell.
Step S304：Belong to inquiring corresponding with the first attribute classification second from third party's information of real estate
Property data when, calculate the first attributes match degree between first attribute data and second attribute data.
It is understood that by the matching degree between calculating " latitude and longitude coordinates point A " and " latitude and longitude coordinates point B ", with
Obtain the first attributes match degree.
Further, the step S304 can also include：Inquired from third party's information of real estate with it is described
When corresponding second attribute data of the first attribute classification, according to the first attribute Query in each matching degree computation rule
Corresponding object matching degree computation rule；Based on the object matching degree computation rule carry out first attribute data with it is described
Matching degree between second attribute data calculates, to obtain the first attributes match degree.
In the concrete realization, it is contemplated that the data format of the attribute data of different attribute classification there are larger difference, than
Such as, " cell name " is mostly Chinese character, letter and number combinatorics on words, and cell longitude and latitude is latitude and longitude information, and the source of houses is matched
The detailed architecture information then for house property is set, the data lattice for adapting to the attribute data of different attribute classification are needed when calculating matching degree
Formula, so, it will be provided with corresponding matching degree computation rule for different attribute classifications in the present embodiment, in order to more adapt to
Different attribute classifications carries out the calculating of matching degree.For example, can be for " developer's information " corresponding matching degree computation rule,
Directly calculate the name of the developer name of the middle record of the developer title and third party's information of real estate recorded in self-built information of real estate
Claim similarity, according to title it is identical whether and identical number of words quantity weigh title similarity, and then calculate matching
Degree.
Further, the first attribute classification is cell longitude and latitude, and the step S304 can also include：From institute
It states when inquiring the second attribute data corresponding with the cell longitude and latitude in third party's information of real estate, calculates and advise in each matching degree
Corresponding longitude and latitude matching degree computation rule is inquired according to the cell longitude and latitude in then；Based on the longitude and latitude matching degree computation rule
The longitude and latitude difference between first attribute data and second attribute data is calculated, and in the first default mapping relations
Corresponding first attributes match degree is determined according to the longitude and latitude difference, and the first default mapping relations include that longitude and latitude is poor
The correspondence of value and attributes match degree.
It is understood that due to that will be that corresponding matching degree computation rule is arranged in different attribute classifications, if Attribute class
Not Wei cell longitude and latitude when, corresponding object matching degree computation rule will be longitude and latitude matching degree computation rule, longitude and latitude matching
Degree computation rule refers to the physical distance calculated between two latitude and longitude coordinates points.It, can for the ease of determining its attributes match degree
The first default mapping relations are pre-set, longitude and latitude difference section and attribute will be accordingly stored in the first default mapping relations
With degree, if for example, calculated physical distance isAnd preset distance x is 1 in the first default mapping relations<X≤2
Corresponding attributes match degree corresponds to 70% in range, then final calculated first attributes match degree is 70%.It is above-mentioned for
The matching process first that the detailed process that the attributes match degree of " cell longitude and latitude " calculates can refer to information of real estate of the present invention is implemented
The matching degree calculation for the latitude and longitude coordinates that example provides.
It specifically describes in the present embodiment " way of contrast of the attribute data of classification of the same race ", meanwhile, the present embodiment
Corresponding matching degree computation rule is pre-set for different attribute classifications so that the calculating process of matching degree is more suitable for difference
The data format of different larger attribute data, improves review efficiency.
It is the flow diagram of the matching process 3rd embodiment of information of real estate of the present invention with reference to Fig. 4, Fig. 4, based on above-mentioned
Second embodiment shown in Fig. 3 proposes the 3rd embodiment of the matching process of information of real estate of the present invention.
In the third embodiment, after the step S303, can also include：
Step S3041：Do not inquiring corresponding with the first attribute classification from third party's information of real estate
When two attribute datas, calls and preset map datum API to obtain third attribute data corresponding with the first attribute classification；
It should be understood that in view of there may be attribute classifications with self-built information of real estate for third party's information of real estate in single library
On difference, default map datum application programming interface (Application Programming can be called
Interface, API) to get the information of real estate stored in other databases, and the source of houses letter stored from other databases
Attribute data corresponding with the first attribute classification is found in breath, specifically, not remembering when in third party's information of real estate
When recording the latitude and longitude coordinates point of specific cell, go to search the longitude and latitude of the cell in the information of real estate that can be stored from other databases
Third attribute data, can be abbreviated as " latitude and longitude coordinates point C " by the concrete numerical value for spending coordinate points B.
Step S3042：Calculate the second attributes match degree between first attribute data and the third attribute data；
Step S40'：When the second attributes match degree is in first matching degree section, by the self-built housing
Attribute data corresponding with the first attribute classification regards as unreliable attribute data in source information.
In the concrete realization, it after getting third attribute data " latitude and longitude coordinates point C " in other databases, can count
The matching degree between " latitude and longitude coordinates point A " and " latitude and longitude coordinates point C " is calculated, to obtain the second attributes match degree, to basis
Whether the second attributes match degree is unreliable attribute data come " the latitude and longitude coordinates point A " judged in self-built information of real estate.
It is understood that due to when there is no the second attribute data can by obtain third attribute data come complete with
The matching of first attribute data is obtained in combination with self-built information of real estate, third party's information of real estate and default map datum API
The information of real estate that is stored in other databases got assesses the reliability of self-built information of real estate, and accuracy is more preferable, Bu Huiyin
Data for third party's information of real estate it is not comprehensive or record the variant accuracy for reducing matching process of attribute classification.
It in the present embodiment will be in combination with self-built information of real estate, third party's information of real estate and default map datum
The information of real estate that is stored in other databases that API is got assesses the reliability of self-built information of real estate, so as to more
Matching that is complete and comprehensively carrying out third party's information of real estate and self-built information of real estate, audits self-built information of real estate with raising
Audit accuracy.
It is the flow diagram of the matching process fourth embodiment of information of real estate of the present invention with reference to Fig. 5, Fig. 5, based on above-mentioned
Second embodiment shown in Fig. 3 proposes the fourth embodiment of the matching process of information of real estate of the present invention.
In the fourth embodiment, after the step S303, can also include：
Step S3043：Do not inquiring corresponding with the first attribute classification from third party's information of real estate
When two attribute datas, corresponding cell ID is determined according to the first attribute classification in the second default mapping relations, is inquired
The second attribute classification corresponding with the cell ID, the second default mapping relations include the cell ID, described
Correspondence between one attribute classification and the second attribute classification；
It is understood that the category for the classification of the same race being different from the matching process second embodiment of information of real estate of the present invention
The way of contrast of property data, will provide the way of contrast of the other attribute data of variety classes in the present embodiment.If specifically,
The first attribute data corresponding with first attribute classification " cell address " in self-built information of real estate is the " cities the XX streets XX XX cells
No. XX ", and the attribute data in third party's information of real estate and there is no " cell address ", then it can be according to the second default mapping relations
To obtain the relevant other attribute data of other Attribute class.
In the concrete realization, consider that there are certain relevances between various attribute classifications, for example, cell address and cell
Longitude and latitude is all the information for indicating address, and there may be certain relevances with cell name for developer information, because, cell name
It may include the division name of developer in title, just allow between the various attribute classifications in information of real estate that there is one
Fixed relevance can establish the second default mapping relations, and there will be the attribute classifications of relevance to be associated storage, when part
When attribute classification is not recorded, other attribute classifications of associated storage can be inquired to complete to verify.For example, with " cell address "
Corresponding attribute classification is the second attribute classification " cell longitude and latitude ".
Wherein, cell ID can be cell name for uniquely marking specific cell.
Step S3044：The 4th attribute corresponding with the second attribute classification is inquired in third party's information of real estate
Data；
Step S3045：It is being inquired from third party's information of real estate and the second attribute classification the corresponding 4th
When attribute data, the third attributes match degree between first attribute data and the 4th attribute data is calculated；
It should be understood that getting with after the specific longitude and latitude numerical value of " cell longitude and latitude ", the first attribute can be calculated
Data are between the address information of " cell address " and the 4th attribute data i.e. specific longitude and latitude numerical value of " cell longitude and latitude "
Third attributes match degree.Can be for the method for calculating matching degree, it is contemplated that the address information of " cell address " can also have warp
Latitude information, after can first inquiring the latitude and longitude information that " cell address " indicates, by the longitude and latitude of " cell address " expression
Information and the specific longitude and latitude numerical value of " cell longitude and latitude " carry out matching degree calculating, can refer to the matching recorded in first embodiment
Spend calculation.
Step S40 "：When the third attributes match degree is in first matching degree section, by the self-built housing
Attribute data corresponding with the first attribute classification regards as unreliable attribute data in source information.
Further, the first attribute classification is cell area boundary, and the cell area boundary is by continuously passing through
The closed polygon that latitude coordinate point is constituted, the second attribute classification are latitude and longitude coordinates point；
Correspondingly, described to be inquired from third party's information of real estate and the second attribute classification the corresponding 4th
When attribute data, the third attributes match degree between first attribute data and the 4th attribute data is calculated, including：
When being inquired from third party's information of real estate with corresponding four attribute data of latitude and longitude coordinates point,
Detect whether the latitude and longitude coordinates point that the 4th attribute data indicates is located at the cell area that first attribute data indicates
On the inside of the boundary on boundary, corresponding third attributes match degree is determined according to testing result.
It is understood that the present embodiment proposes a kind of novel attribute classification, i.e. cell area boundary, in record room
When source information will simultaneously recording cell zone boundary, cell area boundary than cell longitude and latitude can be more accurately to cell
It is recorded, because cell area boundary is the closed polygon being made of continuous latitude and longitude coordinates point, and cell longitude and latitude
An only longitude and latitude point, it should be apparent, however, that cell is the larger groups of building of a floor space, single longitude and latitude point is not
The address information of the groups of building can be recorded well, and can accurately record the cell around the zone boundary of the cell
Take up an area position.
It should be understood that because cell area boundary may not record in third party's information of real estate, in order to
The automatic review operations on cell area boundary are completed, can accordingly record " cell area in the second default mapping relations in advance
Boundary " and " cell longitude and latitude ", judge " cell longitude and latitude " record in third party's information of real estate latitude and longitude coordinates point whether
On the inside of the boundary for falling within " cell area boundary ", when the latitude and longitude coordinates point is fallen on the inside of the boundary on " cell area boundary ",
The matching degree acquired is 100%；When the latitude and longitude coordinates point falls within the outside boundaries on " cell area boundary ", passed through calculating
The air line distance of any on the boundary of latitude coordinate point distance " cell area boundary ", determines according to the distance of the air line distance
The size of corresponding matching degree can refer to the rule of correspondence of the longitude and latitude distance and matching degree that are recorded in first embodiment.
It will be in combination with " alignments of the attribute data of classification of the same race " and " the other category of variety classes in the present embodiment
Property data alignments ", to avoid when the attribute classification incomplete recording in third party's information of real estate caused audit it is accurate
Rate reduces；Meanwhile introduce novel attribute classification i.e. cell area boundary, than cell longitude and latitude can more accurately remember
Record the subdistrict position in information of real estate.
In addition, the embodiment of the present invention also proposes a kind of storage medium, of information of real estate is stored on the storage medium
With program, the matcher of the information of real estate realizes the matching process of information of real estate as described above when being executed by processor
The step of.
In addition, with reference to Fig. 6, the embodiment of the present invention also proposes a kind of coalignment of information of real estate, the information of real estate
Coalignment includes：Data obtaining module 10, category determination module 20, matching degree computing module 30 and data assert module
40；
Described information acquisition module 10, for obtaining self-built housing source information and third party's information of real estate；
The category determination module 20, it is other for extracting self-built Attribute class from the self-built information of real estate, it is described self-built
Attribute classification is the attribute classification of each attribute data in the self-built information of real estate；
The matching degree computing module 30, for be based on each self-built Attribute class do not calculate the self-built information of real estate with it is described
The first attributes match degree between third party's information of real estate；
The data assert module 40, for judging whether the first attributes match degree is in the first matching degree section
It is interior, when the first attributes match degree is in first matching degree section, by the self-built information of real estate with it is described
The corresponding attribute data of self-built attribute classification regards as unreliable attribute data.
Information matches can be carried out to self-built information of real estate and third party's information of real estate in the present embodiment, to calculate the two
Between matching degree, and set the first attributes match degree to filter out unreliable attribute data from self-built information of real estate so that
Business personnel can directly audit unreliable attribute data, than business personnel's direct check and correction by way of manual examination and verification
All informations of real estate grasped, this embodiment reduces the data volumes for waiting for manual examination and verification, improve review efficiency, also just solve
The relatively low technical problem of review efficiency existing for existing information of real estate audit mode.
It should be noted that herein, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that process, method, article or system including a series of elements include not only those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including this
There is also other identical elements in the process of element, method, article or system.
The embodiments of the present invention are for illustration only, can not represent the quality of embodiment.If listing equipment for drying
Unit claim in, several in these devices can be embodied by the same hardware branch.Word first,
Second and the use of third etc. do not indicate that any sequence, can be title by these word explanations.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can add the mode of required general hardware platform to realize by software, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical scheme of the present invention substantially in other words does the prior art
Going out the part of contribution can be expressed in the form of software products, which is stored in a storage medium
In (such as ROM/RAM, magnetic disc, CD), including some instructions are used so that a station terminal equipment (can be mobile phone, computer, clothes
Be engaged in device, air conditioner or the network equipment etc.) execute method described in each embodiment of the present invention.
It these are only the preferred embodiment of the present invention, be not intended to limit the scope of the invention, it is every to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of matching process of information of real estate, which is characterized in that the matching process of the information of real estate includes the following steps：
Obtain self-built housing source information and third party's information of real estate；
It is other that self-built Attribute class is extracted from the self-built information of real estate, the self-built attribute classification is in the self-built information of real estate
Each attribute data attribute classification；
The first attribute between the self-built information of real estate and third party's information of real estate is not calculated based on each self-built Attribute class
Matching degree；
Judge that whether in the first matching degree section, institute is in the first attributes match degree for the first attributes match degree
When stating in the first matching degree section, by attribute data identification corresponding with the self-built attribute classification in the self-built information of real estate
For unreliable attribute data.
2. the matching process of information of real estate as described in claim 1, which is characterized in that described not counted based on each self-built Attribute class
The first attributes match degree between the self-built information of real estate and third party's information of real estate is calculated, including：
It calculates not corresponding with each self-built Attribute class between the self-built information of real estate and third party's information of real estate
Each objective attribute target attribute matching degree；
Determine default weight coefficient not corresponding with each self-built Attribute class, and based on the default weight coefficient to the target category
Property matching degree is weighted, to obtain the first attributes match degree.
3. the matching process of information of real estate as described in claim 1, which is characterized in that described not counted based on each self-built Attribute class
The first attributes match degree between the self-built information of real estate and third party's information of real estate is calculated, including：
Each self-built Attribute class traversed in the self-built information of real estate is other, and the first Attribute class is chosen from each self-built Attribute class is not middle
Not；
The first attribute data corresponding with the first attribute classification is extracted from the self-built information of real estate；
The second attribute data corresponding with the first attribute classification is inquired in third party's information of real estate；
When inquiring the second attribute data corresponding with the first attribute classification from third party's information of real estate, calculate
The first attributes match degree between first attribute data and second attribute data.
4. the matching process of information of real estate as claimed in claim 3, which is characterized in that the first attribute classification passes through for cell
Latitude；
It is described when inquiring the second attribute data corresponding with the first attribute classification from third party's information of real estate,
The first attributes match degree between first attribute data and second attribute data is calculated, including：
When inquiring the second attribute data corresponding with the cell longitude and latitude from third party's information of real estate, at each
Corresponding longitude and latitude matching degree computation rule is inquired according to the cell longitude and latitude with spending in computation rule；
The warp between first attribute data and second attribute data is calculated based on the longitude and latitude matching degree computation rule
Latitude difference, and corresponding first attributes match degree, institute are determined according to the longitude and latitude difference in the first default mapping relations
State the correspondence that the first default mapping relations include longitude and latitude difference and attributes match degree.
5. the matching process of information of real estate as claimed in claim 3, which is characterized in that described in third party's information of real estate
Middle to inquire after the second attribute data corresponding with the first attribute classification, the matching process of the information of real estate further includes：
When not inquiring the second attribute data corresponding with the first attribute classification from third party's information of real estate, adjust
With default map datum API to obtain third attribute data corresponding with the first attribute classification；
Calculate the second attributes match degree between first attribute data and the third attribute data；
When the second attributes match degree is in first matching degree section, by the self-built information of real estate with it is described
The corresponding attribute data of first attribute classification regards as unreliable attribute data.
6. the matching process of information of real estate as claimed in claim 3, which is characterized in that described in third party's information of real estate
Middle to inquire after the second attribute data corresponding with the first attribute classification, the matching process of the information of real estate further includes：
When not inquiring the second attribute data corresponding with the first attribute classification from third party's information of real estate,
Corresponding cell ID, inquiry and the cell ID pair are determined according to the first attribute classification in second default mapping relations
The the second attribute classification answered, the second default mapping relations include the cell ID, the first attribute classification with it is described
Correspondence between second attribute classification；
The 4th attribute data corresponding with the second attribute classification is inquired in third party's information of real estate；
When inquiring four attribute data corresponding with the second attribute classification from third party's information of real estate, calculate
Third attributes match degree between first attribute data and the 4th attribute data；
When the third attributes match degree is in first matching degree section, by the self-built information of real estate with it is described
The corresponding attribute data of first attribute classification regards as unreliable attribute data.
7. the matching process of information of real estate as claimed in claim 6, which is characterized in that the first attribute classification is small trivial
Domain boundary, the cell area boundary are the closed polygon being made of continuous latitude and longitude coordinates point, second Attribute class
It Wei not latitude and longitude coordinates point；
Correspondingly, described that the 4th attribute corresponding with the second attribute classification is being inquired from third party's information of real estate
When data, the third attributes match degree between first attribute data and the 4th attribute data is calculated, including：
When being inquired from third party's information of real estate with corresponding four attribute data of latitude and longitude coordinates point, detection
Whether the latitude and longitude coordinates point that the 4th attribute data indicates is located at the cell area boundary that first attribute data indicates
Boundary on the inside of, according to testing result determine corresponding third attributes match degree.
8. a kind of user equipment, which is characterized in that the user equipment includes：Memory, processor and it is stored in the storage
The matcher of information of real estate can be run on device and on the processor, the matcher of the information of real estate is by the processing
The step of matching process of the information of real estate as described in any one of claim 1 to 7 is realized when device executes.
9. a kind of storage medium, which is characterized in that be stored with the matcher of information of real estate, the source of houses on the storage medium
The match party of the information of real estate as described in any one of claim 1 to 7 is realized when the matcher of information is executed by processor
The step of method.
10. a kind of coalignment of information of real estate, which is characterized in that the coalignment of the information of real estate includes：Acquisition of information
Module, category determination module, matching degree computing module and data assert module；
Described information acquisition module, for obtaining self-built housing source information and third party's information of real estate；
The category determination module, for other, the self-built Attribute class that extracts self-built Attribute class from the self-built information of real estate
The attribute classification of each attribute data that Wei be in the self-built information of real estate；
The matching degree computing module does not calculate the self-built information of real estate and the third party for being based on each self-built Attribute class
The first attributes match degree between information of real estate；
The data assert module, for judging the first attributes match degree whether in the first matching degree section, in institute
When stating the first attributes match degree and being in first matching degree section, by the self-built information of real estate with the self-built attribute
The corresponding attribute data of classification regards as unreliable attribute data.
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