CN106384250A - Site selection method and device - Google Patents

Site selection method and device Download PDF

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Publication number
CN106384250A
CN106384250A CN201610821849.4A CN201610821849A CN106384250A CN 106384250 A CN106384250 A CN 106384250A CN 201610821849 A CN201610821849 A CN 201610821849A CN 106384250 A CN106384250 A CN 106384250A
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grid
coefficient
addressing
poi
target
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董磊
阚长城
高艾凤
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Beijing Baidu Netcom Science and Technology Co Ltd
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Beijing Baidu Netcom Science and Technology Co Ltd
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Priority to CN201610821849.4A priority Critical patent/CN106384250A/en
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0282—Rating or review of business operators or products
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/08—Construction

Abstract

The embodiment of the invention discloses a site selection method and device, and belongs to the technical field of big data. The method comprises the steps: obtaining the identification of a to-be-selected main body and a target site selection area when a site selection event is monitored; carrying out the grid dividing of the target site selection area; determining a site selection coefficient of grids according to the correlation data of the to-be-selected main body and the target site selection area; selecting grids from the target site selection area according to the side selection coefficient of the grids as candidate sites of the to-be-selected main body. According to the embodiment of the invention, the method and device solve problems that the manual collection and analysis of data causes the inaccurate site selection range, high manpower cost and low efficiency.

Description

A kind of site selecting method and device
Technical field
The present embodiments relate to big data technical field, more particularly, to a kind of site selecting method and device.
Background technology
Shown by substantial amounts of scholar's research, the factor of impact addressing includes the density of population and distribution, flow of the people, Ke Huxu Ask temperature and market competition etc..Addressing at present mainly collects data on a large scale by manpower first, and the stream of people including surrounding is rough Data, shop number, communal facility etc.；Then the data collected is analyzed, and determines the scope of addressing.And, it is elected to When location target area scope is larger, need that roughly the relatively small candidate regions of multiple scopes selected by frame to addressing target area Domain, then utilizes a large amount of manpowers to collect data candidate region.
But, artificially the data of described collection is analyzed not only increasing human cost, and have that time-consuming and The low shortcoming of accuracy rate.And, manpower collection data is not accurate, also results in the scope of the addressing determining by this data not Accurately problem.
Content of the invention
The embodiment of the present invention provides a kind of site selecting method and device, and to solve, manpower collects data and analyze data brings The problem that addressing scope is not precisely, human cost is high and efficiency is low.
In a first aspect, embodiments providing a kind of site selecting method, the method includes：
When monitoring addressing event, obtain mark and the target addressing region treating addressing main body；
Stress and strain model is carried out to described target addressing region；
According to the described associated data treating addressing main body and described target addressing region, determine the addressing system of described grid Number；
According to the addressing coefficient of described grid, select grid from target addressing region, as the candidate treating addressing main body Address.
Second aspect, the embodiment of the present invention additionally provides a kind of addressing device, and this device includes：
Data obtaining module, for when monitoring addressing event, obtaining mark and the target addressing area treating addressing main body Domain；
Stress and strain model module, for carrying out stress and strain model to described target addressing region；
Addressing coefficient determination module, according to the described associated data treating addressing main body and described target addressing region, determines The addressing coefficient of described grid；
Candidate site determining module, for the addressing coefficient according to described grid, selects grid from target addressing region, As the candidate site treating addressing main body.
The embodiment of the present invention is passed through according to the described associated data treating addressing main body and described target addressing region, determines mesh In mark addressing region, the addressing coefficient of grid, then determines the candidate site of addressing main body according to the addressing coefficient of grid.Thus Eliminate using the data treating addressing main body and described target addressing region described in manpower collection and using manpower, data is carried out The trouble of analysis.And then solve manpower collect the addressing scope that data and analyze data bring not precisely, human cost is high and effect The low problem of rate.
Brief description
A kind of flow chart of site selecting method that Fig. 1 provides for the embodiment of the present invention one；
Fig. 2 is a kind of flow chart of site selecting method that the embodiment of the present invention two provides；
Fig. 3 is a kind of flow chart of site selecting method that the embodiment of the present invention three provides；
Fig. 4 is the flow chart of another kind of site selecting method that the embodiment of the present invention three provides；
Fig. 5 is a kind of structural representation of addressing device that the embodiment of the present invention four provides.
Specific embodiment
The present invention is described in further detail with reference to the accompanying drawings and examples.It is understood that this place is retouched The specific embodiment stated is used only for explaining the present invention, rather than limitation of the invention.It also should be noted that, in order to just Part related to the present invention rather than entire infrastructure is illustrate only in description, accompanying drawing.
Embodiment one
A kind of flow chart of site selecting method that Fig. 1 provides for the embodiment of the present invention one.The present embodiment is applicable in target In addressing region, addressing main body is carried out with the situation of addressing.The method can be executed by a kind of addressing device, and this device is permissible Realized by the mode of software and/or hardware.Referring to Fig. 1, the site selecting method that the present embodiment provides includes：
S110, when monitoring addressing event, obtain and treat mark and the target addressing region of addressing main body.
Wherein, addressing event is to treat that addressing main body selects the event of situation of building in target addressing region；Treat addressing master Body is the main body needing to consider situation of building according to surrounding environment, and this treats that addressing main body can be commercial network or residence People's house, specifically, commercial network can include：Retail shop, commodity exchange market, fleamarket, vehicle transaction market, thing Stream base, eating and drinking establishment and other Life service industry facilities etc.；Target addressing region is to treat that all of addressing main building position can The region of energy, specifically, described target addressing region can include a city, administrative area, commercial circle or block.
It should be noted that treating the mark of addressing main body and treating addressing main body and correspond, optionally, this treats addressing main body Mark can be the title of addressing main body or default mark.For example, as the mark in hotel, A1 is a star wine to A The mark in shop, A5 is mark of deluxe hotel etc..
S120, stress and strain model is carried out to described target addressing region.
Wherein, size of mesh opening can preset it is also possible to be configured as needed.For example, for treating addressing main body Carry out specific addressing, target addressing region can be carried out the stress and strain model of relatively small size of mesh opening；For saving to be selected Location main body carries out the time of addressing or carries out rough addressing to addressing main body, can carry out target addressing region relatively large The stress and strain model of size of mesh opening.
Typically, described stress and strain model is carried out to described target addressing region can include：Obtain in described addressing event The construction area determining；According to described construction area and/or treat addressing main body produce impact periphery P OI (Point of Interest, point of interest) construction area, determine size of mesh opening；According to described size of mesh opening, described target addressing region is entered Row stress and strain model, and unique Marking the cell is corresponded to described grid mark.
Wherein, the construction area determining in described addressing event is the construction area treating addressing main body.For example, treat addressing master Body is articles for swimming brand shop, treats that the construction area of addressing main body is 200*200 square metre, produces weight to articles for swimming brand shop Periphery P OI to be affected is natatorium, and the construction area of natatorium is 500*500 square metre.If only considering this articles for swimming The construction area of brand shop, then size of mesh opening should be greater than 200*200 square metre, so that articles for swimming brand shop falls in grid； If the construction area considering this articles for swimming brand shop and the building of the periphery natatorium that articles for swimming brand shop is produced with impact Area, then size of mesh opening should be greater than 500*500 square metre so as to articles for swimming brand shop produce material impact periphery swimming Shop falls in grid.Further in addition it is also necessary to consider that the scope treating the situation of building that addressing main body addressing obtains can not be too big, In case the precision of determination situation of building is too low, generally grid is set to 1000*1000 square metre.
S130, according to the described associated data treating addressing main body and described target addressing region, determine the choosing of described grid Location coefficient.
Wherein, the described associated data treating addressing main body and described target addressing region is to obtain from the big data prestoring , this big data directly can be obtained it is also possible to obtain from the server being connected with client from client by network.Institute State and treat that addressing main body and the associated data in described target addressing region can include：Map POI basic data, positioning stop points According to, map inquiry data and map POI data etc..
Specifically, can be according to the map POI in the described associated data treating addressing main body and described target addressing region Data, determines the addressing coefficient of described grid.For example, map POI data is corresponding with the grid in target addressing region, then Determine the addressing coefficient of described grid according to the POI quantity in grid, if the quantity of the POI in described grid is 5, described The addressing coefficient of grid is also 5.If it is understood that the quantity of POI in described grid is more, the choosing of described grid Location coefficient is also bigger, and then the possibility as the candidate site treating addressing main body is also bigger.
S140, the addressing coefficient according to described grid, select grid, as treating addressing main body from target addressing region Candidate site.
Specifically, the addressing coefficient of all grids can be ranked up, by one grid of addressing coefficient highest or choosing Coefficient higher multiple grids in location are as the candidate site treating addressing main body.
The technical scheme of the embodiment of the present invention, by according to the described association treating addressing main body and described target addressing region Data, determines the addressing coefficient of grid in target addressing region, then determines the time of addressing main body according to the addressing coefficient of grid Selection of land location.Thus eliminate using manpower collect described in treat the data of addressing main body and described target addressing region and utilize manpower The trouble that data is analyzed.And then solve manpower collect the addressing scope that data and analyze data bring not precisely, manpower High cost and the low problem of efficiency.
It is to be shown to user by clearer for candidate site, in the addressing coefficient according to described grid, determine and treat addressing master After the candidate site of body, also include：
According to described addressing coefficient, described candidate site is marked at by different colours and is loaded with target addressing region ground In the figure layer of figure.
Embodiment two
Fig. 2 is a kind of flow chart of site selecting method that the embodiment of the present invention two provides.The present embodiment is in above-described embodiment On the basis of provide a kind of alternative.Referring to Fig. 2, the site selecting method that the present embodiment provides includes：
S210, when monitoring addressing event, obtain and treat mark and the target addressing region of addressing main body.
S220, stress and strain model is carried out to described target addressing region.
S230, according to the described associated data treating addressing main body and described target addressing region, determine the poly- of described grid Objective coefficient, at least one stopping in coefficient, search factor and coefficient of competition.
Wherein, gather poly- visitor's effect that visitor's coefficient represents in described grid, gather poly- in the more big described grid of value of visitor's coefficient Objective effect is more obvious；Stop coefficient represents the quantity from the target customer treating the corresponding different active states of addressing main body, described The stream of people of the target customer in the more big described grid of value of stop coefficient in grid is bigger, and demand relation is stronger；Search system Number represents that client treats the demand temperature of addressing main body, treats the demand of addressing main body in the more big described grid of value of search factor Temperature is bigger；Coefficient of competition represents that the competitor having existed treats the impact of addressing main body addressing generation, coefficient of competition The competition being worth in more big described grid is fiercer.
Specifically, the determination mode of poly- visitor's coefficient of described grid can be：Objective according to treating that addressing main body determines that target is gathered POI；Filter out described target in map POI basic data from described associated data and gather visitor POI；To in described grid not Counted with the quantity that the described target of POI type gathers visitor POI；Determine poly- visitor's coefficient of described grid according to statistics. For example, the quantity that the target in described grid gathers visitor POI is 10 it is determined that poly- visitor's coefficient of described grid is 10.
Specifically, the determination mode of the stop coefficient of described grid can be：According to treating that addressing main body determines target customer Crowd；Positioning from described associated data stops the active state data filtering out described target customer crowd in point data； Described active state data is counted；According to the dwell point information in described active state data, by statistics difference Corresponding with the described grid in described target addressing region, and the stop of described grid is determined according to the statistics of described grid Coefficient.
Wherein, target customer crowd is the demander treating addressing main body, and target customer crowd can be divided into lodging class Crowd, food and drink class crowd etc., for example, the target customer crowd in hotel is lodging class crowd.Optionally, can be from associated data Direct access target customer crowd classification it is also possible to by active state data the time of staying judge, for example, if The time of staying in the range of 40 minutes to 2 hours, is then judged as food and drink class crowd；If the time of staying is little to 24 at 4 hours When in the range of, then be judged as lodging class crowd, wherein active state is not limited to resting state, for example, it is also possible to be target visitor The travel speed at family.Specifically, positioning stops point data and can obtain by GPS or other alignment system.Due to client's Stop has randomness, therefore generally represents the feature of described grid with the average of a period of time, can be specifically a season Or one month.
Specifically, the determination mode of the search factor of described grid can be：Treat addressing main body as target master using described Body, determines the search keyword of described target subject；According to described search keyword, the map inquiry from described associated data The search record of target subject and corresponding User Status is filtered out in data；Described search record is counted；According to institute State the customer position information in User Status, statistics is corresponding with the described grid in described target addressing region respectively, And the search factor of described grid is determined according to the statistics of described grid.
Wherein, the search keyword of target subject is to derive to treat addressing main body for the keyword on target ground, permissible It is Partial key phrase, or the information such as road name of association.For example, the search keyword in restaurant can be restaurant, cuisines and The title of vegetable or classification etc..Specifically, the user that map inquiry data can store from server use map software or Obtain in the inquiry log of browser.
Specifically, the determination mode of the coefficient of competition of described grid can be：To treat that addressing main body is identical or phase with described As main body, be defined as competitor；Filter out in map POI body data from described associated data and described competition master Body corresponding competitor POI；Described competitor POI is corresponding with the described grid in described target addressing region respectively； The quantity of the described competitor POI of the different POI types in described grid is counted；According to statistics determines The coefficient of competition of grid.
Specifically, map POI body data can obtain from the server of map software association.
S240, the poly- visitor's coefficient according to described grid, at least one stopping in coefficient, search factor and coefficient of competition are true The addressing coefficient of fixed described grid.
Wherein, the addressing coefficient of described grid is to represent scope in described grid if appropriate for as treating addressing main body The coefficient of candidate site, the value of addressing coefficient is more big more is conducive to described grid as the candidate site treating addressing main body.
Specifically, described poly- visitor's coefficient according to described grid, stop coefficient, in search factor and coefficient of competition at least A kind of addressing coefficient determining described grid includes：By poly- visitor's coefficient of described grid, stop coefficient, search factor and competition system At least one in number is normalized；According to normalization result, calculate the addressing coefficient C of described gridlocation.
Wherein, according to normalization result, calculate the addressing coefficient C of described gridlocationMode, can be by poly- visitor system The normalization result of any one in number, stop coefficient and search factor or multiple normalization result sums are as described grid Clocation.
S250, the addressing coefficient according to described grid, select grid, as treating addressing main body from target addressing region Candidate site.
The technical scheme of the embodiment of the present invention, by according to described grid poly- visitor coefficient, stop coefficient, search factor and The addressing coefficient of the described grid of at least one determination in coefficient of competition, to improve the precision of addressing coefficient further, thus Improve the precision of addressing.
Embodiment three
Fig. 3 is a kind of flow chart of site selecting method that the embodiment of the present invention three provides.The present embodiment is in above-described embodiment On the basis of provide a kind of alternative.Referring to Fig. 3, the site selecting method that the present embodiment provides includes：
S310, when monitoring addressing event, obtain and treat mark and the target addressing region of addressing main body.
S320, stress and strain model is carried out to described target addressing region.
S330, basis treat the Different Effects of addressing main body, to POI setting power different types of in target addressing region Weight.
Wherein, the weight of different types of POI is to treat the actual influence setting of addressing main body according to different types of POI 's.The weight of different types of POI can be arranged by user according to the actual requirements it is also possible to be directly disposed as reacting actual shadow The empirical value ringing, the setting scope of usual weighted value is between 0 to 10.
According to the Different Effects treating addressing main body, permissible to POI setting weight different types of in target addressing region Reach such a effect：Weight according to different types of POI can reflect the not degree to addressing for the different types of POI Impact.It is bigger that weighted value is arranged, and illustrates that the impact to addressing is bigger.Therefore, to different types of in target addressing region POI arranges weight, so that the addressing effect level of described grid is clearly more demarcated.If some type of POI treats addressing main body Impact less, then the POI of the type can be given up, or its weight is set to zero.
It should be noted that above-mentioned different types of POI includes treating the POI of addressing main body competitive POI type.Cause POI for the type treats the addressing of addressing main body and has considerable influence, so the generally setting of the weighted value of the POI of the type is relatively Greatly.For example, treat that addressing main body is hotel, this treats that the POI that addressing body peripheral edge type is hotel can attract the crowd that stays in a large number, Also treat addressing main body to cause to compete.
S340, the distance according to this grid and periphery P OI, determine the extension layer of this grid distance periphery P OI place grid Level, and the decay step of each extension level is set.
Wherein, this grid is to treat the grid that addressing main body is located.Extension level represents that periphery P OI is remote apart from this grid Closely, can directly be determined according to the distance of this grid and periphery P OI.For example, 100 meters of distance is defined as an extension level, If the distance of this grid and periphery P OI is between 0 to 100 meters it is determined that extending level for one；If this grid and periphery The distance of POI is between 100 meters to 200 meters it is determined that extending levels for two.Optionally, can also be using this grid and week Grid number between the POI of side determines.For example, a grid is defined as an extension level, if this grid and periphery P OI it Between grid number be 2 it is determined that for two extension levels.
Wherein, decay step represents according to same type of POI apart from the far and near difference of this grid, same type of POI Different degrees of impact to the addressing treating addressing main body in this grid.Optionally, will be able to be declined according to different extension levels Subtract step and be set to one more than 0, and the decimal less than 1, the then multiplied by weight from different POI types, to represent same class The POI of type is because of the distance apart from this grid, and the different degrees of impact to the addressing treating addressing main body in this grid.Example As the decay step of first extension level is 0.9, and the decay step of second extension level is 0.8, treats that addressing main body is wine Shop, the weight of the POI of hotel's type is 10, if a hotel is in first extension level of this grid, Ze Gai hotel pair The impact treating the addressing of addressing main body in this grid is 0.9*10；If hotel is in second extension level of this grid Interior, the impact to the addressing treating addressing main body in this grid for the Ze Gai hotel is 0.8*10.
Decay step, in addition to aforesaid way, can also be set to one and specifically count by the set-up mode of decay step Then the weight of same type of POI is deducted decay step and is multiplied by extension level between this grid for periphery P OI by value Number, to represent same type of POI because of the distance apart from this grid, and the difference to the addressing treating addressing main body in this grid The impact of degree.Continue with above-mentioned location to be selected main body as hotel, as a example the weight of the POI of hotel's type is 10, but decay step For 1, if a hotel is in first extension level of this grid, Ze Gai hotel is to the addressing treating addressing main body in this grid Impact be 10-1*1；If in second extension level of this grid, Ze Gai hotel is to be selected in this grid in a hotel The impact of the addressing of location main body is 10-1*2.
S350, according to the described associated data treating addressing main body and described target addressing region, determine the poly- of described grid Objective coefficient, stop coefficient, search factor and coefficient of competition.
Specifically, treat addressing main body and the associated data in described target addressing region described in described basis, determine described net Poly- visitor's coefficient of lattice can include：According to treat addressing main body determine target gather visitor POI；Map POI from described associated data Filter out described target in basic data and gather visitor POI；The number of visitor POI is gathered to the described target of the different POI types in this grid Amount is counted；Gather the weight of visitor POI according to the described target in statistics and this grid, calculate poly- visitor's effect of this grid Coefficient Vself；According to weight, described decay step and this grid distance periphery that Home Network described target especially gathers visitor POI Target gathers the extension level of visitor POI place grid, calculates target described in periphery and gathers visitor's expansion effect coefficient to this grid for the POI Vround；According to described poly- visitor effect coefficient VselfWith described expansion effect coefficient VroundCalculate poly- visitor's coefficient of described grid Cclient, wherein Cclient=Vself+Vround.
Wherein, can be that user is according to treating addressing main body'choice according to treating the method that addressing main body determines that target gathers visitor POI Target gathers visitor POI it is also possible to treat that addressing main body is gathered in the corresponding relation of visitor POI with corresponding target default, according to be selected Location main body determines that target gathers visitor POI.V to this gridselfCalculating can be can react this grid poly- visitor's ability all Calculation, for example, the weight limit value of POI in this grid is defined as the V of this gridselfOr by this grid All the weighted value sum of POI is defined as the V of this gridself.Calculate target described in periphery and gather the visitor V to this grid for the POIround's Mode can be to react target described in periphery to gather all calculations that visitor POI gathers the actual influence of visitor's ability to this grid, For example, it is possible to the weight of the poly- visitor POI of target described in periphery is multiplied by adding up after the decay step coefficient of its place extension level Value, gathers the visitor V to this grid for the POI as target described in peripheryroundIt is also possible to the target described in periphery in extension level will be set The weight of poly- visitor POI is multiplied by the accumulated value after the decay step coefficient of extension level that it is located, and gathers visitor as target described in periphery The V to this grid for the POIround, to reduce amount of calculation.It is understood that the present embodiment is to VselfAnd VroundCalculating do not carry out Limit.
Optionally, if having much individual specific POI below each the POI type on map, can be first according to be selected Location main body determines that target gathers the type of visitor POI, then determines that target gathers visitor POI according to the type that this target gathers visitor POI；If map On each POI type concrete POI included below less when, then can directly determine that according to treating addressing main body target gathers visitor POI.
Typically, the described weight gathering visitor POI according to the described target in statistics and this grid, calculates this grid Poly- visitor effect coefficient VselfCan include：
Calculate the poly- visitor effect coefficient V of this gridself, formula is as follows：
V s e l f = Σ i = 1 m W P i × N P i
Wherein,Expression POI type is PiCorresponding described target gathers the weight of visitor POI,Represent in this grid and contain POI type is had to be PiDescribed target gather visitor's POI number, m is different POI types sum.
Typically, described according to Home Network described target especially gather weight, described decay step and this grid of visitor POI away from Gather the extension level of visitor POI place grid from target described in periphery, calculate target described in periphery and gather visitor's extension to this grid for the POI Effect coefficient VroundCan include：
Calculate target described in periphery and gather the visitor expansion effect coefficient V to this grid for the POIround, formula is as follows：
V r o u n d = Σ j = 1 n E P j = Σ j = 1 n ( W P j - S P j × k )
Wherein,Represent that Home Network especially POI type is PjDescribed target gather visitor the expansion effect value to this grid for the POI, n For different POI types sum.It is embodied as POI type PjDescribed target gather visitor POI weightDeduct described decay step RankIt is multiplied by extension level k that target described in this grid distance periphery gathers visitor POI place grid.
Specifically, the determination mode of the stop coefficient of described grid can be：According to treating that addressing main body determines target customer Crowd；Positioning from described associated data stops the active state data filtering out described target customer crowd in point data； Described active state data is counted；According to the dwell point information in described active state data, by statistics difference Corresponding with the described grid in described target addressing region, and the stop of described grid is determined according to the statistics of described grid Coefficient.
Specifically, the determination mode of the search factor of described grid can be：Treat addressing main body as target master using described Body, determines the search keyword of described target subject；According to described search keyword, the map inquiry from described associated data The search record of target subject and corresponding User Status is filtered out in data；Described search record is counted；According to institute State the customer position information in User Status, statistics is corresponding with the described grid in described target addressing region respectively, And the search factor of described grid is determined according to the statistics of described grid.
Specifically, treat addressing main body and the associated data in described target addressing region described in described basis, determine described net The coefficient of competition of lattice can include：
The same or analogous main body of addressing main body will be treated with described, be defined as competitor；
Competitor corresponding with described competitor is filtered out in map POI body data from described associated data POI；
Described competitor POI is corresponding with the described grid in described target addressing region respectively；
The quantity of the described competitor POI of the different POI types in this grid is counted；
According to the weight of the described competitor POI in statistics and this grid, calculate the coefficient of competition of this grid Dself, formula is as follows：
D s e l f = Σ i = 1 m W P i × N P i
Wherein,Expression POI type is PiThe weight of corresponding described competitor POI,Represent in this grid and contain POI type is had to be PiDescribed competitor's POI number, m is different POI types sum；
According to the weight of Home Network described competitor POI especially, described decay step and this grid distance periphery The extension level of competitor POI place grid, calculates the coefficient of competition D to this grid for the competitor POI described in peripheryround, Formula is as follows：
D r o u n d = Σ j = 1 n E P j = Σ j = 1 n W P j - S P j × k
Wherein,Represent that Home Network especially POI type is PjThe expansion effect value to this grid for the described competitor POI, n For different POI types sum.It is embodied as POI type PjDescribed competitor POI weightDeduct described decay step RankIt is multiplied by extension level k of competitor POI place grid described in this grid distance periphery；
According to described coefficient of competition DselfWith described coefficient of competition DroundCalculate the coefficient of competition C of described gridcompete, its Middle Ccompete=Dself+Dround.
S360, the poly- visitor's coefficient according to described grid, stop coefficient, search factor and coefficient of competition determine described grid Addressing coefficient.
Specifically, described poly- visitor's coefficient according to described grid, stop coefficient, described in search factor and coefficient of competition determine The addressing coefficient of grid can include：Poly- visitor's coefficient of described grid, stop coefficient, search factor and coefficient of competition are returned One change；According to normalization result, calculate the addressing coefficient C of described gridlocation.
Wherein, poly- visitor's coefficient of described grid, stop coefficient, search factor and coefficient of competition being normalized can profit Use arbitrary method for normalizing, for example, it may be 0 average standardization or linear function normalization.Optionally, calculate institute The method stating the addressing coefficient of grid can be by the normalization knot of poly- visitor's coefficient, stop coefficient and search factor of described grid Fruit is added, then the normalization result deducting the coefficient of competition of described grid；Can also the impact to addressing according to each coefficient Difference, by the normalization results added of poly- visitor's coefficient, stop coefficient and search factor of the described grid of different set ratio, then Deduct the normalization result of the coefficient of competition of described grid, as the addressing coefficient of described grid.
Specifically, described by described grid poly- visitor coefficient, stop coefficient, search factor and coefficient of competition normalization permissible Including：
By poly- visitor's coefficient of described grid, stop coefficient, search factor and coefficient of competition normalization, normalization formula is such as Under：
Wherein, original value is poly- visitor's coefficient value of described grid, and target area minimum of a value is target taking poly- visitor's coefficient as a example The minimum of a value of poly- visitor's coefficient of all grids in addressing region, target area maximum is all grids in target addressing region The maximum of poly- visitor's coefficient.By the normalization of above-mentioned function, original value can be transformed in the range of [0-1], thus dropping The negative effect of low inaccurate individually data, that is, improve the data precision, larger data be transformed into the scope of [0-1] simultaneously Interior, to accelerate calculating speed.
Specifically, described according to normalization result, calculate described grid addressing coefficient ClocationCan include：
According to normalization result, calculate the addressing coefficient C of described gridlocation, formula is as follows：
Clocation=K1×Vnorm-client+K2×Vnorm-stay+K3×Vnorm-query-K4×Vnorm-compete
Wherein, Vnorm-client、Vnorm-stay、Vnorm-query、Vnorm-competeFor poly- visitor's coefficient of described grid, stop system Value after number, search factor and coefficient of competition normalization, K1≥0,K2≥0,K3≥0,K4>=0, and require K1+K2+K3+K4=1. K1、K2、K3And K4According to the proportionality coefficient to the setting of the Different Effects of addressing for each coefficient, to improve the addressing of described grid The degree of accuracy of coefficient, and then improve the precision of addressing.
S370, the addressing coefficient according to described grid, select grid, as treating addressing main body from target addressing region Candidate site.
The technical scheme of the embodiment of the present invention, by arranging weight to POI different types of in target addressing region, determines The extension level of this grid distance periphery P OI place grid, and the decay step of each extension level is set, so that described net The result of calculation of the addressing coefficient of lattice is more accurate, and level is clearly more demarcated.
Fig. 4 is the flow chart of another kind of site selecting method that the embodiment of the present invention three provides.Referring to Fig. 4, in actual applications, Need to calculate poly- visitor's coefficient first, stop coefficient, search factor and coefficient of competition；Then to poly- visitor's coefficient of described grid, stop Coefficient, search factor and coefficient of competition is stayed to be normalized；Calculate addressing coefficient finally according to normalization result.
Wherein, gather being calculated as of visitor's coefficient：Filter out poly- visitor POI from map POI basic data, and this is gathered visitor POI Corresponding with the grid in target area, i.e. POI data gridding；Then count the number of the poly- visitor POI of different POI types in grid Amount；Finally according to statistics, the corresponding weight of different POI types that pre-sets, decay step and extension level, calculate net In lattice, the poly- visitor's effect with grid external expansion, obtains poly- visitor's coefficient.
Stop being calculated as of coefficient：The location information of target customer is filtered out from the data of positioning dwell point, and should Dwell data in location information is corresponding with the grid in target area, i.e. dwell data gridding；Then in statistics grid Dwell data, and stop coefficient is determined according to statistics.
Being calculated as of search factor：According to the search keyword determining, filter out from map inquiry data and treat addressing The search record of main body；Then Search Results are corresponding with the grid in target area according to customer position information, i.e. dragnet Format；The finally search temperature in statistics grid, and calculate search factor.
Being calculated as of coefficient of competition：Competition POI is filtered out from map POI data, and by this competition POI and target area Interior grid corresponds to, that is, compete POI data gridding；Then the quantity of the different competition POI types in statistics grid；Last root Result, the default different competition corresponding weights of POI type, decay step and extension level calculate in grid and grid according to statistics The competition performance of external expansion, obtains coefficient of competition.Wherein, map POI data is identical with above-mentioned map POI body data.
Example IV
Fig. 5 is a kind of structural representation of addressing device that the embodiment of the present invention four provides.The present embodiment is in above-mentioned reality A kind of addressing device proposing on the basis of applying example.Referring to Fig. 5, the addressing device that the present embodiment provides includes：Acquisition of information mould Block 10, stress and strain model module 20, addressing coefficient determination module 30 and candidate site determining module 40.
Wherein, data obtaining module 10, for when monitoring addressing event, obtaining mark and the target treating addressing main body Addressing region；Stress and strain model module 20, for carrying out stress and strain model to described target addressing region；Addressing coefficient determination module 30, according to the described associated data treating addressing main body and described target addressing region, determine the addressing coefficient of described grid；Candidate Address determination module 40, for the addressing coefficient according to described grid, selects grid, as treating addressing from target addressing region The candidate site of main body.
The technical scheme of the embodiment of the present invention, by according to the described association treating addressing main body and described target addressing region Data, determines the addressing coefficient of grid in target addressing region, then determines the time of addressing main body according to the addressing coefficient of grid Selection of land location.Thus eliminate using manpower collect described in treat the data of addressing main body and described target addressing region and utilize manpower The trouble that data is analyzed.And then solve manpower collect the addressing scope that data and analyze data bring not precisely, manpower High cost and the low problem of efficiency.
Further, described addressing coefficient determination module 30 includes：Factor determination unit and addressing factor determination unit.
Wherein, factor determination unit, for according to the described associated data treating addressing main body and described target addressing region, Determine poly- visitor's coefficient of described grid, at least one stopping in coefficient, search factor and coefficient of competition；Addressing coefficient determines single Unit, for according to poly- visitor's coefficient of described grid, stop coefficient, described at least one in search factor and coefficient of competition determine The addressing coefficient of grid.
Further, described stress and strain model module 20 includes：Construction area acquiring unit, size of mesh opening determining unit and net Lattice division unit.
Wherein, construction area acquiring unit, for obtaining the construction area determining in described addressing event；Size of mesh opening is true Order unit, for the building sides according to described construction area and/or the periphery point of interest POI treating the generation impact of addressing main body Long-pending, determine size of mesh opening；Stress and strain model unit, draws for carrying out grid according to described size of mesh opening to described target addressing region Point, and unique Marking the cell is corresponded to described grid mark.
Further, described addressing device, also includes：Weight setting module and extension level setup module.
Wherein, weight setting module, for according to the described mark treating addressing main body and described target addressing region Associated data, before determining the addressing coefficient of described grid, according to the Different Effects treating addressing main body, to target addressing region In different types of POI weight is set；
Extension level setup module, for the distance according to this grid and periphery P OI, determines this grid distance periphery P OI The extension level of place grid, and the decay step of each extension level is set.
Further, described factor determination unit includes：Target determination subelement, screening subelement, poly- visitor's statistics are single Unit, the first coefficient determination subelement, the second coefficient determination subelement and poly- visitor's coefficient determination subelement.
Wherein, for basis, target determination subelement, treats that addressing main body determines that target gathers visitor POI；
Screening subelement, gathers visitor for filtering out described target in the map POI basic data from described associated data POI；
Poly- visitor's statistics subelement, the quantity for the described target poly- visitor POI to the different POI types in this grid is carried out Statistics；
First coefficient determination subelement, for gathering the weight of visitor POI according to the described target in statistics and this grid, Calculate the poly- visitor effect coefficient V of this gridself；
Second coefficient determination subelement, gathers the weight of visitor POI, described decay step for the described target especially according to Home Network Rank and the extension level of the poly- visitor of target described in this grid distance periphery POI place grid, calculate target described in periphery and gather visitor POI couple The expansion effect coefficient V of this gridround；
Poly- visitor's coefficient determination subelement, for according to described poly- visitor effect coefficient VselfWith described expansion effect coefficient Vround Calculate the poly- visitor coefficient C of described gridclient, wherein Cclient=Vself+Vround.
Further, described first coefficient determination subelement includes：Poly- visitor's calculation of effect device.
Wherein, gather visitor's calculation of effect device, for calculating the poly- visitor effect coefficient V of this gridself, formula is as follows：
V s e l f = Σ i = 1 m W P i × N P i
Wherein,Expression POI type is PiCorresponding described target gathers the weight of visitor POI,Represent in this grid and contain POI type is had to be PiDescribed target gather visitor POI number.
Further, described second coefficient determination subelement includes：Expansion effect calculator.
Wherein, expansion effect calculator, gathers visitor's expansion effect coefficient to this grid for the POI for calculating target described in periphery Vround, formula is as follows：
V r o u n d = Σ j = 1 n E P j = Σ j = 1 n ( W P j - S P j × k )
Wherein,Represent that Home Network especially POI type is PjDescribed target gather visitor the expansion effect value to this grid for the POI, It is embodied as POI type PjDescribed target gather visitor POI weightDeduct described decay step and be multiplied by this grid distance week Target described in side gathers the extension level of visitor POI place grid.
Further, described factor determination unit includes：Target customer's determination subelement, system states filter subelement, state Statistics subelement and stop coefficient determination subelement.
Wherein, for basis, target customer's determination subelement, treats that addressing main body determines target customer crowd；
System states filter subelement, stops for the positioning from described associated data and filters out described target visitor in point data The active state data of family crowd；
Statistic subelement, for counting to described active state data；
Stop coefficient determination subelement, for according to the dwell point information in described active state data, by statistics Corresponding with the described grid in described target addressing region respectively, and described grid is determined according to the statistics of described grid Stop coefficient.
Further, described factor determination unit includes：Keyword determination subelement, record screening subelement, record system Meter subelement and search factor determination subelement.
Wherein, using described, keyword determination subelement, for treating that addressing main body, as target subject, determines target subject Search keyword；
Record screening subelement, for according to described search keyword, the map inquiry data from described associated data In filter out the search record of target subject and corresponding User Status；
Record statistics subelement, for counting to described search record；
Search factor determination subelement, for according to the customer position information in described User Status, statistics being divided Not corresponding with the described grid in described target addressing region, and searching of described grid is determined according to the statistics of described grid Rope coefficient.
Further, described factor determination unit includes：Competitor's determination subelement, competitor screening subelement, Grid corresponds to subelement, competition statistics subelement, the first competition determination subelement, the second competition determination subelement and coefficient of competition Determination subelement.
Wherein, competitor's determination subelement, for treating the same or analogous main body of addressing main body with described, is defined as Competitor；
Competitor screens subelement, filters out and institute in the map POI body data from described associated data State competitor corresponding competitor POI；
Grid correspond to subelement, for by described competitor POI respectively with described target addressing region in described net Lattice correspond to；
Competition statistics subelement, the quantity for the described competitor POI to the different POI types in this grid is carried out Statistics；
First competition determination subelement, for the weight according to the described competitor POI in statistics and this grid, Calculate the coefficient of competition D of this gridself, formula is as follows：
D s e l f = Σ i = 1 m W P i × N P i
Wherein,Expression POI type is PiThe weight of corresponding described competitor POI,Represent in this grid and contain POI type is had to be PiDescribed competitor's POI number；
Second competition determination subelement, for the weight of described competitor POI especially according to Home Network, described decay step Rank and the extension level of competitor POI place grid described in this grid distance periphery, calculate competitor POI couple described in periphery The coefficient of competition D of this gridround, formula is as follows：
D r o u n d = Σ j = 1 n E P j = Σ j = 1 n W P j - S P j × k
Wherein,Represent that Home Network especially POI type is PjThe expansion effect value to this grid for the described competitor POI, It is embodied as POI type PjDescribed competitor POI weightDeduct described decay step and be multiplied by this grid distance week The extension level of competitor POI place grid described in side；
Coefficient of competition determination subelement, for according to described coefficient of competition DselfWith described coefficient of competition DroundCalculate described The coefficient of competition C of gridcompete, wherein Ccompete=Dself+Dround.
Further, described addressing factor determination unit includes：Normalization subelement and addressing coefficient determination subelement.
Wherein, normalize subelement, for by poly- visitor's coefficient of described grid, stop coefficient, search factor and competition being Number normalization；Addressing coefficient determination subelement, for according to normalization result, calculating the addressing coefficient C of described gridlocation.
Further, described normalization subelement includes：Normalization calculator.
Wherein, normalize calculator, for by poly- visitor's coefficient of described grid, stop coefficient, search factor and competition being Number normalization, normalization formula is as follows：
Further, described addressing coefficient determination subelement includes：Addressing coefficient calculator.
Wherein, addressing coefficient calculator, for according to normalization result, calculating the addressing coefficient C of described gridlocation, Formula is as follows：
Clocation=K1×Vnorm-client+K2×Vnorm-stay+K3×Vnorm-query-K4×Vnorm-compete
Wherein, Vnorm-client、Vnorm-stay、Vnorm-query、Vnorm-competeFor poly- visitor's coefficient of described grid, stop system Value after number, search factor and coefficient of competition normalization, K1≥0,K2≥0,K3≥0,K4>=0, and require K1+K2+K3+K4=1.
Further, described target addressing region includes a city, administrative area, commercial circle or block.
Further, described addressing device, also includes：Mark module.
Wherein, mark module, in the addressing coefficient according to described grid, determine treat addressing main body candidate site it Afterwards, according to described addressing coefficient, described candidate site is marked at by different colours and is loaded with target addressing area map In figure layer.
The said goods can perform the method that any embodiment of the present invention is provided, and possesses the corresponding functional module of execution method And beneficial effect.
Note, above are only presently preferred embodiments of the present invention and institute's application technology principle.It will be appreciated by those skilled in the art that The invention is not restricted to specific embodiment described here, can carry out for a person skilled in the art various obvious changes, Readjust and substitute without departing from protection scope of the present invention.Therefore although being carried out to the present invention by above example It is described in further detail, but the present invention is not limited only to above example, without departing from the inventive concept, also Other Equivalent embodiments more can be included, and the scope of the present invention is determined by scope of the appended claims.

Claims (30)

1. a kind of site selecting method is it is characterised in that include：
When monitoring addressing event, obtain mark and the target addressing region treating addressing main body；
Stress and strain model is carried out to described target addressing region；
According to the described associated data treating addressing main body and described target addressing region, determine the addressing coefficient of described grid；
According to the addressing coefficient of described grid, select grid from target addressing region, as the candidate site treating addressing main body.
2. method according to claim 1 is it is characterised in that treat addressing main body and described target addressing region according to described Associated data, determine that the addressing coefficient of described grid includes：
According to the described associated data treating addressing main body and described target addressing region, determine poly- visitor's coefficient of described grid, stop Stay at least one in coefficient, search factor and coefficient of competition；
According to poly- visitor's coefficient of described grid, stop coefficient, at least one in search factor and coefficient of competition determines described net The addressing coefficient of lattice.
3. method according to claim 2 is it is characterised in that according to the described mark treating addressing main body and described target The associated data in addressing region, before determining the addressing coefficient of described grid, also includes：
According to the Different Effects treating addressing main body, weight is arranged to POI different types of in target addressing region；
According to the distance of this grid and periphery P OI, determine the extension level of this grid distance periphery P OI place grid, and arrange The decay step of each extension level.
4. method according to claim 3 is it is characterised in that treat addressing main body and described target addressing described in described basis The associated data in region, determines that poly- visitor's coefficient of described grid includes：
According to treat addressing main body determine target gather visitor POI；
Filter out described target in map POI basic data from described associated data and gather visitor POI；
The quantity of the described target poly- visitor POI of the different POI types in this grid is counted；
Gather the weight of visitor POI according to the described target in statistics and this grid, calculate poly- visitor's effect coefficient of this grid Vself；
Gather weight, described decay step and the target described in this grid distance periphery of visitor POI according to Home Network described target especially The extension level of poly- visitor POI place grid, calculates target described in periphery and gathers the visitor expansion effect coefficient V to this grid for the POIround；
According to described poly- visitor effect coefficient VselfWith described expansion effect coefficient VroundCalculate poly- visitor's coefficient of described grid Cclient, wherein Cclient=Vself+Vround.
5. method according to claim 4 it is characterised in that described according to the described target in statistics and this grid The weight of poly- visitor POI, calculates the poly- visitor effect coefficient V of this gridselfIncluding：
Calculate the poly- visitor effect coefficient V of this gridself, formula is as follows：
V s e l f = Σ i = 1 m W P i × N P i
Wherein,Expression POI type is PiCorresponding described target gathers the weight of visitor POI,Represent and in this grid, contain POI Type is PiDescribed target gather visitor POI number.
6. method according to claim 4 is it is characterised in that described gather visitor POI's according to Home Network described target especially Weight, described decay step and target described in this grid distance periphery gather the extension level of visitor POI place grid, calculate periphery institute State target and gather the visitor expansion effect coefficient V to this grid for the POIroundIncluding：
Calculate target described in periphery and gather the visitor expansion effect coefficient V to this grid for the POIround, formula is as follows：
V r o u n d = Σ j = 1 n E P j = Σ j = 1 n ( W P j - S P j × k )
Wherein,Represent that Home Network especially POI type is PjDescribed target gather visitor the expansion effect value to this grid for the POI, specifically It is expressed as POI type PjDescribed target gather visitor POI weightDeduct described decay stepIt is multiplied by this grid distance periphery Described target gathers extension level k of visitor POI place grid.
7. method according to claim 2 is it is characterised in that treat addressing main body and described target area described in described basis Associated data, determine that the stop coefficient of described grid includes：
According to treating that addressing main body determines target customer crowd；
Positioning from described associated data stops the active state data filtering out described target customer crowd in point data；
Described active state data is counted；
According to the dwell point information in described active state data, by statistics respectively with described target addressing region in institute State grid to correspond to, and determine the stop coefficient of described grid according to the statistics of described grid.
8. method according to claim 2 is it is characterised in that treat addressing main body and described target addressing described in described basis The associated data in region, determines that the search factor of described grid includes：
Treat that addressing main body, as target subject, determines the search keyword of described target subject using described；
According to described search keyword, in the map inquiry data from described associated data, filter out the search note of target subject Record and corresponding User Status；
Described search record is counted；
According to the customer position information in described User Status, by statistics respectively with described target addressing region in described in Grid corresponds to, and determines the search factor of described grid according to the statistics of described grid.
9. method according to claim 2 is it is characterised in that treat addressing main body and described target addressing described in described basis The associated data in region, determines that the coefficient of competition of described grid includes：
The same or analogous main body of addressing main body will be treated with described, be defined as competitor；
Competitor POI corresponding with described competitor is filtered out in map POI body data from described associated data；
Described competitor POI is corresponding with the described grid in described target addressing region respectively；
The quantity of the described competitor POI of the different POI types in this grid is counted；
According to the weight of the described competitor POI in statistics and this grid, calculate the coefficient of competition D of this gridself, public Formula is as follows：
D s e l f = Σ i = 1 m W P i × N P i
Wherein,Expression POI type is PiThe weight of corresponding described competitor POI,Represent in this grid and contain POI type is PiDescribed competitor's POI number；
Compete according to the weight of Home Network described competitor POI especially, described decay step and this grid distance periphery The extension level of main body POI place grid, calculates the coefficient of competition D to this grid for the competitor POI described in peripheryround, formula As follows：
D r o u n d = Σ j = 1 n E P j = Σ j = 1 n W P j - S P j × k
Wherein,Represent that Home Network especially POI type is PjThe expansion effect value to this grid for the described competitor POI, specifically It is expressed as POI type PjDescribed competitor POI weightDeduct described decay stepIt is multiplied by this grid distance periphery Extension level k of described competitor POI place grid；
According to described coefficient of competition DselfWith described coefficient of competition DroundCalculate the coefficient of competition C of described gridcompete, wherein Ccompete=Dself+Dround.
10. method according to claim 2 it is characterised in that described according to described grid poly- visitor coefficient, stop system The addressing coefficient of the described grid of at least one determination in number, search factor and coefficient of competition includes：
By poly- visitor's coefficient of described grid, at least one normalization stopping in coefficient, search factor and coefficient of competition；
According to normalization result, calculate the addressing coefficient C of described gridlocation.
11. methods according to right 10 are it is characterised in that described poly- visitor's coefficient by described grid, stop coefficient, search At least one normalization in coefficient and coefficient of competition includes：
By poly- visitor's coefficient of described grid, at least one normalization stopping in coefficient, search factor and coefficient of competition, normalization Formula is as follows：
12. methods according to claim 10 it is characterised in that described according to normalization result, calculate described grid Addressing coefficient ClocationIncluding：
According to normalization result, calculate the addressing coefficient C of described gridlocation, formula is as follows：
Clocation=K1×Vnorm-client+K2×Vnorm-stay+K3×Vnorm-query-K4×Vnorm-compete
Wherein, Vnorm-client、Vnorm-stay、Vnorm-query、Vnorm-competeFor poly- visitor's coefficient of described grid, stop coefficient, search Value after rope coefficient and coefficient of competition normalization, K1≥0,K2≥0,K3≥0,K4>=0, and require K1+K2+K3+K4=1.
13. methods according to claim 1 are it is characterised in that described carry out stress and strain model to described target addressing region Including：
Obtain the construction area determining in described addressing event；
According to the construction area of described construction area and/or the periphery point of interest POI treating the generation impact of addressing main body, determine net Lattice size；
Stress and strain model is carried out to described target addressing region according to described size of mesh opening, and corresponding to described grid mark unique Marking the cell.
14. methods according to claim 1 are it is characterised in that described target addressing region includes city, an administration Area, commercial circle or block.
15. methods according to claim 1 are it is characterised in that in the addressing coefficient according to described grid, determining and treat addressing After the candidate site of main body, also include：
According to described addressing coefficient, described candidate site is marked at by different colours and is loaded with target addressing area map In figure layer.
A kind of 16. addressing devices are it is characterised in that include：
Data obtaining module, for when monitoring addressing event, obtaining mark and the target addressing region treating addressing main body；
Stress and strain model module, for carrying out stress and strain model to described target addressing region；
Addressing coefficient determination module, according to the described associated data treating addressing main body and described target addressing region, determines described The addressing coefficient of grid；
Candidate site determining module, for the addressing coefficient according to described grid, selects grid from target addressing region, as Treat the candidate site of addressing main body.
17. devices according to claim 16 are it is characterised in that described addressing coefficient determination module includes：
Factor determination unit, described for according to the described associated data treating addressing main body and described target addressing region, determining Poly- visitor's coefficient of grid, at least one stopping in coefficient, search factor and coefficient of competition；
Addressing factor determination unit, for according to poly- visitor's coefficient of described grid, stop coefficient, in search factor and coefficient of competition The described grid of at least one determination addressing coefficient.
18. devices according to claim 17 are it is characterised in that also include：
Weight setting module, for according to described treat addressing main body mark and described target addressing region associated data, Before determining the addressing coefficient of described grid, according to the Different Effects treating addressing main body, to inhomogeneity in target addressing region The POI setting weight of type；
Extension level setup module, for the distance according to this grid and periphery P OI, determines that this grid distance periphery P OI is located The extension level of grid, and the decay step of each extension level is set.
19. devices according to claim 18 are it is characterised in that described factor determination unit includes：
For basis, target determination subelement, treats that addressing main body determines that target gathers visitor POI；
Screening subelement, gathers visitor POI for filtering out described target in the map POI basic data from described associated data；
Poly- visitor's statistics subelement, the quantity for the described target poly- visitor POI to the different POI types in this grid is united Meter；
First coefficient determination subelement, for gathering the weight of visitor POI according to the described target in statistics and this grid, calculates The poly- visitor effect coefficient V of this gridself；
Second coefficient determination subelement, for gathered according to Home Network described target especially the weight of visitor POI, described decay step and Target described in this grid distance periphery gathers the extension level of visitor POI place grid, calculates target described in periphery and gathers visitor POI to Home Network The expansion effect coefficient V of latticeround；
Poly- visitor's coefficient determination subelement, for according to described poly- visitor effect coefficient VselfWith described expansion effect coefficient VroundCalculate The poly- visitor coefficient C of described gridclient, wherein Cclient=Vself+Vround.
20. devices according to claim 19 are it is characterised in that described first coefficient determination subelement includes：
Poly- visitor's calculation of effect device, for calculating the poly- visitor effect coefficient V of this gridself, formula is as follows：
V s e l f = Σ i = 1 m W P i × N P i
Wherein,Expression POI type is PiCorresponding described target gathers the weight of visitor POI,Represent in this grid and contain POI type is PiDescribed target gather visitor POI number.
21. devices according to claim 19 are it is characterised in that described second coefficient determination subelement includes：
Expansion effect calculator, gathers the visitor expansion effect coefficient V to this grid for the POI for calculating target described in peripheryround, formula As follows：
V r o u n d = Σ j = 1 n E P j = Σ j = 1 n ( W P j - S P j × k )
Wherein,Represent that Home Network especially POI type is PjDescribed target gather visitor the expansion effect value to this grid for the POI, specifically It is expressed as POI type PjDescribed target gather visitor POI weightDeduct described decay stepIt is multiplied by this grid distance periphery Described target gathers extension level k of visitor POI place grid.
22. devices according to claim 17 are it is characterised in that described factor determination unit includes：
For basis, target customer's determination subelement, treats that addressing main body determines target customer crowd；
System states filter subelement, stops in point data for the positioning from described associated data and filters out described target customer people The active state data of group；
Statistic subelement, for counting to described active state data；
Stop coefficient determination subelement, for according to the dwell point information in described active state data, by statistics difference Corresponding with the described grid in described target addressing region, and the stop of described grid is determined according to the statistics of described grid Coefficient.
23. devices according to claim 17 are it is characterised in that described factor determination unit includes：
Using described, keyword determination subelement, for treating that addressing main body, as target subject, determines the search of described target subject Keyword；
Record screening subelement, for according to described search keyword, sieving in the map inquiry data from described associated data Select the search record of target subject and corresponding User Status；
Record statistics subelement, for counting to described search record；
Search factor determination subelement, for according to the customer position information in described User Status, by statistics respectively with Described grid in described target addressing region corresponds to, and determines the search system of described grid according to the statistics of described grid Number.
24. devices according to claim 17 are it is characterised in that described factor determination unit includes：
Competitor's determination subelement, for treating the same or analogous main body of addressing main body with described, is defined as competitor；
Competitor screens subelement, competing with described for filtering out in the map POI body data from described associated data Strive main body corresponding competitor POI；
Grid correspond to subelement, for by described competitor POI respectively with described target addressing region in described grid pair Should；
Competition statistics subelement, the quantity for the described competitor POI to the different POI types in this grid is united Meter；
First competition determination subelement, for the weight according to the described competitor POI in statistics and this grid, calculates The coefficient of competition D of this gridself, formula is as follows：
D s e l f = Σ i = 1 m W P i × N P i
Wherein,Expression POI type is PiThe weight of corresponding described competitor POI,Represent and in this grid, contain POI Type is PiDescribed competitor's POI number；
Second competition determination subelement, for the weight of described competitor POI especially according to Home Network, described decay step and The extension level of competitor POI place grid described in this grid distance periphery, calculates competitor POI described in periphery to Home Network The coefficient of competition D of latticeround, formula is as follows：
D r o u n d = Σ j = 1 n E P j = Σ j = 1 n W P j - S P j × k
Wherein,Represent that Home Network especially POI type is PjThe expansion effect value to this grid for the described competitor POI, specifically It is expressed as POI type PjDescribed competitor POI weightDeduct described decay stepIt is multiplied by this grid distance periphery Extension level k of described competitor POI place grid；
Coefficient of competition determination subelement, for according to described coefficient of competition DselfWith described coefficient of competition DroundCalculate described grid Coefficient of competition Ccompete, wherein Ccompete=Dself+Dround.
25. devices according to claim 17 are it is characterised in that described addressing factor determination unit includes：
Normalization subelement, for by poly- visitor's coefficient of described grid, stop coefficient, in search factor and coefficient of competition at least A kind of normalization；
Addressing coefficient determination subelement, for according to normalization result, calculating the addressing coefficient C of described gridlocation.
26. devices according to right 25 are it is characterised in that described normalization subelement includes：
Normalization calculator, for by poly- visitor's coefficient of described grid, stop coefficient, in search factor and coefficient of competition at least A kind of normalization, normalization formula is as follows：
27. devices according to claim 25 are it is characterised in that described addressing coefficient determination subelement includes：
Addressing coefficient calculator, for according to normalization result, calculating the addressing coefficient C of described gridlocation, formula is as follows：
Clocation=K1×Vnorm-client+K2×Vnorm-stay+K3×Vnorm-query-K4×Vnorm-compete
Wherein, Vnorm-client、Vnorm-stay、Vnorm-query、Vnorm-competeFor poly- visitor's coefficient of described grid, stop coefficient, search Value after rope coefficient and coefficient of competition normalization, K1≥0,K2≥0,K3≥0,K4>=0, and require K1+K2+K3+K4=1.
28. devices according to claim 16 are it is characterised in that described stress and strain model module includes：
Construction area acquiring unit, for obtaining the construction area determining in described addressing event；
Size of mesh opening determining unit, for according to described construction area and/or treat addressing main body produce impact periphery interest The construction area of point POI, determines size of mesh opening；
Stress and strain model unit, for carrying out stress and strain model according to described size of mesh opening to described target addressing region, and to described Grid mark corresponds to unique Marking the cell.
29. devices according to claim 16 are it is characterised in that described target addressing region includes city, an administration Area, commercial circle or block.
30. devices according to claim 16 are it is characterised in that also include：
Mark module, in the addressing coefficient according to described grid, after determining the candidate site treating addressing main body, according to institute State addressing coefficient, described candidate site is marked at by different colours in the figure layer being loaded with target addressing area map.
CN201610821849.4A 2016-09-13 2016-09-13 Site selection method and device Pending CN106384250A (en)

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CN108921605A (en) * 2018-06-25 2018-11-30 阿里巴巴集团控股有限公司 It is a kind of that framework and method are expanded based on the trade company of LBS and big data
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CN109345130A (en) * 2018-10-12 2019-02-15 深圳市和讯华谷信息技术有限公司 Method, apparatus, computer equipment and the storage medium of Market Site Selection
CN109447374A (en) * 2018-11-17 2019-03-08 朱学庆 A kind of new shop quick site selection method and apparatus based on big data analysis
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CN108628896A (en) * 2017-03-22 2018-10-09 腾讯科技（深圳）有限公司 It registers behavior temperature processing method and processing device
CN107220308A (en) * 2017-05-11 2017-09-29 百度在线网络技术（北京）有限公司 POI rational detection method and device, equipment and computer-readable recording medium
CN107220308B (en) * 2017-05-11 2021-07-20 百度在线网络技术（北京）有限公司 Method, device and equipment for detecting rationality of POI (Point of interest) and readable medium
CN108009677A (en) * 2017-11-29 2018-05-08 黑龙江鑫联华信息股份有限公司 A kind of site selecting method
CN108009677B (en) * 2017-11-29 2021-11-30 黑龙江鑫联华信息股份有限公司 Site selection method
CN107944767A (en) * 2017-12-21 2018-04-20 湖南大学 Selecting address on building method and its system based on BIM and electronic map
CN108154300A (en) * 2017-12-25 2018-06-12 东软集团股份有限公司 Point of interest site selecting method, device and computer equipment
CN108280685B (en) * 2018-01-19 2019-07-23 百度在线网络技术（北京）有限公司 Information acquisition method and device
CN108280685A (en) * 2018-01-19 2018-07-13 百度在线网络技术（北京）有限公司 Information acquisition method and device
CN108596520B (en) * 2018-05-16 2021-09-17 北京优网助帮信息技术有限公司 Restaurant site selection optimization method and device
CN108596520A (en) * 2018-05-16 2018-09-28 北京优网助帮信息技术有限公司 A kind of dining room Optimization Method for Location-Selection and device
CN108921605A (en) * 2018-06-25 2018-11-30 阿里巴巴集团控股有限公司 It is a kind of that framework and method are expanded based on the trade company of LBS and big data
CN108960912A (en) * 2018-06-27 2018-12-07 北京京东金融科技控股有限公司 Method and apparatus for determining target position
CN109345130B (en) * 2018-10-12 2021-03-16 深圳市和讯华谷信息技术有限公司 Method and device for commercial site selection, computer equipment and storage medium
CN109345130A (en) * 2018-10-12 2019-02-15 深圳市和讯华谷信息技术有限公司 Method, apparatus, computer equipment and the storage medium of Market Site Selection
CN109543888A (en) * 2018-11-07 2019-03-29 中国联合网络通信集团有限公司 Business hall position selecting method, device and storage medium
CN109447374A (en) * 2018-11-17 2019-03-08 朱学庆 A kind of new shop quick site selection method and apparatus based on big data analysis
CN109446244B (en) * 2018-12-06 2021-06-25 重庆协洽科技有限公司 Optimized site selection working method through big data mining
CN109446244A (en) * 2018-12-06 2019-03-08 重庆协洽科技有限公司 It is a kind of that Site Selection method is optimized by big data excavation
CN109636040A (en) * 2018-12-13 2019-04-16 杭州杰富睿科技有限公司 A kind of drinking-water point distributed intelligence system
CN109580883A (en) * 2018-12-17 2019-04-05 清远长天思源环保科技有限公司 A kind of miniature air station prime selected site device and method
CN111400417A (en) * 2018-12-28 2020-07-10 航天信息股份有限公司 Self-service tax service hall site selection method, device, medium and equipment
CN110019568B (en) * 2019-04-12 2022-03-11 深圳市和讯华谷信息技术有限公司 Spatial clustering-based addressing method and device, computer equipment and storage medium
CN110019568A (en) * 2019-04-12 2019-07-16 深圳市和讯华谷信息技术有限公司 Site selecting method, device, computer equipment and storage medium based on space clustering
CN110188937B (en) * 2019-05-23 2021-10-29 中国移动通信集团内蒙古有限公司 Business hall business scale prediction method, device, equipment and storage medium
CN110188937A (en) * 2019-05-23 2019-08-30 中国移动通信集团内蒙古有限公司 Business hall business scale prediction technique, device, equipment and storage medium
CN111311317A (en) * 2020-02-06 2020-06-19 大众问问(北京)信息科技有限公司 Information recommendation method, device, equipment and system
CN112785049A (en) * 2021-01-12 2021-05-11 北京首汽智行科技有限公司 Shared automobile city opening site selection method and system based on POI characteristics
CN113077181A (en) * 2021-04-22 2021-07-06 上海钧正网络科技有限公司 Parking station setting method, device, medium and electronic equipment
CN113240306A (en) * 2021-05-21 2021-08-10 河南高通物联网有限公司 Market site selection method and system based on artificial intelligence and big data
CN113240306B (en) * 2021-05-21 2023-01-13 吴晓冬 Market site selection method and system based on artificial intelligence and big data
CN115660739A (en) * 2022-12-27 2023-01-31 上海祺鲲信息科技有限公司 Urban business strategy data processing method

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Application publication date: 20170208