CN107402966A - The computational methods and device and electronic equipment of hunting zone - Google Patents
The computational methods and device and electronic equipment of hunting zone Download PDFInfo
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- CN107402966A CN107402966A CN201710487621.0A CN201710487621A CN107402966A CN 107402966 A CN107402966 A CN 107402966A CN 201710487621 A CN201710487621 A CN 201710487621A CN 107402966 A CN107402966 A CN 107402966A
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- destination object
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- customer location
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
Abstract
The application provides a kind of computational methods and device of hunting zone, and methods described includes：According to the searching request for destination object, it is determined that searching for the sum of the destination object；Obtain customer location；Obtain the density of destination object described in the grid that the customer location is located at；According to acquired density and identified sum, hunting zone is calculated.Using the embodiment of the present application, the hunting zone for meeting user's request can be calculated automatically.
Description
Technical field
The application is related to computing technique field, more particularly to a kind of computational methods of hunting zone and device and electronics are set
It is standby.
Background technology
With the continuous development of computer and Internet technology, service (LBS, Location are provided based on geographical position
Based Service) it is more and more.
In the service based on LBS, the function of being scanned for based on neighbouring geographic range is typically provided with.For example, search
Neighbouring cuisines, user can nearby eat the shop of cuisines by the functional inquiry.So, even if user is strange at one
City, the shops of needs can also be found.
In the prior art, the function of being scanned for based on neighbouring geographic range, being typically just to provide user, several are fixed
Hunting zone, selected by user.Hunting zone as shown in Figure 1 includes：1 kilometer, 3 kilometers, 5 kilometers, 10 kilometers
Etc..Then, the hunting zone selected according to user scans for.For example, user needs to search for cuisines, and select hunting zone
For 3 kilometers, then server be exactly in the kilometer range of radius 3 centered on user current location search meet cuisines this types
Shop.
However, in actual applications, the distribution in shop and unbalanced in different zones.The hunting zone of user's selection is small
, search out the shop number come very little (selectivity is very little)；The hunting zone of selection is big, searches out the shop number come again too
It is more；User generally requires repeatedly to select hunting zone just to eventually find suitable shop.Cause Consumer's Experience poor.
The content of the invention
The computational methods and device for a kind of hunting zone that the application provides, to solve user's body present in prior art
Test the problem of poor.
A kind of computational methods of the hunting zone provided according to the embodiment of the present application, methods described include：
According to the searching request for destination object, it is determined that searching for the sum of the destination object；
Obtain customer location；
Obtain the density of destination object described in the grid that the customer location is located at；
According to acquired density and identified sum, hunting zone is calculated.
Preferably, the density of destination object described in the grid for obtaining the customer location and being located at, is specifically included：
According to the coordinate of the customer location, grid corresponding to the coordinate is determined；The grid is gridding map；
Count the quantity of destination object described in the grid；
According to the quantity of the sizing grid and the destination object, the close of destination object described in the grid is calculated
Degree.
Preferably, the density of destination object described in the grid for obtaining the customer location and being located at, is specifically included：
According to the coordinate of the customer location, grid corresponding to the coordinate is determined；
From database, the density of destination object described in the grid is inquired about；Wherein：Target described in the database
Off-line calculation is drawn the density of object in the following way：
Gridding processing is carried out to map；
Count the quantity that the destination object is located in each grid；
According to the quantity and sizing grid of destination object in each described grid, mesh described in each grid is calculated
Mark the density of object.
Preferably, the calculating hunting zone passes through below equation：
Wherein, R represents hunting zone, and C represents to determine the sum of destination object, PI expression pis, acquired in E expressions
The density of destination object.
Preferably, the calculating hunting zone passes through below equation：
Wherein, R represents hunting zone, and C represents to determine the sum of destination object, PI expression pis, acquired in E expressions
The density of destination object, the ratio of the density of destination object between grid and adjacent mesh that the i expressions customer location is located at
Relation.
Preferably, the proportionate relationship, is calculated by following manner：
Obtain the density with destination object described in current grid adjacent mesh；
Count the first quantity that density is less than the adjacent mesh of destination object density in current grid；
Count the second quantity that density is more than or equal to the adjacent mesh of destination object density in current grid；
The ratio of first quantity and the second quantity is defined as density between the current grid and adjacent mesh
Proportionate relationship；Wherein, the current grid is the grid that the customer location is located at.
Preferably, the basis is directed to the searching request of destination object, it is determined that searching for the sum of the destination object, specifically
Including：
After the searching request for destination object is received, the sum selected during user's history search is obtained；
The sum selected recently is defined as this sum for searching for the destination object.
Preferably, the basis is directed to the searching request of destination object, it is determined that searching for the sum of the destination object, specifically
Including：
After the searching request for destination object is received, the sum selected during user's history search is obtained；
The sum for selecting number most is defined as this sum for searching for the destination object.
Preferably, the grid includes base station grid, wifi network lattice or map grid.
A kind of computing device of the hunting zone provided according to the embodiment of the present application, described device include：
Total determining unit, according to the searching request for destination object, it is determined that searching for the sum of the destination object；
Position acquisition unit, obtain customer location；
Density acquiring unit, obtain the density of destination object described in the grid that the customer location is located at；
Range calculation unit, according to acquired density and identified sum, calculate hunting zone.
Preferably, the density acquiring unit, is specifically included：
Grid determination subelement, according to the coordinate of the customer location, determine grid corresponding to the coordinate；The grid is
Gridding map；
Statistical magnitude subelement, count the quantity of destination object described in the grid；
Density computation subunit, according to the quantity of the sizing grid and the destination object, calculate in the grid
The density of the destination object.
Preferably, the density acquiring unit, is specifically included：
Grid determination subelement, according to the coordinate of the customer location, determine grid corresponding to the coordinate；
Density inquires about subelement, from database, inquires about the density of destination object described in the grid；Wherein：It is described
Off-line calculation is drawn the density of destination object described in database in the following way：
Gridding handles subelement, and gridding processing is carried out to map；
Statistical magnitude subelement, count the quantity that the destination object is located in each grid；
Density computation subunit, according to the quantity and sizing grid of destination object in each described grid, calculate every
The density of destination object described in one grid.
Preferably, the calculating hunting zone, passes through below equation：
Wherein, R represents hunting zone, and C represents to determine the sum of destination object, PI expression pis, acquired in E expressions
The density of destination object.
Preferably, the calculating hunting zone, passes through below equation：
Wherein, R represents hunting zone, and C represents to determine the sum of destination object, PI expression pis, acquired in E expressions
The density of destination object, the ratio of the density of destination object between grid and adjacent mesh that the i expressions customer location is located at
Relation.
Preferably, the proportionate relationship, it is calculated by following subelement：
Density obtains subelement, obtains the density with destination object described in current grid adjacent mesh；
First quantity statistics subelement, statistics density are less than first of the adjacent mesh of destination object density in current grid
Quantity；
Second quantity statistics subelement, statistics density are more than or equal to the adjacent mesh of destination object density in current grid
Second quantity；
Proportionate relationship determination subelement, by the ratio of first quantity and the second quantity be defined as the current grid with
The proportionate relationship of density between adjacent mesh；Wherein, the current grid is the grid that the customer location is located at.
Preferably, the total determining unit, is specifically included：
History sum obtains subelement, after the searching request for destination object is received, obtains user's history search
When the sum that selects；
Total determination subelement, the sum selected recently is defined as this sum for searching for the destination object.
Preferably, the total determining unit, is specifically included：
History sum obtains subelement, after the searching request for destination object is received, obtains user's history search
When the sum that selects；
Total determination subelement, the sum for selecting number most is defined as this sum for searching for the destination object.
Preferably, the grid includes base station grid, wifi network lattice or map grid.
The a kind of electronic equipment provided according to the embodiment of the present application, including：
Processor；
For storing the memory of processor-executable instruction；
Wherein, the processor is configured as：
According to the searching request for destination object, it is determined that searching for the sum of the destination object；
Obtain customer location；
Obtain the density of destination object described in the grid that the customer location is located at；
According to acquired density and identified sum, hunting zone is calculated.
In the embodiment of the present application, it with reference to need the distribution situation of destination object searched in user region, that is, use
Family position destination object within a grid density, further according to the sum for the destination object for needing to search for, calculate search automatically
The hunting zone of destination object.The hunting zone so calculated, i.e., not too large (cause search out quantity too many) not yet
Meeting too small (causing the quantity searched out very little), meet the search need of user.So, it is only necessary to once search for can and help
User finds the destination object of needs, avoids user from operating the problem of caused experience is poor repeatedly.
Brief description of the drawings
Fig. 1 is the schematic diagram that hunting zone is selected in the search interface that the application provides；
Fig. 2 is the flow chart of the computational methods for the hunting zone that the embodiment of the application one provides；
Fig. 3 is the total schematic diagram of selection target object in the search interface that the embodiment of the application one provides；
Fig. 4 is the schematic diagram for the gridding map that the embodiment of the application one provides；
Fig. 5 is the schematic diagram of the density of destination object in the current grid that the embodiment of the application one provides and adjacent mesh；
Fig. 6 is the module diagram of the computing device for the hunting zone that the embodiment of the application one provides.
Embodiment
Here exemplary embodiment will be illustrated in detail, its example is illustrated in the accompanying drawings.Following description is related to
During accompanying drawing, unless otherwise indicated, the same numbers in different accompanying drawings represent same or analogous key element.Following exemplary embodiment
Described in embodiment do not represent all embodiments consistent with the application.On the contrary, they be only with it is such as appended
The example of the consistent apparatus and method of some aspects be described in detail in claims, the application.
It is only merely for the purpose of description specific embodiment in term used in this application, and is not intended to be limiting the application.
" one kind " of singulative used in the application and appended claims, " described " and "the" are also intended to including majority
Form, unless context clearly shows that other implications.It is also understood that term "and/or" used herein refers to and wrapped
Containing the associated list items purpose of one or more, any or all may be combined.
It will be appreciated that though various information, but this may be described using term first, second, third, etc. in the application
A little information should not necessarily be limited by these terms.These terms are only used for same type of information being distinguished from each other out.For example, do not departing from
In the case of the application scope, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as
One information.Depending on linguistic context, word as used in this " if " can be construed to " ... when " or " when ...
When " or " in response to determining ".
In order to solve the above problems, Fig. 2 is referred to, the computational methods of the hunting zone provided for the embodiment of the application one
Flow chart, comprise the following steps：
Step 110：According to the searching request for destination object, it is determined that searching for the sum of the destination object.
In general, user can input the destination object for wanting search in search box, so as to providing search service
Server sends the searching request for the destination object.
In one implementation, the sum of the destination object can be user's manually determined.
It is to be understood that the sum for searching for the destination object is carried in the searching request；In this way, service end can
According to the searching request for being directed to destination object, to obtain this and search the sum that the destination object is searched in carrying in element request.
For example, search interface schematic diagram as shown in Figure 3, user inputs the target for wanting search in search box 31
Object is " cuisines ".Nearby under function of search, there is provided there is the selection of multiple shop quantity, including：15,20,40,50
Family etc..User oneself can select to need the shop quantity searched for.Assuming that user have selected " 40 ", then server can
It is determined that the sum for searching for the destination object " cuisines " is 40.
In another implementation, the sum of the destination object can also be that server is true according to user's history data
Fixed.
For example, server selects when after the searching request for destination object is received, can obtain user's history search
The sum selected, the sum selected recently is defined as to the sum of this search destination object.For example, last user have selected 20
Family, then this search destination object is also using 20.
For another example when server after the searching request for destination object is received, can obtain user's history search
The sum of selection, the sum for selecting number most is defined as to the sum of this search destination object.For example, user's history selects
The number of 20 is most, then this search destination object also uses 20.
Step 120：Obtain customer location.
In general, the customer location can be the geographical position that user is currently located.
The customer location can be the location of such as user terminal (such as mobile phone), can be recorded through the user terminal
What the positioner of positional information was recorded, represent the coordinate information of position.Common positioner can be defended using GPS of America
Star navigation system, European " Galileo " satellite navigation system, Russian GLONASS satellites navigation system, or Chinese Beidou
Satellite navigation system etc., or similar combination.The coordinate information of this kind of positioning is also referred to as running fix.
The customer location can also be what signal characteristic of the network equipment based on user terminal was converted to, such as by net
Using base station covering principle, the position being calculated by the signal of the user terminal by architecture is believed for network operator
Breath.In such location Calculation, typically by the down-bound pilot frequency signal of user terminal measurement different base station, obtain under different base station
Row pilot tone due in (Time of Arrival, TOA) or reaching time-difference (Time Difference of Arrival,
TDOA), according to the measurement result and the coordinate of combination base station, triangle formula algorithm for estimating typically is used, so as to calculate user
The position of terminal.Actual location-estimation algorithm needs to consider the situation of (3 or more than the 3) positioning in more base stations, prior art
In have many algorithms, it is complex.In general, the number of base stations of moving table measuring is more, measurement accuracy is higher, positioning performance
Improve more obvious.
The customer location can also be what the wifi network based on user terminal access determined.For example, user terminal connects
The wifi network of certain market offer is entered, so as to using the position where the market as customer location.
Using the combination of above-mentioned multiple positioning modes, customer location more can be accurately positioned.
Certainly, user can also select an other geographical position as customer location.For example, user is currently in A positions
Put, prepare to go B location to have a meal at night, when selecting the shop to be gone in advance, it is possible to select B location as customer location.
User terminal can be uploaded to service end after it located customer location, so that the service end can obtain
Take customer location.
Step 130：Obtain the density of destination object described in the grid that the customer location is located at.
The grid can include base station grid, wifi network lattice or map grid.
The region that the wireless base station that the base station grid is for example established according to Virtual network operator can cover is carried out to map
Mesh generation.
Similarly, the wifi network lattice for example carry out mesh generation according to the region that wifi can be covered to map.
The map grid, gridding is carried out by map and handles to obtain.
It is illustrated by taking gridding map as an example：
Implementation 1：
The step 130, is specifically included：
According to the coordinate of the customer location, grid corresponding to the coordinate is determined；The grid is gridding map；
Count the quantity of destination object described in the grid；
According to the quantity of the sizing grid and the destination object, the close of destination object described in the grid is calculated
Degree.
In the embodiment, the map can be the map area where the customer location, such as residing for the user
City map.
The gridding processing, can be that map is divided into some grids according to default area.It refer to shown in Fig. 4
The gridding map grid schematic diagram before and after the processing provided for the application.The default size can artificially be set in advance
Fixed.In general, area is smaller, the number of grid of division will be more, although number of grid can finally to calculate more
Hunting zone it is more accurate, but cost (including calculating cost, time cost etc.) is also bigger；Area is bigger, the grid of division
Quantity is fewer, although number of grid can make it that cost is also few less, can cause the hunting zone inaccuracy finally calculated.
Therefore, optimal area can be drawn based on mass data and using machine learning techniques off-line training so that cost and
Accuracy can ensure business needs.
Generally, customer location can be the coordinate of a longitude and latitude；And map is also based on the coordinate exploitation of longitude and latitude,
Therefore, after gridding processing, the coordinate range of each grid is confirmable.Pass through the coordinate bit of computed user locations
In the grid for customer location is assured that in the coordinate range of which grid being located at.
In general, there is provided business service side can collect mass data, for example, in map navigation service, service side can receive
Collect the information such as the address in all shops, title in map.Based on this, server can counts destination object in the grid
Quantity.
Incorporated by reference to shown in Fig. 3, Fig. 4, i.e. the destination object of user's input is " cuisines "；Then server is determining user position
After residing grid is put as the grid 41 in Fig. 4, it is possible to by the shop for belonging to " cuisines " type or label in the grid
Quantity.It is assumed that statistics show in grid 41 that the shop quantity of " cuisines " is 30；" cuisines " shop can be then calculated in grid 41
Density：
Specifically, the area of quantity/grid of density=destination object；Will " cuisines " shop quantity 21 divided by grid
41 area；Assuming that gridding process is divided according to the area of 0.6 sq-km, then in the example, density=30/0.6
=50 (individual/sq-kms).
Implementation 2：
The step 130, it can specifically include：
According to the coordinate of the customer location, grid corresponding to the coordinate is determined；
From database, the density of destination object described in the grid is inquired about；Wherein, target described in the database
Off-line calculation obtains the density of object in the following way：
Gridding processing is carried out to map；
Count the quantity that the destination object is located in each grid；
According to the quantity and sizing grid of destination object in each described grid, mesh described in each grid is calculated
Mark the density of object.
The embodiment difference of the embodiment and implementation 1 is, the customer location position is obtained in implementation 1
In grid described in destination object density, calculate in real time；The present embodiment is then precalculated, is needing to obtain
Described in the grid that the customer location is located at during the density of destination object, inquired about from database, so as to improve effect
Rate.
In the embodiment, the density calculating process of destination object is identical with above-mentioned implementation 1 in each grid, this
Place repeats no more.
In actual applications, the density of destination object is always continually changing, for example, can all have daily newly hold shop,
And the shop closed, therefore, in order to ensure the accurate of data, data can generally periodically update in database, this
Sample can make it that the density of destination object in each grid is newest.For example, being updated according to T+1 days, that is, collect the T days
Data, and in being calculated the T days at the T+1 days in each grid each destination object density.
It is noted that off-line calculation does not interfere with being normally carried out for business on line；And off-line data is calculating effect
It is higher in rate, for example, off-line data be pre-cache it is good without being downloaded temporarily.
It should be noted that in same grid, the density of different target object can be different.With reality
Border search exemplified by, for different target object such as " cuisines ", " KTV ", " supermarket ", " hotel " density generally all differ
's.
Step 140：According to acquired density and identified sum, hunting zone is calculated.
In the present embodiment, it is being determined that user needs to search for the sum of destination object, and is getting customer location and be located at
Grid in destination object density after, it is possible to the automatic hunting zone for calculating search destination object.
Specifically, the calculating hunting zone can pass through equation below 1：
Wherein, R represents hunting zone, and C represents to determine the sum of destination object, PI expression pis, acquired in E expressions
The density of destination object.
Illustrate, it is assumed that the sum of identified destination object is 50；Acquired customer location is located in grid
The density of destination object is 30；
Then,
Afterwards, server according to the hunting zone calculated with regard to scanning for.
As a rule, the hunting zone can be search radius.Search radius scope i.e. centered on customer location
Interior search destination object.Such as the hunting zone being calculated in above-mentioned example is when being 0.7km, you can with using customer location in
Search destination object in the kilometer range of radius 0.7 of the heart.Assuming that destination object is " cuisines ", then server using customer location in
The shop of search " cuisines " in the kilometer range of radius 0.7 of the heart.
Certainly, in other embodiments, the hunting zone can be not limited to search radius, can also for example search for
The 0.7km being calculated in the length of side, such as above-mentioned example, using customer location as summit or the square of 0.7 kilometer of the length of side at center
Destination object is searched in shape region.It is appreciated that the region of search determined with the hunting zone can be the area of arbitrary shape
Domain.
By embodiment, due to the distribution situation of destination object that with reference to need in user region to search for, that is, use
Family position destination object within a grid density, further according to the sum for the destination object for needing to search for, it is possible to automatic meter
Calculate the hunting zone of search destination object.The hunting zone so calculated, i.e., it is not too large (to cause the quantity searched out too
It is more) also will not too small (causing the quantity searched out very little), meet the search need of user.So, it is only necessary to once search for just
User can be helped to find the destination object of needs, avoid user from operating the problem of caused experience is poor repeatedly.
, may be due to ginseng only with reference to the density of destination object in current grid where customer location in above-mentioned formula 1
The problem of accuracy for the smaller and existing final calculating hunting zone of grid scope examined is not high；Therefore, in actual applications,
The density with destination object in current grid adjacent mesh can also be referred to；In this way, can be adjusted to formula 1, draw as
Lower formula 2：
Wherein, R represents hunting zone, and C represents to determine the sum of destination object, PI expression pis, acquired in E expressions
The density of destination object, the ratio of the density of destination object between grid and adjacent mesh that the i expressions customer location is located at
Relation.
The proportionate relationship can be calculated in the following way：
Obtain the density with destination object described in current grid adjacent mesh；
Count the first quantity that density is less than the adjacent mesh of destination object density in current grid；
Count the second quantity that density is more than or equal to the adjacent mesh of destination object density in current grid；
The ratio of first quantity and the second quantity is defined as density between the current grid and adjacent mesh
Proportionate relationship；Wherein, the current grid is the grid that the customer location is located at.
As shown in figure 5, the density of destination object is 30 in current grid；
The density of destination object is 35 in adjacent mesh 1；
The density of destination object is 40 in adjacent mesh 2；
The density of destination object is 35 in adjacent mesh 3；
The density of destination object is 20 in adjacent mesh 4；
The density of destination object is 30 in adjacent mesh 5；
The density of destination object is 32 in adjacent mesh 6；
The density of destination object is 9 in adjacent mesh 7；
The density of destination object is 12 in adjacent mesh 8；
Then, the first quantity that density is less than the adjacent mesh of destination object density (35) in current grid is 3；
The second quantity that density is more than or equal to the adjacent mesh of destination object density (35) in current grid is 5；
Therefore, the proportionate relationship of density is 3/5 between the customer location is located at grid and adjacent mesh.
Still continue to use the example in above-mentioned steps 140, use the hunting zone that formula 1 is calculated for
And by the present embodiment, after adding proportionate relationship, the hunting zone being calculated is then
It is adjacent with current grid due to reference to relative to the foregoing hunting zone calculated using formula 1, the present embodiment
The density of destination object in grid, so the hunting zone calculated is more accurate.
Corresponding with the computational methods embodiment of the hunting zone described in earlier figures 1, present invention also provides one kind to search for
The embodiment of the computing device of scope.Described device embodiment can be realized by software, can also pass through hardware or soft or hard
The mode that part combines is realized.It is the place by equipment where it as the device on a logical meaning exemplified by implemented in software
Corresponding computer program instructions in nonvolatile memory are read what operation in internal memory was formed by reason device.From hardware view
Speech, a kind of hardware configuration of equipment where the computing device of the application hunting zone can include processor, network interface, internal memory
And outside nonvolatile memory, the actual work(of calculating of equipment in embodiment where device generally according to the hunting zone
Can, other hardware can also be included, this is repeated no more.
Referring to Fig. 6, the module map of the computing device of the hunting zone provided for the embodiment of the application one, described device bag
Include：
Total determining unit 310, according to the searching request for destination object, it is determined that searching for the total of the destination object
Number；
Position acquisition unit 320, obtain customer location；
Density acquiring unit 330, obtain the density of destination object described in the grid that the customer location is located at；
Range calculation unit 340, according to acquired density and identified sum, calculate hunting zone.
In an optional embodiment：
The density acquiring unit 330, is specifically included：
Grid determination subelement, according to the coordinate of the customer location, determine grid corresponding to the coordinate；The grid is
Gridding map；
Statistical magnitude subelement, count the quantity of destination object described in the grid；
Density computation subunit, according to the quantity of the sizing grid and the destination object, calculate in the grid
The density of the destination object.
In an optional embodiment：
The density acquiring unit 330, is specifically included：
Grid determination subelement, according to the coordinate of the customer location, determine grid corresponding to the coordinate；
Density inquires about subelement, from database, inquires about the density of destination object described in the grid；Wherein：It is described
Off-line calculation is drawn the density of destination object described in database in the following way：
Gridding handles subelement, and gridding processing is carried out to map；
Statistical magnitude subelement, count the quantity that the destination object is located in each grid；
Density computation subunit, according to the quantity and sizing grid of destination object in each described grid, calculate every
The density of destination object described in one grid.
In an optional embodiment：
Plain scope is searched in the calculating, passes through below equation：
Wherein, R represents hunting zone, and C represents to determine the sum of destination object, PI expression pis, acquired in E expressions
The density of destination object.
In an optional embodiment：
Plain scope is searched in the calculating, passes through below equation：
Wherein, R represents hunting zone, and C represents to determine the sum of destination object, PI expression pis, acquired in E expressions
The density of destination object, the ratio of the density of destination object between grid and adjacent mesh that the i expressions customer location is located at
Relation.
In an optional embodiment：
The proportionate relationship, it is calculated by following subelement：
Density obtains subelement, obtains the density with destination object described in current grid adjacent mesh；
First quantity statistics subelement, statistics density are less than first of the adjacent mesh of destination object density in current grid
Quantity；
Second quantity statistics subelement, statistics density are more than or equal to the adjacent mesh of destination object density in current grid
Second quantity；
Proportionate relationship determination subelement, by the ratio of first quantity and the second quantity be defined as the current grid with
The proportionate relationship of density between adjacent mesh；Wherein, the current grid is the grid that the customer location is located at.
In an optional embodiment：
The total determining unit 310, is specifically included：
History sum obtains subelement, after the searching request for destination object is received, obtains user's history search
When the sum that selects；
Total determination subelement, the sum selected recently is defined as this sum for searching for the destination object.
In an optional embodiment：
The total determining unit 310, is specifically included：
History sum obtains subelement, after the searching request for destination object is received, obtains user's history search
When the sum that selects；
Total determination subelement, the sum for selecting number most is defined as this sum for searching for the destination object.
In an optional embodiment：
The grid includes base station grid, wifi network lattice or map grid.
System, device, module or the unit that above-described embodiment illustrates, it can specifically be realized by computer chip or entity,
Or realized by the product with certain function.One kind typically realizes that equipment is computer, and the concrete form of computer can
To be personal computer, laptop computer, cell phone, camera phone, smart phone, personal digital assistant, media play
In device, navigation equipment, E-mail receiver/send equipment, game console, tablet PC, wearable device or these equipment
The combination of any several equipment.
The function of unit and the implementation process of effect specifically refer to and step are corresponded in the above method in said apparatus
Implementation process, it will not be repeated here.
For device embodiment, because it corresponds essentially to embodiment of the method, so related part is real referring to method
Apply the part explanation of example.Device embodiment described above is only schematical, wherein described be used as separating component
The unit of explanation can be or may not be physically separate, can be as the part that unit is shown or can also
It is not physical location, you can with positioned at a place, or can also be distributed on multiple NEs.Can be according to reality
Need to select some or all of module therein to realize the purpose of application scheme.Those of ordinary skill in the art are not paying
In the case of going out creative work, you can to understand and implement.
Figure 6 above describes inner function module and the structural representation of the computing device of hunting zone, and it is substantial to hold
Row main body can be a kind of electronic equipment, including：
Processor；
For storing the memory of processor-executable instruction；
Wherein, the processor is configured as：
According to the searching request for destination object, it is determined that searching for the sum of the destination object；
Obtain customer location；
Obtain the density of destination object described in the grid that the customer location is located at；
According to acquired density and identified sum, hunting zone is calculated.
In the embodiment of above-mentioned electronic equipment, it should be appreciated that the processor can be CPU (English：
Central Processing Unit, referred to as：CPU), it can also be other general processors, digital signal processor (English：
Digital Signal Processor, referred to as：DSP), application specific integrated circuit (English：Application Specific
Integrated Circuit, referred to as：ASIC) etc..General processor can be microprocessor or the processor can also be
Any conventional processor etc., and foregoing memory can be read-only storage (English：Read-only memory, abbreviation：
ROM), random access memory (English：Random access memory, referred to as：RAM), flash memory, hard disk or solid
State hard disk.The step of method with reference to disclosed in the embodiment of the present invention, can be embodied directly in hardware processor and perform completion, or
Hardware and software module combination in person's processor perform completion.
Each embodiment in this specification is described by the way of progressive, identical similar portion between each embodiment
Divide mutually referring to what each embodiment stressed is the difference with other embodiment.Set especially for electronics
For standby embodiment, because it is substantially similar to embodiment of the method, so description is fairly simple, related part is real referring to method
Apply the part explanation of example.
Those skilled in the art will readily occur to the application its after considering specification and putting into practice invention disclosed herein
Its embodiment.The application is intended to any modification, purposes or the adaptations of the application, these modifications, purposes or
Person's adaptations follow the general principle of the application and including the undocumented common knowledges in the art of the application
Or conventional techniques.Description and embodiments are considered only as exemplary, and the true scope of the application and spirit are by following
Claim is pointed out.
It should be appreciated that the precision architecture that the application is not limited to be described above and is shown in the drawings, and
And various modifications and changes can be being carried out without departing from the scope.Scope of the present application is only limited by appended claim.
Claims (10)
1. a kind of computational methods of hunting zone, methods described include：
According to the searching request for destination object, it is determined that searching for the sum of the destination object；
Obtain customer location；
Obtain the density of destination object described in the grid that the customer location is located at；
According to acquired density and identified sum, hunting zone is calculated.
2. according to the method for claim 1, destination object described in the grid for obtaining the customer location and being located at
Density, specifically include：
According to the coordinate of the customer location, grid corresponding to the coordinate is determined；The grid is gridding map；
Count the quantity of destination object described in the grid；
According to the quantity of the sizing grid and the destination object, the density of destination object described in the grid is calculated.
3. according to the method for claim 1, destination object described in the grid for obtaining the customer location and being located at
Density, specifically include：
According to the coordinate of the customer location, grid corresponding to the coordinate is determined；
From database, the density of destination object described in the grid is inquired about；Wherein：Destination object described in the database
Density off-line calculation is drawn in the following way：
Gridding processing is carried out to map；
Count the quantity that the destination object is located in each grid；
According to the quantity and sizing grid of destination object in each described grid, target pair described in each grid is calculated
The density of elephant.
4. according to the method for claim 1, the calculating hunting zone passes through below equation：
<mrow>
<mi>R</mi>
<mo>=</mo>
<msqrt>
<mrow>
<mi>C</mi>
<mo>/</mo>
<mrow>
<mo>(</mo>
<mi>P</mi>
<mi>I</mi>
<mo>*</mo>
<mi>E</mi>
<mo>)</mo>
</mrow>
</mrow>
</msqrt>
<mo>;</mo>
</mrow>
Wherein, R represents hunting zone, and C represents to determine the sum of destination object, and PI represents pi, target acquired in E expressions
The density of object.
5. according to the method for claim 1, the calculating hunting zone passes through below equation：
<mrow>
<mi>R</mi>
<mo>=</mo>
<msqrt>
<mrow>
<mi>C</mi>
<mo>*</mo>
<mi>i</mi>
<mo>/</mo>
<mrow>
<mo>(</mo>
<mi>P</mi>
<mi>I</mi>
<mo>*</mo>
<mi>E</mi>
<mo>)</mo>
</mrow>
</mrow>
</msqrt>
<mo>;</mo>
</mrow>
Wherein, R represents hunting zone, and C represents to determine the sum of destination object, and PI represents pi, target acquired in E expressions
The density of object, the proportionate relationship of the density of destination object between grid and adjacent mesh that the i expressions customer location is located at.
6. according to the method for claim 5, the proportionate relationship, it is calculated by following manner：
Obtain the density with destination object described in current grid adjacent mesh；
Count the first quantity that density is less than the adjacent mesh of destination object density in current grid；
Count the second quantity that density is more than or equal to the adjacent mesh of destination object density in current grid；
The ratio of first quantity and the second quantity is defined as to the ratio of density between the current grid and adjacent mesh
Relation；Wherein, the current grid is the grid that the customer location is located at.
7. according to the method for claim 1, the basis is directed to the searching request of destination object, it is determined that searching for the target
The sum of object, is specifically included：
After the searching request for destination object is received, the sum selected during user's history search is obtained；
The sum selected recently is defined as this sum for searching for the destination object.
8. according to the method for claim 1, the basis is directed to the searching request of destination object, it is determined that searching for the target
The sum of object, is specifically included：
After the searching request for destination object is received, the sum selected during user's history search is obtained；
The sum for selecting number most is defined as this sum for searching for the destination object.
9. a kind of computing device of hunting zone, described device include：
Total determining unit, according to the searching request for destination object, it is determined that searching for the sum of the destination object；
Position acquisition unit, obtain customer location；
Density acquiring unit, obtain the density of destination object described in the grid that the customer location is located at；
Range calculation unit, according to acquired density and identified sum, calculate hunting zone.
10. a kind of electronic equipment, including：
Processor；
For storing the memory of processor-executable instruction；
Wherein, the processor is configured as：
According to the searching request for destination object, it is determined that searching for the sum of the destination object；
Obtain customer location；
Obtain the density of destination object described in the grid that the customer location is located at；
According to acquired density and identified sum, hunting zone is calculated.
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|---|---|---|---|
| CN201710487621.0A CN107402966A (en) | 2017-06-23 | 2017-06-23 | The computational methods and device and electronic equipment of hunting zone |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201710487621.0A CN107402966A (en) | 2017-06-23 | 2017-06-23 | The computational methods and device and electronic equipment of hunting zone |
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