CN109522374A - A kind of localization method, device, electronic equipment and readable storage medium storing program for executing - Google Patents
A kind of localization method, device, electronic equipment and readable storage medium storing program for executing Download PDFInfo
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Abstract
The present invention provides a kind of localization method and devices, which comprises obtains user for the multi-medium data in the behavioral data of business object；Extract generation time and the anchor point of the multi-medium data；The anchor point is clustered, one or more clustering clusters are obtained；According to the positioning points in the generation time and each clustering cluster, optimum cluster cluster is determined；It is determined as the standard setting point of the business object according to the centre spot in the optimum cluster cluster.It solves the problems, such as that error present in existing location technology is high, yield poor results and be not easy to execute, standard setting point can be determined by the anchor point of the multi-medium data in user behavior data.
Description
Technical field
The present embodiments relate to field of locating technology more particularly to a kind of localization methods and device.
Background technique
In field of locating technology, such as in O2O, map class application, the ten million even POI of more than one hundred million ranks are included on line
(Point of Interest, point of interest) data, i.e., in GIS-Geographic Information System, a POI can be a house, one
Retail shop, a mailbox, a bus station etc., the positioning accuracy of these POI datas is particularly important, influences very on user experience
Greatly.
In the prior art, the scheme calibrated to POI coordinate, mainly includes the following three types: by address inverse, or
By acquiring on the spot, multi-source fusion algorithm.
However, address inverse refers to, by the address of POI, reckoning obtains its latitude and longitude coordinates, can there is biggish mistake
Difference.Adopt and refer in fact, artificial team is arranged to sweep the streets, under line the address POI and latitude and longitude coordinates acquired on the spot, due to
Artificial carelessness bring mistake and human cost are very high, are often unable to ensure timeliness.Longitude and latitude multi-source calibration algorithm is
A kind of sort algorithm based on space density, needs to rely on too many data source, it is desirable that covering trade company is more, and without using picture
In include location information.
Summary of the invention
The present invention provides a kind of localization method and device, to solve the above problem in the prior art.
According to the first aspect of the invention, a kind of localization method is provided, which comprises
User is obtained for the multi-medium data in the behavioral data of business object；
Extract generation time and the anchor point of the multi-medium data；
The anchor point is clustered, one or more clustering clusters are obtained；
According to the positioning points in the generation time and each clustering cluster, optimum cluster cluster is determined；
It is determined as the standard setting point of the business object according to the centre spot in the optimum cluster cluster.
According to the second aspect of the invention, a kind of positioning device is provided, described device includes:
Multi-medium data obtains module, for obtaining user for the multi-medium data in the behavioral data of business object；
Data information obtains module, for extracting generation time and the anchor point of the multi-medium data；
Cluster module obtains one or more clustering clusters for clustering to the anchor point；
Optimum cluster cluster determining module, for being counted according to the positioning in the generation time and each clustering cluster,
Determine optimum cluster cluster；
Standard setting point determining module, for being determined as the business according to the centre spot in the optimum cluster cluster
The standard setting point of object.
According to the third aspect of the invention we, a kind of electronic equipment is provided, comprising:
Processor, memory and it is stored in the computer journey that can be run on the memory and on the processor
Sequence, the processor realize method above-mentioned when executing described program.
According to the fourth aspect of the invention, provide a kind of readable storage medium storing program for executing, when the instruction in the storage medium by
When the processor of electronic equipment executes, so that electronic equipment is able to carry out method above-mentioned.
The embodiment of the invention provides a kind of localization method and device, described includes: to obtain user for business object
Multi-medium data in behavioral data；Extract generation time and the anchor point of the multi-medium data；The anchor point is carried out
Cluster, obtains one or more clustering clusters；According to the positioning points in the generation time and each clustering cluster, determine
Optimum cluster cluster out；It is determined as the standard setting point of the business object according to the centre spot in the optimum cluster cluster.
It solves the problems, such as that error present in existing location technology is high, yield poor results and be not easy to execute, user behavior data can be passed through
In the anchor point of multi-medium data determine standard setting point.To efficiently, simply obtain anchor point.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by institute in the description to the embodiment of the present invention
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the invention
Example, for those of ordinary skill in the art, without any creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is a kind of specific steps flow chart for localization method that the embodiment of the present invention one provides；
Fig. 2 is a kind of specific steps flow chart of localization method provided by Embodiment 2 of the present invention；
Fig. 2A is data processing example flow diagram provided by Embodiment 2 of the present invention；
Fig. 3 is a kind of structure chart for positioning device that the embodiment of the present invention three provides；
Fig. 4 is a kind of structure chart for positioning device that the embodiment of the present invention four provides.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
Embodiment one
Referring to Fig.1, a kind of specific steps flow chart of the localization method provided it illustrates the embodiment of the present invention one.
Step 101, user is obtained for the multi-medium data in the behavioral data of business object；
In the embodiment of the present invention, user is behavioral data in the data for carrying out various operations for a business object, wherein
Including the scene description figure that user comment data, trade company upload, the error information of user's addition, crowdsourcing task, user's notes etc..
Specifically, multi-medium data therein, i.e. image or video data are obtained in numerous user behavior datas.
It is to be appreciated that trade company is also one of the user using application platform.
It is to be appreciated that above-mentioned multi-medium data is unexpected in addition to including image or video data, can also include other can
To provide multi-medium data of user's location information, such as audio, text etc., the embodiments of the present invention are not limited thereto.
Step 102, generation time and the anchor point of the multi-medium data are extracted；
Specifically, in user's upload multimedia data, since mobile terminal can obtain the location information of user in real time, and
Label is in above-mentioned multi-medium data, it is possible to the location information is extracted in multi-medium data.
Similarly, again with timestamp in user's upload multimedia data, it is possible to extract multi-medium data when
Between stab, with obtain user shoot multi-medium data the specific time.
It is to be appreciated that shooting time is when shooting multi-medium data with user, the time being marked in mobile terminal.
Step 103, the anchor point is clustered, obtains one or more clustering clusters.
In the embodiment of the present invention, the anchor point belonged under the same POI is clustered, wherein POI is " Point of
The abbreviation of Interest ", Chinese can be translated as " point of interest ".In GIS-Geographic Information System, a POI can be a room
Son, a retail shop, a mailbox, a bus station etc..
So the anchor point polymerization under a POI is become different clustering clusters after cluster.
Step 104, it is counted according to the positioning in the generation time and each clustering cluster, determines optimum cluster
Cluster；
Specifically, the point that the positioning points in the newest point of shooting time in clustering cluster or clustering cluster are most, determines
For optimum cluster cluster.
The more clustering cluster it is to be appreciated that time newer clustering cluster or positioning are counted, the positioning points provided can
To obtain accurate location information.
Step 105, it is determined as the standard setting of the business object according to the centre spot in the optimum cluster cluster
Point.
Specifically, the latitude and longitude value of each of optimum cluster cluster anchor point is done into mean value calculation, what is obtained is final
The corresponding centre spot of average value, as the standard setting point of the trade company.
It is to be appreciated that above-mentioned standard anchor point is to carry out central point by optimum cluster method to be calculated, the present invention
What is used in embodiment is Density Clustering method, and in practical applications, clustering method is not limited to Density Clustering method, so final
Standard setting point not necessarily by mean value calculation centre spot, such as it is every by the weight calculation of each longitude and latitude
The score of a point, selecting the highest anchor point of score is center anchor point, and is determined as standard setting point, since weighted value is by correlation
Technical staff's setting, obtained centre spot can be not necessarily the obtained centre spot of average value of each point, therefore,
In the corresponding centre spot of the average value that the embodiment of the present invention is not limited in foregoing description to the concept of centre spot.
In conclusion the embodiment of the invention provides a kind of localization methods, which comprises obtain user and be directed to business
Multi-medium data in the behavioral data of object；Extract generation time and the anchor point of the multi-medium data；To the positioning
Point is clustered, and one or more clustering clusters are obtained；According to the anchor point in the generation time and each clustering cluster
Number, determines optimum cluster cluster；It is determined as the standard of the business object according to the centre spot in the optimum cluster cluster
Anchor point.It solves the problems, such as that error present in existing location technology is high, yield poor results and be not easy to execute, user's row can be passed through
Standard setting point is determined for the anchor point of the multi-medium data in data.
Embodiment two
Referring to Fig. 2, it illustrates a kind of specific steps flow charts of localization method provided by Embodiment 2 of the present invention.
Step 201, user is obtained for the multi-medium data in the behavioral data of business object；
This step is identical as step 101, and this will not be detailed here.
Step 202, generation time and the anchor point of the multi-medium data are extracted；
This step is identical as step 102, and this will not be detailed here.
Step 203, the anchor point is clustered by having noisy density-based algorithms, obtains one
Or multiple clustering clusters.
In the embodiment of the present invention, multimedia-data procession flow chart as shown in Figure 2 A, to the warp belonged under the same POI
Latitude point is clustered using DBSCAN, wherein POI is the abbreviation of " Point of Interest ", and Chinese can be translated as " interest
Point ".In GIS-Geographic Information System, a POI can be a house, a retail shop, a mailbox, a bus station etc..
Specifically, density clustering DBSCAN (Density-Based Spatial Clustering of
Applications with Noise) it is a more representational density-based algorithms.It is poly- with division and level
Class method is different, and cluster is defined as the maximum set of the connected point of density by it, can be with region division highdensity enough
For cluster, and the cluster of arbitrary shape can be found in the spatial database of noise.
Wherein, presetting at least includes 3 points in cluster, and distance between points is set as 20m.
It step 204, is that the newest clustering cluster is determined as the first clustering cluster by the shooting time；
Specifically, in obtained all clusters, in conjunction with the shooting time of the anchor point in each cluster, average clap is calculated
The date is taken the photograph away from modern number of days, selects the clustering cluster nearest away from modern time, is labeled as the first clustering cluster.
Step 205, the most clustering cluster of positioning points in the clustering cluster is determined as the second clustering cluster；
Specifically, the most cluster of positioning points is selected from the cluster of cluster, is labeled as the second clustering cluster.
Step 206, if first clustering cluster is identical with second clustering cluster, the clustering cluster is determined as optimal
Clustering cluster；
Specifically, if the first clustering cluster and the second clustering cluster be it is same, choosing this cluster is final cluster, i.e., optimal poly-
Class cluster.
Step 207, it if first clustering cluster is different with second clustering cluster, obtains in first clustering cluster
First positioning points；
Step 208, if first clustering cluster is determined as most by the first positioning points more than the second preset threshold
Excellent clustering cluster；
Step 209, if the first positioning points are less than the second preset threshold, second clustering cluster is determined as
Optimum cluster cluster.
Specifically, if the first clustering cluster and the second clustering cluster are not same, the positioning of the nearest cluster of acquisition time
Points, if wherein anchor point quantity accounts for 1/3 (the second preset threshold) of total quantity or more, access time newest cluster, i.e., the
One clustering cluster, otherwise chooses the maximum cluster of quantity, i.e. the second clustering cluster is optimum cluster cluster.
It is to be appreciated that the above method be in practical applications in order to cope with the behaviors such as trade company's resettlement, in combination with the time and
Quantity is preferably weighed, can change perceived can guarantee certain confidence level again.
Step 210, the positioning points in the optimum cluster cluster are subjected to discretization according to Fibonacci method, obtained discrete
Anchor point；
Specifically, combine Fibonacci sequence (Fibonacci method) progress discrete positioning points in optimum cluster cluster
Change, Fibonacci sequence are as follows: 112358 13 21 34 55 89 144 ... are due to defining each cluster minimum 3
Point, so being described as follows according to the corresponding marking strategy that discrete location points are made.
Step 211, it is given a mark using default marking strategy to the discrete location point, obtains the discrete location point
Position score value；
Specifically, presetting marking strategy is, discrete point number is 10 points at 3-5, and 5-8 are 20 points, and 8-13 are 30
Point, 13-21 are 40 points, and so on, 89-144 is 90 points ..., and the method can be understood as a kind of discretization method.
It is to be appreciated that continuous data is carried out discretization by the way of golden section, compared to equal than dividing, have
Low frequency is sensitive, more meets current application scene.
Step 212, if the positioning score value is lower than the first preset threshold, prompt information is sent to the user.
Specifically, if the score value curve for carrying out the score value composition of discretization marking in optimum cluster cluster is too low, it is lower than
First preset threshold of related technical personnel's setting, then show that the anchor point in optimum cluster cluster is not accurate enough, then sends out to user
Prompt information is sent, illustrates that the anchor point is perhaps not accurate enough.
It is to be appreciated that corresponding measure can be taken to carry out the score value excellent after backstage technical staff gets the prompt
Change, for example, the modification of address information corresponding in clustering cluster push trade company is carried out manual examination and verification, or push user's modification
Deng.
Step 213, the latitude and longitude value of each anchor point in the optimum cluster cluster is obtained；
In the embodiment of the present invention, each anchor point in determining optimum cluster cluster has latitude and longitude value, extracts every
The latitude and longitude value of a point, in case operation.
Step 214, the average latitude and longitude value of the latitude and longitude value is calculated；
Specifically, the longitude of each anchor point is added resulting value, the ratio with positioning points is longitude average value, together
Sample, calculate latitude average value.
Step 215, according to the average latitude and longitude value, the centre spot in the optimum cluster cluster is obtained；
Specifically, an anchor point is determined according to longitude average value and dimension average value, as in the optimum cluster cluster
Centre spot.
Step 216, the centre spot is determined as to the standard setting point of the business object.
Specifically, which is determined as the business object, i.e. trade company, standard setting point.
It is to be appreciated that the standard setting point for combining cluster and time to obtain, does not depend on the description with address.
Wherein, newest anchor point longitude and latitude can be obtained at any time, then by mean value calculation mode, obtained standard is fixed
Site accuracy rate is higher, executes simple, does not depend on and manpower intervention.
In conclusion the embodiment of the invention provides a kind of localization methods, which comprises obtain user and be directed to business
Multi-medium data in the behavioral data of object；Extract generation time and the anchor point of the multi-medium data；To the positioning
Point is clustered, and one or more clustering clusters are obtained；According to the anchor point in the generation time and each clustering cluster
Number, determines optimum cluster cluster；Positioning points in the optimum cluster cluster are subjected to discretization according to Fibonacci method, are obtained
Discrete location point；It is given a mark using default marking strategy to the discrete location point, obtains the positioning of the discrete location point
Score value；If the positioning score value is lower than the first preset threshold, prompt information is sent to the user.According to the optimum cluster
Centre spot in cluster is determined as the standard setting point of the business object.Solves error present in existing location technology
Height yields poor results and is not easy the problem of executing, to determine bid by the anchor point of the multi-medium data in user behavior data
Certainly site.In addition to this, anchor point discretization and marking are carried out by Fibonacci method, anchor point can be determined by score value
Accuracy, to user to refer to.
Embodiment three
It is specific as follows it illustrates a kind of structure chart for positioning device that the embodiment of the present invention three provides referring to Fig. 3.
Multi-medium data obtains module 301, for obtaining user for the multimedia number in the behavioral data of business object
According to；
Data information obtains module 302, for extracting generation time and the anchor point of the multi-medium data；
Cluster module 303 obtains one or more clustering clusters for clustering to the anchor point；
Optimum cluster cluster determining module 304, for according to the anchor point in the generation time and each clustering cluster
Number, determines optimum cluster cluster；
Standard setting point determining module 305, it is described for being determined as according to the centre spot in the optimum cluster cluster
The standard setting point of business object.
In conclusion described device includes: that multi-medium data obtains mould the embodiment of the invention provides a kind of positioning device
Block, for obtaining user for the multi-medium data in the behavioral data of business object；Data information obtains module, for extracting
The generation time of the multi-medium data and anchor point；Cluster module, for being clustered to the anchor point, obtain one or
Multiple clustering clusters；Optimum cluster cluster determining module, for according to the anchor point in the generation time and each clustering cluster
Number, determines optimum cluster cluster；Standard setting point determining module, for true according to the centre spot in the optimum cluster cluster
It is set to the standard setting point of the business object.It solves the height of error present in existing location technology, yield poor results and be not easy to hold
Capable problem can determine standard setting point by the anchor point of the multi-medium data in user behavior data.
Embodiment three is the corresponding Installation practice of embodiment of the method one, and details are referred to the detailed of embodiment one
Illustrate, details are not described herein.
Example IV
It is specific as follows it illustrates a kind of structure chart for positioning device that the embodiment of the present invention four provides referring to Fig. 4.
Multi-medium data obtains module 401, for obtaining user for the multimedia number in the behavioral data of business object
According to；
Data information obtains module 402, for extracting generation time and the anchor point of the multi-medium data；
Cluster module 403 obtains one or more clustering clusters for clustering to the anchor point；
Preferably, the cluster module 403, comprising:
Submodule is clustered, for being clustered by having noisy density-based algorithms to the anchor point,
Obtain one or more clustering clusters.
Optimum cluster cluster determining module 404, for according to the anchor point in the generation time and each clustering cluster
Number, determines optimum cluster cluster；
Preferably, the optimum cluster cluster determining module 404, comprising:
First clustering cluster submodule, for being that the newest clustering cluster is determined as the first cluster by the shooting time
Cluster；
Second clustering cluster submodule, for the most clustering cluster of positioning points in the clustering cluster to be determined as second
Clustering cluster；
Optimum cluster cluster determines submodule, if identical with second clustering cluster for first clustering cluster, by institute
It states clustering cluster and is determined as optimum cluster cluster；
First positioning points acquisition submodule obtains if different with second clustering cluster for first clustering cluster
First in first clustering cluster is taken to position points；
First optimum cluster cluster determines submodule, if for the first positioning points more than the second preset threshold, it will
First clustering cluster is determined as optimum cluster cluster；
Second optimum cluster cluster determines submodule, if being less than the second preset threshold for the first positioning points,
Second clustering cluster is determined as optimum cluster cluster.
Descretization module 405, it is discrete for carrying out the positioning points in the optimum cluster cluster according to Fibonacci method
Change, obtains discrete location point；
It positions score value and obtains module 406, for being given a mark using default marking strategy to the discrete location point, obtain
The positioning score value of the discrete location point；
Cue module 407 sends prompt information to the use if being lower than the first preset threshold for the positioning score value
Family.
Standard setting point determining module 407, it is described for being determined as according to the centre spot in the optimum cluster cluster
The standard setting point of business object.
Preferably, the standard setting point determining module 407, comprising:
Latitude and longitude value acquisition submodule, for obtaining the latitude and longitude value of each anchor point in the optimum cluster cluster；
Average latitude and longitude value computational submodule, for calculating the average latitude and longitude value of the latitude and longitude value；
Centre spot acquisition submodule, for obtaining in the optimum cluster cluster according to the average latitude and longitude value
Centre spot；
Standard setting point determines submodule, for the centre spot to be determined as to the standard setting of the business object
Point.
In conclusion described device includes that multi-medium data obtains mould the embodiment of the invention provides a kind of positioning device
Block, for obtaining user for the multi-medium data in the behavioral data of business object；Data information obtains module, for extracting
The generation time of the multi-medium data and anchor point；Cluster module, for being clustered to the anchor point, obtain one or
Multiple clustering clusters；Optimum cluster cluster determining module, for according to the anchor point in the generation time and each clustering cluster
Number, determines optimum cluster cluster；Descretization module, for counting the positioning in the optimum cluster cluster according to Fibonacci method
Discretization is carried out, discrete location point is obtained；It positions score value and obtains module, for utilizing default marking strategy to the discrete location
Point is given a mark, and the positioning score value of the discrete location point is obtained；Cue module, if pre- lower than first for the positioning score value
If threshold value, then prompt information is sent to the user.Standard setting point determining module, for according in the optimum cluster cluster
Centre spot is determined as the standard setting point of the business object.It is determined according to the centre spot in the optimum cluster cluster
For the standard setting point of the business object.It solves the height of error present in existing location technology, yield poor results and be not easy to execute
The problem of, standard setting point can be determined by the anchor point of the multi-medium data in user behavior data.In addition to this, lead to
It crosses Fibonacci method and carries out anchor point discretization and marking, the accuracy of anchor point can be determined by score value, to user to join
It examines
Example IV is the corresponding Installation practice of embodiment of the method two, and details are referred to the detailed of embodiment two
Illustrate, details are not described herein.
The embodiment of the invention also provides a kind of electronic equipment, comprising: processor, memory and is stored in the storage
On device and the computer program that can run on the processor, the processor realize side above-mentioned when executing described program
Method.
The embodiment of the invention also provides a kind of readable storage medium storing program for executing, when the instruction in the storage medium is by electronic equipment
Processor execute when so that electronic equipment is able to carry out method above-mentioned.
For device embodiment, since it is basically similar to the method embodiment, related so being described relatively simple
Place illustrates referring to the part of embodiment of the method.
Algorithm and display are not inherently related to any particular computer, virtual system, or other device provided herein.
Various general-purpose systems can also be used together with teachings based herein.As described above, it constructs required by this kind of system
Structure be obvious.In addition, the present invention is also not directed to any particular programming language.It should be understood that can use various
Programming language realizes summary of the invention described herein, and the description done above to language-specific is to disclose this hair
Bright preferred forms.
In the instructions provided here, numerous specific details are set forth.It is to be appreciated, however, that implementation of the invention
Example can be practiced without these specific details.In some instances, well known method, structure is not been shown in detail
And technology, so as not to obscure the understanding of this specification.
Similarly, it should be understood that in order to simplify the disclosure and help to understand one or more of the various inventive aspects,
Above in the description of exemplary embodiment of the present invention, each feature of the invention is grouped together into single implementation sometimes
In example, figure or descriptions thereof.However, the disclosed method should not be interpreted as reflecting the following intention: i.e. required to protect
Shield the present invention claims features more more than feature expressly recited in each claim.More precisely, as following
Claims reflect as, inventive aspect is all features less than single embodiment disclosed above.Therefore,
Thus the claims for following specific embodiment are expressly incorporated in the specific embodiment, wherein each claim itself
All as a separate embodiment of the present invention.
Those skilled in the art will understand that can be carried out adaptively to the module in the equipment in embodiment
Change and they are arranged in one or more devices different from this embodiment.It can be the module or list in embodiment
Member or component are combined into a module or unit or component, and furthermore they can be divided into multiple submodule or subelement or
Sub-component.Other than such feature and/or at least some of process or unit exclude each other, it can use any
Combination is to all features disclosed in this specification (including adjoint claim, abstract and attached drawing) and so disclosed
All process or units of what method or apparatus are combined.Unless expressly stated otherwise, this specification is (including adjoint power
Benefit require, abstract and attached drawing) disclosed in each feature can carry out generation with an alternative feature that provides the same, equivalent, or similar purpose
It replaces.
Various component embodiments of the invention can be implemented in hardware, or to run on one or more processors
Software module realize, or be implemented in a combination thereof.It will be understood by those of skill in the art that can be used in practice
Microprocessor or digital signal processor (DSP) are some or complete in positioning device according to an embodiment of the present invention to realize
The some or all functions of portion's component.The present invention be also implemented as a part for executing method as described herein or
The device or device program of person's whole.It is such to realize that program of the invention can store on a computer-readable medium, or
Person may be in the form of one or more signals.Such signal can be downloaded from an internet website to obtain, Huo Zhe
It provides, or is provided in any other form on carrier signal.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and ability
Field technique personnel can be designed alternative embodiment without departing from the scope of the appended claims.In the claims,
Any reference symbol between parentheses should not be configured to limitations on claims.Word "comprising" does not exclude the presence of not
Element or step listed in the claims.Word "a" or "an" located in front of the element does not exclude the presence of multiple such
Element.The present invention can be by means of including the hardware of several different elements and being come by means of properly programmed computer real
It is existing.In the unit claims listing several devices, several in these devices can be through the same hardware branch
To embody.The use of word first, second, and third does not indicate any sequence.These words can be explained and be run after fame
Claim.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can easily think of the change or the replacement, and should all contain
Lid is within protection scope of the present invention.Therefore, protection scope of the present invention should be subject to the protection scope in claims.
Claims (12)
1. a kind of localization method, which is characterized in that the described method includes:
User is obtained for the multi-medium data in the behavioral data of business object；
Extract generation time and the anchor point of the multi-medium data；
The anchor point is clustered, one or more clustering clusters are obtained；
According to the positioning points in the generation time and each clustering cluster, optimum cluster cluster is determined；
The standard setting point of the business object is determined according to the center in the optimum cluster cluster.
2. the method according to claim 1, wherein described according to the generation time and each described poly-
After the step of positioning in class cluster counts, determines optimum cluster cluster, further includes:
Positioning points in the optimum cluster cluster are subjected to discretization according to Fibonacci method, obtain discrete location point；
It is given a mark using default marking strategy to the discrete location point, obtains the positioning score value of the discrete location point；
If the positioning score value is lower than the first preset threshold, prompt information is sent to the user.
3. the method according to claim 1, wherein described cluster the anchor point, obtain one or
The step of multiple clustering clusters, comprising:
The anchor point is clustered by having noisy density-based algorithms, obtains one or more clusters
Cluster.
4. the method according to claim 1, wherein described according to the generation time and each cluster
The step of positioning in cluster counts, determines optimum cluster cluster, comprising:
It is that the newest clustering cluster is determined as the first clustering cluster by the shooting time；
The most clustering cluster of positioning points in the clustering cluster is determined as the second clustering cluster；
If first clustering cluster is identical with second clustering cluster, the clustering cluster is determined as optimum cluster cluster；
If first clustering cluster is different with second clustering cluster, the first anchor point in first clustering cluster is obtained
Number；
If first clustering cluster is determined as optimum cluster cluster more than the second preset threshold by the first positioning points；
If the first positioning points are less than the second preset threshold, second clustering cluster is determined as optimum cluster cluster.
5. according to the method described in claim 4, it is characterized in that, the centre spot according in the optimum cluster cluster
The step of being determined as the standard setting point of the business object, comprising:
Obtain the latitude and longitude value of each anchor point in the optimum cluster cluster；
Calculate the average latitude and longitude value of the latitude and longitude value；
According to the average latitude and longitude value, the centre spot in the optimum cluster cluster is obtained；
The centre spot is determined as to the standard setting point of the business object.
6. a kind of positioning device, which is characterized in that described device includes:
Multi-medium data obtains module, for obtaining user for the multi-medium data in the behavioral data of business object；
Data information obtains module, for extracting generation time and the anchor point of the multi-medium data；
Cluster module obtains one or more clustering clusters for clustering to the anchor point；
Optimum cluster cluster determining module is determined for being counted according to the positioning in the generation time and each clustering cluster
Optimum cluster cluster out；
Standard setting point determining module, for being determined as the business object according to the centre spot in the optimum cluster cluster
Standard setting point.
7. device according to claim 6, which is characterized in that further include:
Descretization module is obtained for the positioning points in the optimum cluster cluster to be carried out discretization according to Fibonacci method
Discrete location point；
Position score value and obtain module, for being given a mark using default marking strategy to the discrete location point, obtain described in from
Dissipate the positioning score value of anchor point；
Cue module sends prompt information to the user if being lower than the first preset threshold for the positioning score value.
8. device according to claim 6, which is characterized in that the cluster module, comprising:
Submodule is clustered, for being clustered by having noisy density-based algorithms to the anchor point, is obtained
One or more clustering clusters.
9. device according to claim 6, which is characterized in that the optimum cluster cluster determining module, comprising:
First clustering cluster submodule, for being that the newest clustering cluster is determined as the first clustering cluster by the shooting time；
Second clustering cluster submodule, for the most clustering cluster of positioning points in the clustering cluster to be determined as the second cluster
Cluster；
Optimum cluster cluster determines submodule, will be described poly- if identical with second clustering cluster for first clustering cluster
Class cluster is determined as optimum cluster cluster；
First positioning points acquisition submodule obtains institute if different with second clustering cluster for first clustering cluster
State the first positioning points in the first clustering cluster；
First optimum cluster cluster determines submodule, if for the first positioning points more than the second preset threshold, it will be described
First clustering cluster is determined as optimum cluster cluster；
Second optimum cluster cluster determines submodule, if the second preset threshold is less than for the first positioning points, by institute
It states the second clustering cluster and is determined as optimum cluster cluster.
10. device according to claim 9, which is characterized in that the standard setting point determining module, comprising:
Latitude and longitude value acquisition submodule, for obtaining the latitude and longitude value of each anchor point in the optimum cluster cluster；
Average latitude and longitude value computational submodule, for calculating the average latitude and longitude value of the latitude and longitude value；
Centre spot acquisition submodule, for obtaining the center in the optimum cluster cluster according to the average latitude and longitude value
Anchor point；
Standard setting point determines submodule, for the centre spot to be determined as to the standard setting point of the business object.
11. a kind of electronic equipment characterized by comprising
Processor, memory and it is stored in the computer program that can be run on the memory and on the processor,
It is characterized in that, the processor realizes the method as described in one or more in claim 1-5 when executing described program.
12. a kind of readable storage medium storing program for executing, which is characterized in that when the instruction in the storage medium is held by the processor of electronic equipment
When row, so that electronic equipment is able to carry out the method as described in one or more in claim to a method 1-5.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
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| CN201811075583.9A CN109522374B (en) | 2018-09-14 | 2018-09-14 | Positioning method, positioning device, electronic equipment and readable storage medium |
| PCT/CN2019/092354 WO2020052312A1 (en) | 2018-09-14 | 2019-06-21 | Positioning method and apparatus, electronic device, and readable storage medium |
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| CN201811075583.9A CN109522374B (en) | 2018-09-14 | 2018-09-14 | Positioning method, positioning device, electronic equipment and readable storage medium |
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| CN109522374B CN109522374B (en) | 2020-04-17 |
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| WO2020052312A1 (en) | 2020-03-19 |
| CN109522374B (en) | 2020-04-17 |
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