CN109213836B - Point location data aggregation method and system - Google Patents
Point location data aggregation method and system Download PDFInfo
- Publication number
- CN109213836B CN109213836B CN201810906349.XA CN201810906349A CN109213836B CN 109213836 B CN109213836 B CN 109213836B CN 201810906349 A CN201810906349 A CN 201810906349A CN 109213836 B CN109213836 B CN 109213836B
- Authority
- CN
- China
- Prior art keywords
- point location
- point
- aggregation
- data
- location data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Navigation (AREA)
- Processing Or Creating Images (AREA)
Abstract
The invention discloses a point location data aggregation method for a map thermodynamic diagram, which comprises the following steps: carrying out point location aggregation on a plurality of point data in the point location data list of the map thermodynamic diagram; calculating the distance between each point corresponding to the plurality of point data and other points, and judging whether the distance is smaller than a set threshold value; and aggregating two point location data corresponding to each point location with the distance smaller than the set threshold and the other point location corresponding to the plurality of point location data to generate point location data of an aggregation point and replace the point location data corresponding to each point location. The invention also discloses a point location data aggregation system which can realize the point location data aggregation method.
Description
Technical Field
The invention relates to the technical field of maps, in particular to a point location data aggregation method and system, which are used for map-based thermodynamic diagrams.
Background
At present, the display principle of map-based thermodynamic diagrams is to present the effect of thermodynamic diagrams according to the position information and numerical values of Global Positioning System (GPS) points provided by users. Taking the application of the thermodynamic diagram of a Geographic Information System (GIS) map as an example, a common data loading method is to load the numerical value at each latitude and longitude point into a map engine and then render the map engine into the form of the thermodynamic diagram. Under the condition of small data quantity, the method can completely meet the requirements of general service application.
However, in some business application scenarios, the amount of data used for analyzing the thermodynamic diagram is too large, so that the data is loaded at a slow speed, the rendering time is too long, and the like, so that the waiting time of the user is too long. Therefore, the data needs to be aggregated to achieve that only a small amount of data needs to be loaded, thereby reducing the time for loading and rendering the data.
Disclosure of Invention
The invention provides a point location data aggregation method and system, which can compress point location data with large data volume so as to realize data aggregation, so that a user side can achieve a considerable thermodynamic diagram presentation effect on a macroscopic level by only loading a small amount of data.
In one aspect, a point location data aggregation method is provided, which includes:
carrying out point location aggregation on a plurality of point data in the point location data list of the map thermodynamic diagram;
calculating the distance between each point corresponding to the plurality of point data and other points, and judging whether the distance is smaller than a set threshold value; and
and aggregating the point location data of each point location with the distance smaller than the set threshold value and the two point location data corresponding to the other point location corresponding to the plurality of point location data to generate point location data of an aggregation point and replace the point location data corresponding to each point location.
In another aspect, a point location data aggregation system is provided, which includes a processor and a memory, where the memory stores a point location data aggregation unit, and the point location data aggregation unit is configured to:
carrying out point location aggregation on a plurality of point data in the point location data list of the map thermodynamic diagram;
calculating the distance between each point corresponding to the plurality of point data and other points, and judging whether the distance is smaller than a set threshold value; and
and aggregating the point location data of each point location with the distance smaller than the set threshold value and the two point location data corresponding to the other point location corresponding to the plurality of point location data to generate point location data of an aggregation point and replace the point location data corresponding to each point location.
According to the invention, the position and the numerical value of each point location are analyzed, and the data of all the point locations within the distance threshold range are aggregated into one point location data, so that the point location data are compressed, and the macroscopic presentation effect of the thermodynamic diagram is not influenced.
Drawings
The accompanying drawings are included to provide a further understanding of the embodiments and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments and together with the description serve to explain the principles of the invention. Other embodiments and many of the intended advantages of embodiments will be readily appreciated as they become better understood by reference to the following detailed description. The elements of the drawings are not necessarily to scale relative to each other. Like reference numerals designate corresponding similar parts.
FIG. 1 is a flow diagram of a point location data aggregation method according to one embodiment of the invention; and
FIG. 2 is a schematic diagram of a point location data aggregation system according to one embodiment of the invention.
Detailed Description
In the following detailed description, reference is made to the accompanying drawings, which form a part hereof, and in which is shown by way of illustration specific embodiments in which the invention may be practiced. It is to be understood that other embodiments may be utilized and logical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined by the appended claims.
FIG. 1 shows a flow diagram of a point location data aggregation method according to one embodiment of the invention. The point location data aggregation method is applied to map-based thermodynamic diagrams and is used for achieving aggregation of point location data of the thermodynamic diagrams. In an embodiment, the point location data aggregation method is implemented by the point location data aggregation System shown in fig. 2, and is applied to a map thermodynamic diagram G (not shown) of, for example, a Geographic Information System (GIS). As shown in fig. 1, the point location data aggregation method includes the following steps:
s10: the dot position data Dp (not shown) in the dot position data list L (not shown) of the map thermodynamic diagram G is subjected to dot position aggregation (not shown).
The point location data list L includes all the point location data Dp in the map thermodynamic diagram G, the point location data Dp includes location information I (not shown) and a point location value V (not shown), and each point location data Dp corresponds to one of the map thermodynamic diagrams GPoint P (not shown). All the original point bit data Dp are read from the point bit data list L0And for the original point location data Dp0The site aggregation is performed to generate an aggregation result R (not shown).
In one embodiment, the point location aggregation is implemented by using a GeoHash algorithm. In addition, according to the final aggregated distance parameter value, the corresponding GeoHash aggregation precision can be selected, and then the point location data list L to be calculated is read in a traversing manner, so that the GeoHash aggregation is performed on all the point location data Dp. And calculating data point location information of each GeoHash region block according to the corresponding weight, thereby calculating an aggregation result R of GeoHash aggregation.
S20: the distance D (not shown) between each point P corresponding to the point data Dp and another point P is calculated, and whether the distance D is smaller than the set threshold T (not shown) is determined.
After all the point data Dp in the point data list L is subjected to the first point location aggregation in step S10, all the point data Dp after the first point location aggregation are subjected to the first point location aggregation1And carrying out second point location polymerization.
Reading the aggregation result R in a traversal manner, first directly writing the first bit data Dp in the read aggregation result R into the custom range aggregation result Rc (not shown), then reading the other bit data Dp (except the first bit data Dp) in the aggregation result R one by one, and comparing each bit data Dp with the bit data Dp in the custom range aggregation result Rc one by one. In one embodiment, step S20 includes:
adding the first point position data Dp into a self-defined range aggregation result Rc;
calculating the distance D between the point position P corresponding to each of the other point position data Dp and the point position P corresponding to each point position data Dp in the user-defined range aggregation result Rc; and
and judging whether the distance D is smaller than a set threshold value T.
In the step of calculating the distance D between the point P corresponding to each of the other point data Dp and the point P corresponding to each point data Dp in the custom range aggregation result Rc, the linear distance between the two point data P may be calculated according to the three-dimensional coordinates of the point P corresponding to each of the other point data Dp and the point P corresponding to each point data Dp in the custom range aggregation result Rc. For example, when the three-dimensional coordinates of one point Pa in the other point location data Dp is (X1, Y1, Z1) and the three-dimensional coordinates of one point Pb in the custom range aggregation result Rc is (X2, Y2, Z2), the following straight-line distance formula can be used to calculate the straight-line distance between the two point locations P:
if the distance D is smaller than the set threshold T as a result of the determination, step S30 is executed. In an embodiment, if the distance D between the point P corresponding to each of the other point data Dp and the point P corresponding to all the point data Dp in the custom range aggregation result Rc is not less than the set threshold T, each of the other point data Dp is added to the custom range aggregation result Rc (that is, the result of comparison with the point P in all the current custom range aggregation results Rc is not less than the set threshold T, the point data Dp of the current point P is written into the custom range aggregation result Rc for new data).
S30: the two point data Dp corresponding to each point P having a distance D smaller than the set threshold T and the other point P corresponding to the point data Dp are aggregated to generate the point data Dp of the aggregation point M (not shown) and replace the point data Dp corresponding to each point P.
The point location data Dp of all the point locations P whose distance D is within the range of the set threshold T is aggregated into one point location data Dp, thereby updating the point location data list L. In one embodiment, step S30 includes:
calculating position information I and a point location numerical value V of an aggregation point M according to position information I and a point location numerical value V in two point location data Dp corresponding to each point location P and the other point location P, wherein the distance D is smaller than a set threshold value T; and
generating point location data Dp of the aggregation point M and replacing the point location data Dp corresponding to each point location P, where the point location data Dp of the aggregation point M includes the location information I and the point location value V of the aggregation point M.
For example, when the position information I of the point location a and the other point location B having the distance D smaller than the set threshold T are three-dimensional coordinates (Xa, Ya, Za) and (Xb, Yb, Zb), the point location value is Va and Vb, and the calculation formula of the position information I (Xm, Ym, Zm) of the aggregation point M is:
Xm=(Xb-Xa)×Va/(Va+Vb)+Xa；
Ym=(Yb-Ya)×Va/(Va+Vb)+Ya；
Zm=(Zb-Za)×Va/(Va+Vb)+Za；
the point location value Vm of the aggregation point M is calculated by the formula:
Vm=Va+Vb。
steps S20-S30 are repeatedly executed so as to find all the dot data Dp in the dot data list L1And carrying out second point location polymerization. In the process, after step S30 or when step S20 determines that the distance D is not less than the set threshold T, the next group of point location data Dp after point location aggregation is read (according to the formulated traversal order) until all the point location data Dp in the point location data list L are traversed, a new data list L is formed, and then execution is finished. In an embodiment, in order to further improve the accuracy of data aggregation, the steps S20-S30 may be repeated to perform data aggregation on the aggregation result R multiple times until the number of times of aggregation reaches a set upper limit, or the number of data aggregations after aggregation is unchanged.
In this embodiment, the distance is calculated by the position coordinates of each point location and the position coordinates of other points, and whether the distance is smaller than the set threshold is determined by calculating the distance between every two point locations. And when the distance is less than the threshold, calculating the aggregation point location information of the two point locations according to the numerical values of the point locations to form new point location data to replace the old two point location data, thereby aggregating the point location data less than the threshold to achieve the data compression effect.
FIG. 2 is a schematic diagram of a point location data aggregation system according to one embodiment of the invention. The point location data aggregation system is applied to map-based thermodynamic diagrams and is used for achieving aggregation of point location data of the thermodynamic diagrams. As shown in FIG. 2, in one embodiment, point location data aggregation system 100 is a computing device (e.g., a server, a computer, and a mobile intelligent terminal). The point location data aggregation system 100 includes a processor 110 and a memory 120, and a point location data aggregation unit 121 is stored in the memory 120. The processor 110 is an integrated circuit chip, such as a microprocessor (CPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic device, for executing computer programs stored in the memory 120. The point location data aggregation unit 121 includes a computer program for implementing the point location data aggregation method shown in fig. 1.
The point location data aggregation system in the embodiment of the present application and the point location data aggregation method in the embodiment of the present application are based on the same inventive concept, and some specific technical features of the system may refer to the method embodiment, which is not described in detail herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
It will be apparent to those skilled in the art that various modifications and variations can be made to the embodiments of the present invention without departing from the spirit and scope of the invention. In this way, if these modifications and changes are within the scope of the claims of the present invention and their equivalents, the present invention is also intended to cover these modifications and changes. The word "comprising" does not exclude the presence of other elements or steps than those listed in a claim. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Any reference signs in the claims shall not be construed as limiting the scope.
Claims (3)
1. A point location data aggregation method for map thermodynamic diagrams, comprising:
carrying out point location aggregation on a plurality of point data in a point location data list of the map thermodynamic diagram, wherein the point location data list L comprises all point location data Dp in the map thermodynamic diagram G, the point location data Dp comprises location information I and a point location numerical value V, each point data Dp corresponds to one point location P in the map thermodynamic diagram G, and reading all original point data Dp from the point location data list L0And for the original point location data Dp0Performing point location aggregation to generate an aggregation result R, performing first point location aggregation on all point location data Dp in the point location data list L, and then performing first point location aggregation on all point location data Dp after the first point location aggregation1Carrying out second point location polymerization;
the point aggregation algorithm specifically includes:
calculating the distance between each point corresponding to the plurality of point data and other points, and judging whether the distance is smaller than a set threshold value; and
aggregating two point location data corresponding to each point location with the distance smaller than the set threshold and the other point location corresponding to the plurality of point location data to generate point location data of an aggregation point and replace the point location data corresponding to each point location;
calculating the position information and the point location numerical value of the aggregation point according to the position information and the point location numerical value in the two point location data corresponding to each point location and the other point location with the distance smaller than the set threshold; and
generating point location data of the aggregation point and replacing the point location data corresponding to each point location, wherein the point location data of the aggregation point comprises position information and a point location numerical value of the aggregation point;
the position information of each point location A and the position information of another point location B, the distance of which is less than the set threshold value, are (Xa, Ya, Za) and (Xb, Yb, Zb), and the point location numerical values are Va and Vb respectively;
wherein, the calculation formula of the position information (Xm, Ym, Zm) of the aggregation point M is:
Xm＝(Xb-Xa)*Va/(Va+Vb)+Xa；
Ym＝(Yb-Ya)*Va/(Va+Vb)+Ya；
Zm＝(Zb-Za)*Va/(Va+Vb)+Za；
the calculation formula of the point location value Vm of the aggregation point M is as follows:
Vm＝Va+Vb；
the step of calculating the distance between each point corresponding to the plurality of point data and other points, and determining whether the distance is smaller than a set threshold value includes:
adding the first point location data into a self-defined range aggregation result;
calculating the distance between the point location corresponding to each of the other point location data and the point location corresponding to each of the point location data in the custom range aggregation result; and
judging whether the distance is smaller than the set threshold value;
wherein, the step of calculating the distance between the point location corresponding to each of the other point location data and the point location corresponding to each of the point location data in the custom range aggregation result includes:
calculating the linear distance between two point positions according to the three-dimensional coordinates of the point position corresponding to each of the other point position data and the point position corresponding to each of the point position data in the user-defined range aggregation result;
the step of judging whether the distance is smaller than the set threshold value comprises the following steps:
judging whether the distance is smaller than the set threshold value;
and if the distance between the point location corresponding to each of the other point location data and the point location corresponding to all the point location data in the user-defined range aggregation result is not less than the set threshold, adding each of the other point location data into the user-defined range aggregation result.
2. A point location data aggregation system for map thermodynamic diagrams, comprising a processor and a memory, wherein the memory stores a point location data aggregation unit, the point location data aggregation unit is configured to:
carrying out point location aggregation on a plurality of point data in a point location data list of the map thermodynamic diagram, wherein the point location data list L comprises all point location data Dp in the map thermodynamic diagram G, the point location data Dp comprises location information I and a point location numerical value V, each point data Dp corresponds to one point location P in the map thermodynamic diagram G, and reading all original point data Dp from the point location data list L0And for the original point location data Dp0Performing point location aggregation to generate an aggregation result R, performing first point location aggregation on all point location data Dp in the point location data list L, and then performing first point location aggregation on all point location data Dp after the first point location aggregation1Carrying out second point location polymerization;
the point aggregation algorithm specifically includes: calculating the distance between each point corresponding to the plurality of point data and other points, and judging whether the distance is smaller than a set threshold value; and
aggregating two point location data corresponding to each point location with the distance smaller than the set threshold and the other point location corresponding to the plurality of point location data to generate point location data of an aggregation point and replace the point location data corresponding to each point location;
calculating the position information and the point location numerical value of the aggregation point according to the position information and the point location numerical value in the two point location data corresponding to each point location and the other point location with the distance smaller than the set threshold; and
generating point location data of the aggregation point and replacing the point location data corresponding to each point location, wherein the point location data of the aggregation point comprises position information and a point location numerical value of the aggregation point;
the position information of each point location A and the position information of another point location B, the distance of which is less than the set threshold value, are (Xa, Ya, Za) and (Xb, Yb, Zb), and the point location numerical values are Va and Vb respectively;
wherein, the calculation formula of the position information (Xm, Ym, Zm) of the aggregation point M is:
Xm＝(Xb-Xa)*Va/(Va+Vb)+Xa；
Ym＝(Yb-Ya)*Va/(Va+Vb)+Ya；
Zm＝(Zb-Za)*Va/(Va+Vb)+Za；
the calculation formula of the point location value Vm of the aggregation point M is as follows:
Vm＝Va+Vb；
calculating the distance between each point corresponding to the plurality of point data and other points, and judging whether the distance is smaller than a set threshold value comprises:
adding the first point location data into a self-defined range aggregation result;
calculating the distance between the point location corresponding to each of the other point location data and the point location corresponding to each of the point location data in the custom range aggregation result; and
judging whether the distance is smaller than the set threshold value;
wherein, the step of calculating the distance between the point location corresponding to each of the other point location data and the point location corresponding to each of the point location data in the custom range aggregation result includes:
calculating the linear distance between two point positions according to the three-dimensional coordinates of the point position corresponding to each of the other point position data and the point position corresponding to each of the point position data in the user-defined range aggregation result;
the step of judging whether the distance is smaller than the set threshold value comprises the following steps:
judging whether the distance is smaller than the set threshold value;
and if the distance between the point location corresponding to each of the other point location data and the point location corresponding to all the point location data in the user-defined range aggregation result is not less than the set threshold, adding each of the other point location data into the user-defined range aggregation result.
3. A computer readable storage medium having one or more computer programs stored thereon, wherein the one or more computer programs, when executed by a computer processor, implement the following point location data aggregation method for a map thermodynamic diagram:
carrying out point location aggregation on a plurality of point data in a point location data list of the map thermodynamic diagram, wherein the point location data list L comprises all point location data Dp in the map thermodynamic diagram G, the point location data Dp comprises location information I and a point location numerical value V, each point data Dp corresponds to one point location P in the map thermodynamic diagram G, and reading all original point data Dp from the point location data list L0And for the original point location data Dp0Performing point location aggregation to generate an aggregation result R, performing first point location aggregation on all point location data Dp in the point location data list L, and then performing first point location aggregation on all point location data Dp after the first point location aggregation1Carrying out second point location polymerization;
the point aggregation algorithm specifically includes:
calculating the distance between each point corresponding to the plurality of point data and other points, and judging whether the distance is smaller than a set threshold value; and
aggregating two point location data corresponding to each point location with the distance smaller than the set threshold and the other point location corresponding to the plurality of point location data to generate point location data of an aggregation point and replace the point location data corresponding to each point location;
calculating the position information and the point location numerical value of the aggregation point according to the position information and the point location numerical value in the two point location data corresponding to each point location and the other point location with the distance smaller than the set threshold; and
generating point location data of the aggregation point and replacing the point location data corresponding to each point location, wherein the point location data of the aggregation point comprises position information and a point location numerical value of the aggregation point;
the position information of each point location A and the position information of another point location B, the distance of which is less than the set threshold value, are (Xa, Ya, Za) and (Xb, Yb, Zb), and the point location numerical values are Va and Vb respectively;
wherein, the calculation formula of the position information (Xm, Ym, Zm) of the aggregation point M is:
Xm＝(Xb-Xa)*Va/(Va+Vb)+Xa；
Ym＝(Yb-Ya)*Va/(Va+Vb)+Ya；
Zm＝(Zb-Za)*Va/(Va+Vb)+Za；
the calculation formula of the point location value Vm of the aggregation point M is as follows:
Vm＝Va+Vb；
the step of calculating the distance between each point corresponding to the plurality of point data and other points, and determining whether the distance is smaller than a set threshold value includes:
adding the first point location data into a self-defined range aggregation result;
calculating the distance between the point location corresponding to each of the other point location data and the point location corresponding to each of the point location data in the custom range aggregation result; and
judging whether the distance is smaller than the set threshold value;
wherein, the step of calculating the distance between the point location corresponding to each of the other point location data and the point location corresponding to each of the point location data in the custom range aggregation result includes:
calculating the linear distance between two point positions according to the three-dimensional coordinates of the point position corresponding to each of the other point position data and the point position corresponding to each of the point position data in the user-defined range aggregation result;
the step of judging whether the distance is smaller than the set threshold value comprises the following steps:
judging whether the distance is smaller than the set threshold value;
and if the distance between the point location corresponding to each of the other point location data and the point location corresponding to all the point location data in the user-defined range aggregation result is not less than the set threshold, adding each of the other point location data into the user-defined range aggregation result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810906349.XA CN109213836B (en) | 2018-08-10 | 2018-08-10 | Point location data aggregation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810906349.XA CN109213836B (en) | 2018-08-10 | 2018-08-10 | Point location data aggregation method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109213836A CN109213836A (en) | 2019-01-15 |
| CN109213836B true CN109213836B (en) | 2021-04-02 |
Family
ID=64989095
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810906349.XA Active CN109213836B (en) | 2018-08-10 | 2018-08-10 | Point location data aggregation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109213836B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110399441B (en) * | 2019-07-04 | 2021-04-20 | 佳都新太科技股份有限公司 | Mass point data aggregation rendering method, device, equipment and storage medium |
| CN110866078A (en) * | 2019-11-11 | 2020-03-06 | 广州小鹏汽车科技有限公司 | Data processing method and device, display control method and device and vehicle |
| CN111127626B (en) * | 2019-11-19 | 2023-11-03 | 贝壳技术有限公司 | Method, device and storage medium for generating room source zone visible frequency thermodynamic diagram |
| CN111353008B (en) * | 2019-12-26 | 2023-07-25 | 中科星图股份有限公司 | Real-time space aggregation method for Beidou position stream data |
| CN112035559B (en) * | 2020-11-02 | 2021-02-02 | 浙江口碑网络技术有限公司 | Thermodynamic diagram display method, server and system |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104991918A (en) * | 2015-06-24 | 2015-10-21 | 东方网力科技股份有限公司 | WEBGIS based online big data display method |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9691128B2 (en) * | 2012-09-20 | 2017-06-27 | Facebook, Inc. | Aggregating and displaying social networking system user information via a map interface |
| CN105550199B (en) * | 2015-11-28 | 2019-04-12 | 浙江宇视科技有限公司 | A kind of point polymerization and device based on multi-source map |
| CN107784017A (en) * | 2016-08-30 | 2018-03-09 | 杭州海康威视系统技术有限公司 | The polymerization and device of map resource point |
| CN107958064A (en) * | 2017-12-04 | 2018-04-24 | 携程旅游网络技术（上海）有限公司 | The method, apparatus of map displaying Flight Information, electronic equipment, storage medium |
-
2018
- 2018-08-10 CN CN201810906349.XA patent/CN109213836B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104991918A (en) * | 2015-06-24 | 2015-10-21 | 东方网力科技股份有限公司 | WEBGIS based online big data display method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109213836A (en) | 2019-01-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109213836B (en) | Point location data aggregation method and system | |
| CN109543909B (en) | Method and device for predicting number of vehicle cases and computer equipment | |
| JP2015509618A (en) | Automatic input signal recognition using position-based language modeling | |
| JP7186864B2 (en) | Selection of points of interest for display on personalized digital maps | |
| US20070103480A1 (en) | Information processing apparatus, information processing method, and program | |
| CN104102637A (en) | Method and device for generating hot spot region | |
| CN111597279B (en) | Information prediction method based on deep learning and related equipment | |
| CN115905342B (en) | Method and device for thinning track of moving object on water and computer equipment | |
| US20150339848A1 (en) | Method and apparatus for generating a composite indexable linear data structure to permit selection of map elements based on linear elements | |
| CN104142153A (en) | Electronic map display method, display device and navigation terminal | |
| CN108280135B (en) | Method and device for realizing visualization of data structure and electronic equipment | |
| US10378918B2 (en) | Generating routes from lines based on zoom levels | |
| JP5940718B2 (en) | Information processing apparatus, method, and computer program | |
| CN111460057B (en) | POI (Point of interest) coordinate determining method, device and equipment | |
| CN109241208A (en) | Address location, address monitoring, information processing method and device | |
| US9888347B1 (en) | Resolving location criteria using user location data | |
| CN111767937A (en) | Target detection model training method and device, electronic equipment and storage medium | |
| CN110968621A (en) | Chart generation method and device | |
| CN106443732B (en) | Path diagram drawing method and system based on GPS | |
| US7526379B2 (en) | Determining elevation values in a geocoding system | |
| CN115471550B (en) | 2.5-dimensional image space geometric azimuth correction method, device, equipment and medium | |
| CN112685553A (en) | Method, device, equipment and medium for searching and replacing online document | |
| JP5327869B2 (en) | Celebrity score calculation device, method and program thereof | |
| CN111753200B (en) | Data determination method, device, equipment and medium | |
| CN113254809B (en) | Geographic information obtaining method and device and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |