CN104123318A - Method and system for displaying interest points in map - Google Patents
Method and system for displaying interest points in map Download PDFInfo
- Publication number
- CN104123318A CN104123318A CN201310156741.4A CN201310156741A CN104123318A CN 104123318 A CN104123318 A CN 104123318A CN 201310156741 A CN201310156741 A CN 201310156741A CN 104123318 A CN104123318 A CN 104123318A
- Authority
- CN
- China
- Prior art keywords
- interest
- point
- quoted
- classification
- poi
- 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.)
- Granted
Links
Classifications
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides a method for displaying interest points in a map. The method includes the steps that data classification is performed on the interest points, and the number of citation times of the interest points is counted; the interest points of each classification are denoised according to the number of citation times of the interest points; the importance degrees of the interest points obtained through denoising processing according to the number of citation times of the interest points are obtained and used for displaying the interest points in the map. The invention further provides a system for displaying the interest points in the map. According to the technical scheme, the important interest points can be effectively displayed in the map in time.
Description
[technical field]
The present invention relates to internet, applications field, relate in particular to the method and system that a kind of map shows point of interest.
[background technology]
At cartographic information system (GIS, Geographic Information System) in, in map, need to show point of interest (POI, Point of Interest), but because the size of display screen is limited, and displayable POI quantity is a lot, therefore can not on map, demonstrate all POI in region, therefore just need to select POI, only on map, show the POI selecting.
At present, all to select the POI for showing according to the importance degree of POI, but the importance degree of POI is relevant to the affiliated area of POI, for example, for same market the importance degree of busy section of town with different at backland importance degree, therefore the importance degree that judges POI is more scabrous problem always, and all neither one proven technique scheme can realize the importance degree of objective judgement POI.The method that generally judges the importance degree of POI is to be first that POI distributes weights according to the classification of POI, then carries out obtaining after artificial tune is weighed the importance degree of POI based on these weights.The method of the importance degree of this judgement POI is because needs manually participate in, therefore the importance degree Main Basis subjective factor of POI obtains, cause some important POI to show, unessential POI shows a lot of problems, make user cannot obtain timely and effectively satisfied demonstration result in map application, user experiences poor; And the One's name is legion of POI, if each POI needs artificial participation judgement to obtain importance degree, by consuming, more manpower and efficiency are lower.
[summary of the invention]
In view of this, the invention provides the method and system that a kind of map shows point of interest, can in map, show timely and effectively important point of interest.
Concrete technical scheme of the present invention is as follows:
According to one preferred embodiment of the present invention, a kind of map shows the method for point of interest, comprising:
For point of interest carries out Data classification, and add up the quantity to be quoted of point of interest;
According to the quantity to be quoted of point of interest, the point of interest under each classification being carried out to denoising point processes;
The importance degree that obtains the point of interest obtaining after denoising point is processed according to the quantity to be quoted of described point of interest, the importance degree of described point of interest shows point of interest for map.
In said method, describedly for carrying out Data classification, point of interest is specially:
According to the classification code of default point of interest, in the one-to-one relationship of default classification code and item name, obtain the item name of point of interest, point of interest identical item name is classified as to same classification.
In said method, the quantity to be quoted of described statistics point of interest is specially:
The title of point of interest and affiliated area are retrieved at search engine as query word, obtained the result for retrieval of each search engine;
Obtain according to described result for retrieval the webpage of quoting described point of interest in each search engine, the Number of websites of described webpage being carried out obtaining quoting in search engine after duplicate removal to described point of interest, the Number of websites of described point of interest is the quantity to be quoted of point of interest at search engine;
Point of interest is increased or cuts down processing in the quantity to be quoted of search engine;
Point of interest is added in the quantity to be quoted of each search engine, obtains the quantity to be quoted of described point of interest.
In said method, described to the point of interest under each classification carry out denoising point process be specially:
According to the descending order of quantity to be quoted, the point of interest under same classification is sorted, successively the difference of the quantity to be quoted of two adjacent points of interest before and after judgement;
In the time that the difference of two adjacent points of interest exceedes predetermined threshold value, these two points of interest are passed through to examination & verification interface display to user;
In the time judging previous point of interest according to user feedback and be everyday words, delete previous point of interest and delete.
In said method, the importance degree of described point of interest equals: the difference of the mean value of the quantity to be quoted of the point of interest of the quantity to be quoted of point of interest and point of interest place classification is divided by the standard deviation of the quantity to be quoted of the point of interest of point of interest place classification.
In said method, the mean value of the quantity to be quoted of the point of interest of described point of interest place classification equals the cumulative sum of the quantity to be quoted of all points of interest under the classification of described point of interest place divided by the sum of point of interest under described classification.
In said method, the following formula of standard deviation utilization of the quantity to be quoted of the point of interest of described point of interest place classification obtains:
Wherein, σ represents the standard deviation of the quantity to be quoted of the point of interest of point of interest place classification, and link (i) represents the quantity to be quoted of described point of interest, and μ represents the mean value of the quantity to be quoted of the point of interest of described point of interest place classification.
Map shows a system for point of interest, comprising: taxon, statistic unit, processing unit, generation unit; Wherein,
Taxon, is used to point of interest to carry out Data classification;
Statistic unit, for adding up the quantity to be quoted of point of interest;
Processing unit, carries out denoising point for the quantity to be quoted according to point of interest to the point of interest under each classification and processes;
Generation unit, the importance degree of the point of interest obtaining after processing for the quantity to be quoted acquisition denoising point according to described point of interest, the importance degree of described point of interest shows point of interest for map.
In said system, described taxon is that point of interest carries out Data classification, specifically comprises:
According to the classification code of default point of interest, in the one-to-one relationship of default classification code and item name, obtain the item name of point of interest, point of interest identical item name is classified as to same classification.
In said system, the quantity to be quoted of described statistic unit statistics point of interest, specifically comprises:
The title of point of interest and affiliated area are retrieved at search engine as query word, obtained the result for retrieval of each search engine;
Obtain according to described result for retrieval the webpage of quoting described point of interest in each search engine, the Number of websites of described webpage being carried out obtaining quoting in search engine after duplicate removal to described point of interest, the Number of websites of described point of interest is the quantity to be quoted of point of interest at search engine;
Point of interest is increased or cuts down processing in the quantity to be quoted of search engine;
Point of interest is added in the quantity to be quoted of each search engine, obtains the quantity to be quoted of described point of interest.
In said system, described processing unit carries out denoising point to the point of interest under each classification to be processed, and specifically comprises:
According to the descending order of quantity to be quoted, the point of interest under same classification is sorted, successively the difference of the quantity to be quoted of two adjacent points of interest before and after judgement;
In the time that the difference of two adjacent points of interest exceedes predetermined threshold value, these two points of interest are passed through to examination & verification interface display to user;
In the time judging previous point of interest according to user feedback and be everyday words, delete previous point of interest and delete.
In said system, the importance degree of described point of interest equals: the difference of the mean value of the quantity to be quoted of the point of interest of the quantity to be quoted of point of interest and point of interest place classification is divided by the standard deviation of the quantity to be quoted of the point of interest of point of interest place classification.
In said system, the mean value of the quantity to be quoted of the point of interest of described point of interest place classification equals the cumulative sum of the quantity to be quoted of all points of interest under the classification of described point of interest place divided by the sum of point of interest under described classification.
In said system, the following formula of standard deviation utilization of the quantity to be quoted of the point of interest of described point of interest place classification obtains:
Wherein, σ represents the standard deviation of the quantity to be quoted of the point of interest of point of interest place classification, and link (i) represents the quantity to be quoted of described point of interest, and μ represents the mean value of the quantity to be quoted of the point of interest of described point of interest place classification.
As can be seen from the above technical solutions, provided by the invention have a following beneficial effect:
Quantity to be quoted according to POI in search engine obtains the importance degree of POI, in map, show according to the importance degree of POI the POI that importance degree rank is forward again, thereby can realize the importance degree that rationally, objectively obtains POI, make can demonstrate timely and effectively important POI in map, provide satisfied demonstration result to user, promote user and experience; Meanwhile, in technical solution of the present invention, can automatically generate the importance degree of POI, save manpower, and efficiency be higher.
[brief description of the drawings]
Fig. 1 is that the present invention realizes the schematic flow sheet that map shows the preferred embodiment of the method for point of interest;
Fig. 2 is that the present invention realizes the structural representation that map shows the preferred embodiment of the system of point of interest;
Fig. 3 (a) is the exemplary plot that shows POI according to the importance degree that utilizes conventional solution to obtain POI at map;
Fig. 3 (b) is the exemplary plot that shows POI according to the importance degree that utilizes technical solution of the present invention to obtain POI at map.
[embodiment]
Basic thought of the present invention is: for point of interest carries out Data classification, and add up the quantity to be quoted of point of interest; According to the quantity to be quoted of point of interest, the point of interest under each classification being carried out to denoising point processes; The importance degree that obtains the point of interest obtaining after denoising point is processed according to the quantity to be quoted of described point of interest, the importance degree of described point of interest shows point of interest for map.
In order to make the object, technical solutions and advantages of the present invention clearer, describe the present invention below in conjunction with the drawings and specific embodiments.
The invention provides a kind of method that map shows point of interest, Fig. 1 is that the present invention realizes the schematic flow sheet that map shows the preferred embodiment of the method for point of interest, and as shown in Figure 1, the preferred embodiment comprises the following steps:
Step S101, for POI carries out Data classification.
Concrete, receiving the POI that data partner provides, these POI carry simple descriptor simultaneously, and the descriptor of POI mainly comprises classification code, title and the affiliated area of POI; The item name that obtains POI according to the classification code of POI in the one-to-one relationship of default classification code and item name, is classified as same classification by POI identical item name, thereby realize, POI is carried out to Data classification; Wherein, the classification of POI is very many, and common classification is as park, school, hotel, shopping center etc.
Step S102, the quantity to be quoted of statistics POI.
Concrete, for each POI, all add up corresponding quantity to be quoted; The quantity to be quoted of POI refers to the Number of websites of quoting this POI; The method of quantity to be quoted of statistics POI is: first, using the title of POI together with affiliated area as query word in default more than one retrieving respectively in search engine, obtain the result for retrieval of each search engine; Then, obtain the webpage of quoting this POI in each search engine according to result for retrieval, these webpages are carried out to duplicate removal according to Main Domain, thereby obtain quoting in search engine the Number of websites of this POI, the Number of websites of this POI is exactly the quantity to be quoted of this POI at this search engine, thereby can obtain the quantity to be quoted of POI at each search engine; Then, according to the utilization rate of search engine, the quantity to be quoted of POI in each search engine increased or cut down, increasing the quantity to be quoted of the POI of the search engine that utilization rate is higher, the quantity to be quoted that reduces the POI of the search engine that frequency of utilization is lower is turned down; Finally, POI is added in the quantity to be quoted of each search engine, obtains the quantity to be quoted of this POI.
For example, " Beijing's the Forbidden City " is retrieved in the search engines such as Baidu's search, soso, google as query word, the quantity to be quoted of POI in Baidu's search and google is heightened, the quantity to be quoted of this POI in soso is turned down.Generally, it is more that POI is cited, and represents that this POI is just more important, and therefore the quantity to be quoted of POI is using as the important evidence of importance degree that obtains this POI.
Step S103, carries out denoising point according to the quantity to be quoted of POI to POI and processes.
Concrete, obtaining after the quantity to be quoted of each POI, because some POI belongs to everyday words, can not reflect the true importance of a POI, for example, " swimming place " is an everyday words, and in the title of some POI, just comprise " swimming place ", and the title of POI and item name exist and overlap, and therefore the quantity to be quoted of this POI just can not correctly reflect its importance degree, need to carry out denoising point to POI, in POI, delete title and item name and have the POI overlapping.
The method of POI being carried out to the processing of denoising point according to the quantity to be quoted of POI is: for each classification, according to the descending order of quantity to be quoted, to same class, other POI sorts, successively the difference of the quantity to be quoted of two adjacent POI before and after judgement; In the time that the difference of two adjacent POI exceedes predetermined threshold value, extract this two POI, and by auditing interface display to user, by user, the previous POI in these two POI is analyzed, while determining this POI really for everyday words, on examination & verification interface, trigger delete button, thereby previous POI is deleted, realize the everyday words of deleting in POI; Wherein, described user refers to relevant auditor.
Step S104, obtains the importance degree of POI according to the quantity to be quoted of POI, the importance degree of this POI shows POI for map.
Concrete, POI is being carried out to, after the processing of denoising point, for the POI retaining, according to the quantity to be quoted of each POI, and utilize following formula to calculate the importance degree of each POI:
In this formula, rank (i) represents the importance degree of POI (i), link (i) represents the quantity to be quoted of POI (i), μ represents the mean value of the quantity to be quoted of the POI of POI (i) place classification, and σ represents the standard deviation of the quantity to be quoted of the POI of POI (i) place classification.
Wherein, the average value mu of the quantity to be quoted of the POI of POI place classification can be calculated with following formula:
In this formula, N represents the sum of POI under this POI place classification, and N is positive integer; Σ link (i) represents the cumulative sum of the quantity to be quoted of all POI under this POI place classification, wherein 1≤i≤N.
Wherein, the standard deviation sigma of the quantity to be quoted of the POI of POI place classification can be calculated with following formula:
In this formula, link (i) represents the quantity to be quoted of this POI (i), and μ represents the mean value of the quantity to be quoted of the POI of POI (i) place classification.
Calculate after the importance degree of POI, in the database of map application, preserve the importance degree of POI, in the time need to showing the POI in certain region in map, the order descending according to the importance degree of POI sorts to all POI in this region, and more than one POI forward rank is presented in map.
In order to realize said method, the present invention also provides a kind of map to show the system of point of interest, Fig. 2 is that the present invention realizes the structural representation that map shows the preferred embodiment of the system of point of interest, and as shown in Figure 2, this system comprises: taxon, statistic unit, processing unit, generation unit; Wherein,
Taxon 201, is used to point of interest to carry out Data classification;
Statistic unit 202, for adding up the quantity to be quoted of point of interest;
Processing unit 203, carries out denoising point for the quantity to be quoted according to point of interest to the point of interest under each classification and processes;
Generation unit 204, the importance degree of the point of interest obtaining after processing for the quantity to be quoted acquisition denoising point according to described point of interest, the importance degree of described point of interest shows point of interest for map.
Wherein, described taxon 201, for point of interest carries out Data classification, specifically comprises:
According to the classification code of default point of interest, in the one-to-one relationship of default classification code and item name, obtain the item name of point of interest, point of interest identical item name is classified as to same classification.
Wherein, described statistic unit 202 is added up the quantity to be quoted of point of interest, specifically comprises:
The title of point of interest and affiliated area are retrieved at search engine as query word, obtained the result for retrieval of each search engine;
Obtain according to described result for retrieval the webpage of quoting described point of interest in each search engine, the Number of websites of described webpage being carried out obtaining quoting in search engine after duplicate removal to described point of interest, the Number of websites of described point of interest is the quantity to be quoted of point of interest at search engine;
Point of interest is increased or cuts down processing in the quantity to be quoted of search engine;
Point of interest is added in the quantity to be quoted of each search engine, obtains the quantity to be quoted of described point of interest.
Wherein, described processing unit 203 carries out denoising point to the point of interest under each classification to be processed, and specifically comprises:
According to the descending order of quantity to be quoted, the point of interest under same classification is sorted, successively the difference of the quantity to be quoted of two adjacent points of interest before and after judgement;
In the time that the difference of two adjacent points of interest exceedes predetermined threshold value, these two points of interest are passed through to examination & verification interface display to user;
In the time judging previous point of interest according to user feedback and be everyday words, delete previous point of interest and delete.
Wherein, the importance degree of described point of interest equals: the difference of the mean value of the quantity to be quoted of the point of interest of the quantity to be quoted of point of interest and point of interest place classification is divided by the standard deviation of the quantity to be quoted of the point of interest of point of interest place classification.
The mean value of the quantity to be quoted of the point of interest of described point of interest place classification equals the cumulative sum of the quantity to be quoted of all points of interest under the classification of described point of interest place divided by the sum of point of interest under described classification.
The following formula of standard deviation utilization of the quantity to be quoted of the point of interest of described point of interest place classification obtains:
Wherein, σ represents the standard deviation of the quantity to be quoted of the point of interest of point of interest place classification, and link (i) represents the quantity to be quoted of described point of interest, and μ represents the mean value of the quantity to be quoted of the point of interest of described point of interest place classification.
Fig. 3 (a) is the exemplary plot that shows POI according to the importance degree that utilizes conventional solution to obtain POI at map, Fig. 3 (b) is the exemplary plot that shows POI according to the importance degree that utilizes technical solution of the present invention to obtain POI at map, as Fig. 3 (a) with 3(b), before using technical solution of the present invention, in the map of Changzhi City, a lot of important POI do not show, as Changzhi City geological museum, Song Jiazhuan village, village is closed in southwest, park, riverfront, The Medical College of Changzhi, Shanxi etc., and these POI POI that this regional user pays close attention to often, therefore, in technical solution of the present invention, quantity to be quoted according to POI in search engine obtains the importance degree of POI, in map, show according to the importance degree of POI the POI that importance degree rank is forward again, thereby can realize rationally, objectively obtain the importance degree of POI, make can demonstrate timely and effectively important POI in map, provide satisfied demonstration result to user, promoting user experiences, meanwhile, in technical solution of the present invention, can automatically generate the importance degree of POI, save manpower, and efficiency be higher.
Special map score-system is to the map that utilizes conventional solution and obtain and utilize the map that technical solution of the present invention obtains to mark respectively, the mark obtaining is respectively 57 and 76 points, expression technical solution of the present invention can be distinguished the importance degree of each POI, thereby ensure that map effectively shows important POI, map effect is better.
The foregoing is only preferred embodiment of the present invention, in order to limit the present invention, within the spirit and principles in the present invention not all, any amendment of making, be equal to replacement, improvement etc., within all should being included in the scope of protection of the invention.
Claims (14)
1. map shows a method for point of interest, it is characterized in that, the method comprises:
For point of interest carries out Data classification, and add up the quantity to be quoted of point of interest;
According to the quantity to be quoted of point of interest, the point of interest under each classification being carried out to denoising point processes;
The importance degree that obtains the point of interest obtaining after denoising point is processed according to the quantity to be quoted of described point of interest, the importance degree of described point of interest shows point of interest for map.
2. method according to claim 1, is characterized in that, is describedly specially for point of interest carries out Data classification:
According to the classification code of default point of interest, in the one-to-one relationship of default classification code and item name, obtain the item name of point of interest, point of interest identical item name is classified as to same classification.
3. method according to claim 1, is characterized in that, the quantity to be quoted of described statistics point of interest is specially:
The title of point of interest and affiliated area are retrieved at search engine as query word, obtained the result for retrieval of each search engine;
Obtain according to described result for retrieval the webpage of quoting described point of interest in each search engine, the Number of websites of described webpage being carried out obtaining quoting in search engine after duplicate removal to described point of interest, the Number of websites of described point of interest is the quantity to be quoted of point of interest at search engine;
Point of interest is increased or cuts down processing in the quantity to be quoted of search engine;
Point of interest is added in the quantity to be quoted of each search engine, obtains the quantity to be quoted of described point of interest.
4. method according to claim 1, is characterized in that, described to the point of interest under each classification carry out denoising point process be specially:
According to the descending order of quantity to be quoted, the point of interest under same classification is sorted, successively the difference of the quantity to be quoted of two adjacent points of interest before and after judgement;
In the time that the difference of two adjacent points of interest exceedes predetermined threshold value, these two points of interest are passed through to examination & verification interface display to user;
In the time judging previous point of interest according to user feedback and be everyday words, delete previous point of interest and delete.
5. method according to claim 1, it is characterized in that, the importance degree of described point of interest equals: the difference of the mean value of the quantity to be quoted of the point of interest of the quantity to be quoted of point of interest and point of interest place classification is divided by the standard deviation of the quantity to be quoted of the point of interest of point of interest place classification.
6. method according to claim 5, it is characterized in that, the mean value of the quantity to be quoted of the point of interest of described point of interest place classification equals the cumulative sum of the quantity to be quoted of all points of interest under the classification of described point of interest place divided by the sum of point of interest under described classification.
7. method according to claim 5, is characterized in that, the following formula of standard deviation utilization of the quantity to be quoted of the point of interest of described point of interest place classification obtains:
Wherein, σ represents the standard deviation of the quantity to be quoted of the point of interest of point of interest place classification, and link (i) represents the quantity to be quoted of described point of interest, and μ represents the mean value of the quantity to be quoted of the point of interest of described point of interest place classification.
8. map shows a system for point of interest, it is characterized in that, this system comprises: taxon, statistic unit, processing unit, generation unit; Wherein,
Taxon, is used to point of interest to carry out Data classification;
Statistic unit, for adding up the quantity to be quoted of point of interest;
Processing unit, carries out denoising point for the quantity to be quoted according to point of interest to the point of interest under each classification and processes;
Generation unit, the importance degree of the point of interest obtaining after processing for the quantity to be quoted acquisition denoising point according to described point of interest, the importance degree of described point of interest shows point of interest for map.
9. system according to claim 8, is characterized in that, described taxon is that point of interest carries out Data classification, specifically comprises:
According to the classification code of default point of interest, in the one-to-one relationship of default classification code and item name, obtain the item name of point of interest, point of interest identical item name is classified as to same classification.
10. system according to claim 8, is characterized in that, the quantity to be quoted of described statistic unit statistics point of interest, specifically comprises:
The title of point of interest and affiliated area are retrieved at search engine as query word, obtained the result for retrieval of each search engine;
Obtain according to described result for retrieval the webpage of quoting described point of interest in each search engine, the Number of websites of described webpage being carried out obtaining quoting in search engine after duplicate removal to described point of interest, the Number of websites of described point of interest is the quantity to be quoted of point of interest at search engine;
Point of interest is increased or cuts down processing in the quantity to be quoted of search engine;
Point of interest is added in the quantity to be quoted of each search engine, obtains the quantity to be quoted of described point of interest.
11. systems according to claim 8, is characterized in that, described processing unit carries out denoising point to the point of interest under each classification to be processed, and specifically comprises:
According to the descending order of quantity to be quoted, the point of interest under same classification is sorted, successively the difference of the quantity to be quoted of two adjacent points of interest before and after judgement;
In the time that the difference of two adjacent points of interest exceedes predetermined threshold value, these two points of interest are passed through to examination & verification interface display to user;
In the time judging previous point of interest according to user feedback and be everyday words, delete previous point of interest and delete.
12. systems according to claim 8, it is characterized in that, the importance degree of described point of interest equals: the difference of the mean value of the quantity to be quoted of the point of interest of the quantity to be quoted of point of interest and point of interest place classification is divided by the standard deviation of the quantity to be quoted of the point of interest of point of interest place classification.
13. systems according to claim 12, it is characterized in that, the mean value of the quantity to be quoted of the point of interest of described point of interest place classification equals the cumulative sum of the quantity to be quoted of all points of interest under the classification of described point of interest place divided by the sum of point of interest under described classification.
14. systems according to claim 12, is characterized in that, the following formula of standard deviation utilization of the quantity to be quoted of the point of interest of described point of interest place classification obtains:
Wherein, σ represents the standard deviation of the quantity to be quoted of the point of interest of point of interest place classification, and link (i) represents the quantity to be quoted of described point of interest, and μ represents the mean value of the quantity to be quoted of the point of interest of described point of interest place classification.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310156741.4A CN104123318B (en) | 2013-04-28 | 2013-04-28 | A kind of method and system of map denotation point of interest |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310156741.4A CN104123318B (en) | 2013-04-28 | 2013-04-28 | A kind of method and system of map denotation point of interest |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104123318A true CN104123318A (en) | 2014-10-29 |
| CN104123318B CN104123318B (en) | 2019-01-15 |
Family
ID=51768730
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310156741.4A Active CN104123318B (en) | 2013-04-28 | 2013-04-28 | A kind of method and system of map denotation point of interest |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104123318B (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105222803A (en) * | 2015-10-20 | 2016-01-06 | 北京百度网讯科技有限公司 | Map POI display packing and terminal |
| CN107679189A (en) * | 2017-09-30 | 2018-02-09 | 百度在线网络技术（北京）有限公司 | A kind of point of interest update method, device, server and medium |
| CN107798018A (en) * | 2016-09-06 | 2018-03-13 | 高德软件有限公司 | A kind of method to set up and device of point of interest display information |
| CN107918512A (en) * | 2017-11-16 | 2018-04-17 | 携程旅游信息技术（上海）有限公司 | Hotel information display methods, device, electronic equipment, storage medium |
| CN108073712A (en) * | 2017-12-22 | 2018-05-25 | 金蝶软件（中国）有限公司 | Master data delet method, device and computer equipment in information system |
| CN108182253A (en) * | 2017-12-29 | 2018-06-19 | 百度在线网络技术（北京）有限公司 | For generating the method and apparatus of information |
| CN108446303A (en) * | 2018-01-30 | 2018-08-24 | 中国电子科技集团公司第三十研究所 | A kind of map nodes polymerization display, layering aggregation method and device |
| CN109241225A (en) * | 2018-08-27 | 2019-01-18 | 百度在线网络技术（北京）有限公司 | Point of interest competitive relation method for digging, device, computer equipment and storage medium |
| CN110688434A (en) * | 2018-06-19 | 2020-01-14 | 百度在线网络技术（北京）有限公司 | Method, device, equipment and medium for processing interest points |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20010102890A (en) * | 2001-10-17 | 2001-11-17 | 박홍성 | Personal navigation system and method for displaying a information of interesting point |
| CN101271000A (en) * | 2008-04-30 | 2008-09-24 | 凯立德欣技术（深圳）有限公司 | Vehicle mounted navigation terminal and its interest point indication method |
| CN101350154A (en) * | 2008-09-16 | 2009-01-21 | 北京搜狗科技发展有限公司 | Method and apparatus for ordering electronic map data |
| CN101388023A (en) * | 2008-09-12 | 2009-03-18 | 北京搜狗科技发展有限公司 | Electronic map interest point data redundant detecting method and system |
| CN102479229A (en) * | 2010-11-29 | 2012-05-30 | 北京四维图新科技股份有限公司 | Method and system for generating point of interest (POI) data |
| CN102541936A (en) * | 2010-12-31 | 2012-07-04 | 高德软件有限公司 | Method and device for acquiring popularity of POI (Point of Interest) |
| CN102682023A (en) * | 2011-03-11 | 2012-09-19 | 富士通株式会社 | Method and device for determing website search keywords |
-
2013
- 2013-04-28 CN CN201310156741.4A patent/CN104123318B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20010102890A (en) * | 2001-10-17 | 2001-11-17 | 박홍성 | Personal navigation system and method for displaying a information of interesting point |
| CN101271000A (en) * | 2008-04-30 | 2008-09-24 | 凯立德欣技术（深圳）有限公司 | Vehicle mounted navigation terminal and its interest point indication method |
| CN101388023A (en) * | 2008-09-12 | 2009-03-18 | 北京搜狗科技发展有限公司 | Electronic map interest point data redundant detecting method and system |
| CN101350154A (en) * | 2008-09-16 | 2009-01-21 | 北京搜狗科技发展有限公司 | Method and apparatus for ordering electronic map data |
| CN102479229A (en) * | 2010-11-29 | 2012-05-30 | 北京四维图新科技股份有限公司 | Method and system for generating point of interest (POI) data |
| CN102541936A (en) * | 2010-12-31 | 2012-07-04 | 高德软件有限公司 | Method and device for acquiring popularity of POI (Point of Interest) |
| CN102682023A (en) * | 2011-03-11 | 2012-09-19 | 富士通株式会社 | Method and device for determing website search keywords |
Non-Patent Citations (1)
| Title |
|---|
| 管于华: "《统计学》", 31 August 2005 * |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017067211A1 (en) * | 2015-10-20 | 2017-04-27 | 北京百度网讯科技有限公司 | Map poi display method and terminal |
| CN105222803A (en) * | 2015-10-20 | 2016-01-06 | 北京百度网讯科技有限公司 | Map POI display packing and terminal |
| CN107798018B (en) * | 2016-09-06 | 2020-04-10 | 高德软件有限公司 | Method and device for setting display information of interest points |
| CN107798018A (en) * | 2016-09-06 | 2018-03-13 | 高德软件有限公司 | A kind of method to set up and device of point of interest display information |
| CN107679189A (en) * | 2017-09-30 | 2018-02-09 | 百度在线网络技术（北京）有限公司 | A kind of point of interest update method, device, server and medium |
| CN107918512A (en) * | 2017-11-16 | 2018-04-17 | 携程旅游信息技术（上海）有限公司 | Hotel information display methods, device, electronic equipment, storage medium |
| CN108073712A (en) * | 2017-12-22 | 2018-05-25 | 金蝶软件（中国）有限公司 | Master data delet method, device and computer equipment in information system |
| CN108073712B (en) * | 2017-12-22 | 2020-08-18 | 金蝶软件（中国）有限公司 | Method and device for deleting main data in information system and computer equipment |
| CN108182253B (en) * | 2017-12-29 | 2021-12-28 | 百度在线网络技术（北京）有限公司 | Method and apparatus for generating information |
| CN108182253A (en) * | 2017-12-29 | 2018-06-19 | 百度在线网络技术（北京）有限公司 | For generating the method and apparatus of information |
| CN108446303A (en) * | 2018-01-30 | 2018-08-24 | 中国电子科技集团公司第三十研究所 | A kind of map nodes polymerization display, layering aggregation method and device |
| CN110688434A (en) * | 2018-06-19 | 2020-01-14 | 百度在线网络技术（北京）有限公司 | Method, device, equipment and medium for processing interest points |
| CN110688434B (en) * | 2018-06-19 | 2022-12-09 | 百度在线网络技术（北京）有限公司 | Method, device, equipment and medium for processing interest points |
| CN109241225A (en) * | 2018-08-27 | 2019-01-18 | 百度在线网络技术（北京）有限公司 | Point of interest competitive relation method for digging, device, computer equipment and storage medium |
| US11232116B2 (en) | 2018-08-27 | 2022-01-25 | Baidu Online Network Technology (Beijing) Co., Ltd. | Method, computer device and storage medium for mining point of interest competitive relationship |
| CN109241225B (en) * | 2018-08-27 | 2022-03-25 | 百度在线网络技术（北京）有限公司 | Method and device for mining competition relationship of interest points, computer equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104123318B (en) | 2019-01-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104123318A (en) | Method and system for displaying interest points in map | |
| TWI564738B (en) | Method and apparatus for recommending candidate words based on geographic location | |
| Poblete et al. | Do all birds tweet the same? Characterizing Twitter around the world | |
| Zhong et al. | Research on China's tourism: A 35‐year review and authorship analysis | |
| CN102426610B (en) | Microblog rank searching method and microblog searching engine | |
| US20190325357A1 (en) | Systems and methods of generating itineraries using location data | |
| CN103914536A (en) | Interest point recommending method and system for electronic maps | |
| CN106326371A (en) | Method and device for pushing services | |
| Brovelli et al. | Public participation GIS: A FOSS architecture enabling field-data collection | |
| CN106202294A (en) | The related news computational methods merged based on key word and topic model and device | |
| CN101299217A (en) | Method, apparatus and system for processing map information | |
| CN103577442A (en) | Method and device for calculating map data importance | |
| CN104216889B (en) | Data dissemination analyzing and predicting method and system based on cloud service | |
| CN103279523A (en) | Method and device for processing address information | |
| CN104102637A (en) | Method and device for generating hot spot region | |
| CN110633406A (en) | Event topic generation method and device, storage medium and terminal equipment | |
| Maghrebi et al. | Transportation application of social media: Travel mode extraction | |
| WO2021164131A1 (en) | Map display method and system, computer device and storage medium | |
| CN103440328B (en) | A kind of user classification method based on mouse behavior | |
| CN111177289A (en) | Method and system for extracting and checking related information of data space of multi-source network | |
| CN102567392A (en) | Control method for interest subject excavation based on time window | |
| US20130031458A1 (en) | Hyperlocal content determination | |
| CN103106234A (en) | Searching method and device of webpage content | |
| Honarparvar et al. | Improvement of a location-aware recommender system using volunteered geographic information | |
| CN104281646B (en) | Urban waterlogging detection method based on microblog data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |