WO2016127879A1 - 一种确定热点区域的方法和装置 - Google Patents

一种确定热点区域的方法和装置 Download PDF

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Publication number
WO2016127879A1
WO2016127879A1 PCT/CN2016/073270 CN2016073270W WO2016127879A1 WO 2016127879 A1 WO2016127879 A1 WO 2016127879A1 CN 2016073270 W CN2016073270 W CN 2016073270W WO 2016127879 A1 WO2016127879 A1 WO 2016127879A1
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Prior art keywords
positioning
area
hotspot
location
mobile device
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PCT/CN2016/073270
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English (en)
French (fr)
Inventor
张杨
刘欣
吴兴昊
邵茂材
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Alibaba Group Holding Ltd
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Alibaba Group Holding Ltd
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor

Definitions

  • the present invention relates to the field of computer application technologies, and in particular, to a method and apparatus for determining a hot spot area.
  • the mobile application pushes information based on the hotspot area of the mobile device; when updating the data such as maps and locations, the mobile application preferentially updates the data of the hotspot area of the mobile device; when the user searches using the mobile device, the hotspot area adjusts the search result as a parameter. Sorting; and so on.
  • the commonly used method is to continuously collect the positioning result of the mobile device on the server side, and determine the hot spot area of each mobile device based on the positioning result.
  • this method requires the mobile device to perform positioning by means of GPS or network positioning, and continuously uploads the positioning result, which has a great influence on the network resources and the performance of the mobile device.
  • the location information of the mobile device collected by the server is point-like, and usually the hotspot area of the user activity should be planar, and the hotspot area cannot be directly reflected.
  • the present invention provides a method and apparatus for determining hotspot regions in order to reduce the impact on network resources and mobile device performance.
  • the present invention provides a method of determining a hot spot area, the method comprising:
  • Positioning is performed by using a positioning database locally preset by the mobile device, and the positioning result is recorded; wherein the positioning database includes positioning area data, and the positioning area data includes a positioning area identifier and corresponding location information;
  • the positioning by using a positioning database locally preset by the mobile device includes:
  • Determining the base station detected by the mobile device Determining the base station detected by the mobile device, querying the corresponding location information in the location database according to the location area corresponding to the detected base station, and determining the location result of the mobile device by using the queried location information.
  • the positioning by using a positioning database locally preset by the mobile device includes:
  • the location information is used to query the location information in the location database by using the identifier information corresponding to the location area after the handover, and the location result of the mobile device is determined by using the queried location information.
  • the positioning area data is pre-configured in the positioning database
  • the mobile device acquires the location area data from a server and stores the location database.
  • the method further includes:
  • the location area data includes location area code LAC data, and the hotspot location area is LAC; or
  • the location area data includes cell data, and the hotspot location area is a cell; or
  • the hotspot area data includes LAC data and cell data, and the hotspot location area is an LAC or a cell.
  • the method further includes: acquiring, by the server, the cell data corresponding to the hotspot LAC, And acquiring the acquired cell data in the positioning database.
  • determining a hot spot of the mobile device according to the positioning result The bit areas include:
  • the heat value of each positioning area is set according to the number of the positioning results, and the positioning area whose heat value meets the preset condition is determined as the hot spot positioning area, and the preset condition includes: the heat value is ranked in the first M, and the M is the preset positive An integer, or heat value, is greater than or equal to a preset heat threshold.
  • the weight of the positioning result obtained by using the GPS or the network positioning method is greater than the weight of the positioning result obtained by using the positioning database locally preset by the mobile device.
  • determining the hotspot location area of the mobile device according to the positioning result includes:
  • the location area corresponding to the preset hotspot area standard is determined as the hotspot location area, where the hotspot area standard includes: the number of the positioning results is ranked in the first N, and the N is a preset positive integer; or, The number of positioning results is greater than or equal to the preset number threshold.
  • determining the hotspot location area of the mobile device according to the positioning result includes:
  • the time series analysis method is used to obtain the X positioning results in which the positioning time is within a certain time period, and the positioning area corresponding to the X positioning results is determined as the hotspot positioning area in the certain time period, X is greater than or equal to the preset number threshold.
  • the hot spot area is described in at least one of the following ways:
  • the present invention also provides an apparatus for determining a hot spot area, characterized in that the apparatus comprises:
  • An offline positioning unit configured to perform positioning by using a positioning database preset by the mobile device, where the positioning database includes positioning area data, where the positioning area data includes a positioning area identifier and corresponding location information;
  • the analyzing unit is configured to determine a hotspot location area of the mobile device according to the positioning result recorded by the recording unit, and determine the hotspot location area as a hotspot area.
  • the offline positioning unit performs positioning, specifically:
  • Determining the base station detected by the mobile device Determining the base station detected by the mobile device, querying the corresponding location information in the location database according to the location area corresponding to the detected base station, and determining the location result of the mobile device by using the queried location information.
  • the offline positioning unit when performing the positioning, specifically performs: when monitoring the switching of the positioning area of the mobile device, using the identification information corresponding to the switched positioning area in the positioning database. Querying the corresponding location information, and determining the location result of the mobile device by using the queried location information.
  • the positioning area data is pre-configured in the positioning database
  • the device further includes: an obtaining unit, configured to acquire the positioning area data from the server end and store the data in the positioning database.
  • the recording unit is further configured to record a positioning result obtained by using GPS or network positioning.
  • the location area data includes location area code LAC data, and the hotspot location area is LAC; or
  • the location area data includes cell data, and the hotspot location area is a cell; or
  • the hotspot area data includes LAC data and cell data, and the hotspot location area is an LAC or a cell.
  • the apparatus further includes: an obtaining unit, configured to obtain, after the analyzing unit determines the hotspot LAC of the mobile device, from the server The cell data corresponding to the hot spot LAC, and the acquired cell data is stored in the positioning database.
  • the analyzing unit is configured to set a heat value of each positioning area according to the number of positioning results, and determine a positioning area whose heat value meets a preset condition as a hot spot positioning area, and the preset condition Including: the heat value is ranked in the first M, M is a preset positive integer, or the heat value is greater than or equal to a preset heat threshold.
  • the weight of the positioning result obtained by using the GPS or the network positioning method is greater than the weight of the positioning result obtained by using the positioning database locally preset by the mobile device.
  • the analyzing unit is specifically configured to:
  • the location area corresponding to the preset hotspot area standard is determined as the hotspot location area, where the hotspot area standard includes: the number of the positioning results is ranked in the first N, and the N is a preset positive integer; or, The number of positioning results is greater than or equal to the preset number threshold.
  • the analyzing unit is specifically configured to use time series analysis to obtain X positioning results whose positioning time is within a certain time period meets the correlation requirement, and locate the corresponding positioning results of the X positioning results.
  • the area is determined as a hotspot location area within the certain time period, and the X is greater than or equal to a preset number threshold.
  • the hot spot area is described in at least one of the following ways:
  • the method for determining the hotspot area is based on the positioning result of the mobile device end, that is, the mobile device side uses the local preset positioning database for positioning, and the offline positioning method does not need the GPS module and does not need to be moved.
  • the device uploads the positioning result to the server in real time, which reduces the impact on mobile device performance and network resources.
  • FIG. 1 is a flowchart of a method for determining a hotspot area according to an embodiment of the present invention
  • FIG. 2 is a structural diagram of a device according to an embodiment of the present invention.
  • the core idea of the present invention is to preset a positioning database locally in the mobile device, where the positioning database includes positioning area data, wherein the positioning area data includes a positioning area identifier and corresponding location information.
  • the mobile device can use the local preset positioning database to locate and record the positioning result. And determining, by the mobile device, the hotspot location area according to the recorded positioning result, and determining the hotspot location area as the hotspot area.
  • the location area data may include LAC data, and the corresponding hotspot location area is a hotspot LAC.
  • the location area may also include cell data, and the corresponding hotspot location area is a hotspot cell.
  • the locating area may also include LAC data and cell data, and the corresponding hotspot locating area may be a hotspot LAC or a hotspot cell.
  • the LAC data includes LAC identification information and corresponding location information
  • the cell data includes a Cellid (Cell ID) and corresponding location information.
  • Cell ID Cell ID
  • the "cell” herein refers to the concept of a cell in mobile communication and is the coverage of a base station signal.
  • the "hot spot area” referred to in the embodiment of the present invention refers to the area where the mobile device is often located, which reflects the range of places where the user frequently moves.
  • FIG. 1 is a flowchart of a method for determining a hotspot area according to an embodiment of the present invention.
  • the location area data is used as the LAC data
  • the hotspot location area is the hotspot LAC.
  • the location area data is the cell data
  • the implementation manner of the hotspot location area is the hotspot cell is similar to the process in FIG.
  • the method can include the following steps:
  • the mobile device locally presets the location database.
  • the LAC data may be preset in the positioning database, and may be manually configured or factory configured, or may be stored in the positioning database after the LAC data obtained from the server is used.
  • the data used for positioning is mainly stored on the server side, and is stored on the server side.
  • the stored data is mainly at the base station level, and the amount of data is large.
  • the LAC data may be stored only in the location database of the mobile device, and the LAC data amount is compared with the data of the base station level, which greatly reduces the amount of data. Reduced from tens of millions to 10,000 levels, it can be stored on the mobile device side.
  • the server-side base station level data usually includes a base station id (identification), an associated LAC identifier, and base station location information.
  • the LAC data may be obtained by combining base station level data based on the LAC identifier.
  • the LAC data may include LAC identification information and corresponding location information.
  • the location information may include location information of the center point of the area covered by the LAC, and may also include contour information or radius information of the area covered by the LAC.
  • the base station data that belongs to the same LAC is clustered based on the location information.
  • the base station data belonging to the same LAC is clustered into the same class, and the location information of the center point of the corresponding class of the LAC is recorded, and the location information may be
  • the latitude and longitude may also be the administrative division information of the location, for example, in the xx district of the xx province, and further, the contour information or the radius information of the LAC corresponding class may be recorded.
  • the base station data of the same LAC may be clustered into multiple classes ("multiple" refers to more than one in the embodiment of the present invention).
  • the obtained class can be separately judged whether it meets the preset attribute standard, and if it does not, the class is filtered out.
  • the location information of the center point of the class corresponding to the attribute standard corresponding to the LAC is recorded, and the profile information of the class conforming to the attribute standard may be further recorded.
  • the creation time of the base station in the class is within the most recent preset time range. This situation is to prevent some base stations from being created for a long time. It is possible that the actual base station is no longer used, but the base station data in the database is not updated in time. For the class generated in this case, it can be filtered out without recording.
  • the coverage area of the class is greater than or equal to the preset area standard. Some base stations are distributed in a small class separated from most other base stations. The probability of users in the area covered by this type is usually much lower than other classes, often some places far away from the urban area, based on some kind of Special needs The base station is created, so the class generated for this case can be filtered out.
  • the number of base stations in the class is greater than or equal to the preset number standard. Generally, a larger number of base stations are usually set in places where users are denser and demand is higher. Similar to the case of the above 2), some base stations are distributed into a small class away from most other base stations, and the probability of users in the coverage area of the class is usually much lower than other classes, so this situation is generated.
  • the class can filter it out.
  • the area covered by the class finally obtained after the above filtering is the area covered by the LAC.
  • clustering methods such as K-means, K-medoids, DBSCAN (Density-Based Spatial Clustering of Applications with Noise, and noise-based clustering methods) may be employed.
  • the present invention does not limit the clustering method.
  • each base station data in the class is used as a location point, and one of the classes is determined to be the most among the points in the class.
  • a point on the outer side as a first contour point; determining a second contour point adjacent to the first contour point and connected to the first contour point to form a straight line such that all the position points are on the same side of the straight line or the straight line,
  • the second contour point is fed into the contour point queue; starting from the second contour point, the other contour points are sequentially found in the same way until the first contour point is found again and the first contour point is included in the contour point queue.
  • the position point in the final contour point queue is the outline of the class, that is, the sample point located at the outermost side of the area covered by the class.
  • the cell data is obtained by the server according to the positioning data, and the positioning results belonging to the same cell in the positioning data are integrated, and when the integration is performed, the positioning result belonging to the same cell may be clustered. Similarly, at least one class is generated after clustering, and these classes can also be filtered.
  • the area covered by the finally obtained class is used as the area corresponding to the cell, and the location information of the area may include location information of the center point, and may also include contour information or radius information of the area.
  • the method of determining the clustering mode, filtering mode, and contour information is similar to the processing in the LAC data. No longer.
  • the location information of the central point can be described by latitude and longitude, or by administrative division information.
  • the Cellid and its corresponding location information are then recorded to obtain the cell data.
  • the localization preset database of the mobile device is used for positioning, and the positioning time and the positioning result are recorded.
  • the first method is to determine the base station currently detected by the mobile device, query the corresponding location information in the location database according to the LAC identification information of the currently detected base station, and determine the location result of the mobile device by using the queried location information.
  • This method can be positioned periodically, for example, every preset time. It can also be executed when the located event is triggered. For example, if the operation of the user on the mobile device generates a positioning event, the positioning is performed once.
  • the recorded positioning time is the time when the positioning is performed in this mode.
  • the second method is: when the LAC switch occurs on the mobile device, the location information is used to query the location information in the location database, and the location information of the mobile device is used to determine the location result of the mobile device.
  • This method is a positioning method that is performed when an LAC switch occurs.
  • the recorded positioning time may be the time when the positioning is performed in the present mode, or may be a time period, that is, the time from the occurrence of the switching to the time when the next switching occurs.
  • the location information of the LAC2 is used to query the location information in the location database, and the location information of the LAC2 is used to determine the location result of the mobile device.
  • the time is t1.
  • the location time corresponding to the location information of LAC2 is recorded as t1 to t2. That is to say, during the period from t1 to t2, the mobile device is located in the area of the LAC2.
  • the location information obtained by querying the local database may be the latitude and longitude of the central point, or may be a combination of the latitude and longitude of the central point and the radius of the region, or may be a combination of the latitude and longitude of the central point and the contour information, or may be an administrative division. Information, such as xx province xx city xx district, except the center In addition to the latitude and longitude of the point, other location information is the location information.
  • the above two methods are offline positioning methods, without consuming network traffic, and without having a GPS module.
  • the module for positioning may be encapsulated in the system layer, and the API supply layer call is provided.
  • the API is called to obtain the positioning result.
  • the positioning time and the positioning result obtained by other positioning methods may also be recorded on the mobile device side and used for subsequent determination of the hot spot area. That is, other targeting methods can be used as an aid to offline positioning.
  • the network positioning refers to the manner in which the positioning logic is on the server side, and after the server side completes the positioning process of the mobile device, the positioning result is returned to the mobile device through the network, such as base station positioning and wifi positioning, which belong to the network positioning.
  • the hotspot LAC of the preset time period is determined according to the recorded positioning time and the positioning result.
  • the hotspots of the activities may be different in different time periods. For example, in the daytime activity hotspot area is the office, and in the evening, the activity hotspot area is home. For example, if the user lived in Haidian District last year, then the hot spot activity area is Haidian District. This year, he lived in Chaoyang District, and his hot spot activity area is Chaoyang District.
  • the time zone may be divided to determine the hot spot area of the preset time period.
  • the preset time period can be granular in hours, days, weeks, months, and even years.
  • the time period may not be limited and divided.
  • the positioning result can be recorded without recording the positioning time.
  • the positioning result obtained by the mobile device by using other positioning methods may be recorded.
  • the hotspot LAC is determined according to the recorded positioning result.
  • the positioning result in the preset time period may be determined according to the positioning time and the positioning result;
  • the LAC of the preset time period is clustered to obtain at least one class.
  • the LAC corresponding to the class that meets the preset hotspot area standard is determined as the hotspot LAC in the preset time period, and the hot spot LAC is the mobile device.
  • the preset hotspot area standard may be used but not limited to: the number of the positioning results is ranked in the first N, and N is a preset positive integer; and the number of the positioning results is greater than or equal to the preset number threshold. For example, the class containing the largest number of positioning results is determined as the hotspot area.
  • the hotspot area criteria are defined to rule out errors caused by occasional activities. Ideally, all the positioning results in the class belong to the same LAC, and some occasional situations may cause errors. For example, the mobile device is located in the vicinity of the LAC switch, which may cause the mobile device to access different LACs. The LAC corresponding to most of the positioning results in the class is the hotspot LAC.
  • two time periods are preset, one time period is: 9:00 to 17:00; and one time period is 10:00 to 6:00.
  • the positioning results with the positioning time in the range of 9:00 to 17:00 are found, and the positioning results are clustered, and it is assumed that three classes, one class, and the corresponding positions of the three classes are obtained.
  • the information is: Zhichun Road, Haidian District, Beijing, Peony Garden, Haidian District, Beijing, and Peking University, Haidian District, Beijing.
  • the three categories contain the number of positioning results: 88, 10 and 2, respectively, then the Zhichun Road in Haidian District, Beijing can be used as an activity hotspot area from 9:00 to 17:00.
  • the positioning results of the positioning time from 22:00 to 6:00 are found from the recorded positioning time and the positioning result, and the positioning results are clustered. It is assumed that three classes are also obtained, and the position information corresponding to the three classes is respectively For: Huilongguan Community, Changping District, Beijing, Sanlitun, Chaoyang District, Beijing, Haidian District, Beijing.
  • the three categories contain the number of positioning results: 91, 3 and 7, respectively, then the Huilongguan Community in Changping District, Beijing can be used as an activity hotspot in the period from 22:00 to 6:00. Since the user usually works in the company from 9:00 to 17:00 and the user is at home during the period from 22:00 to 6:00, the above method can be used to determine that the user's office location is Beijing. Zhichun Road, Haidian District, the user's residence is Huilongguan Community, Changping District, Beijing.
  • the preset time period is nearly one month.
  • the positioning result of the positioning time in the past month is found, and the positioning results are clustered and faked.
  • Ten categories were obtained, including the first three in the ranking results: Zhichun Road, Haidian District, Beijing, Huilongguan Community, Changping District, Beijing, Zhongguancun, Haidian District, Beijing. Then these three areas can be used as the activity hotspot area of the user in the past month. In this way, changes in the user's hotspot area can be gradually obtained.
  • the LAC value of each LAC may be set according to the number of positioning results in the preset time period, and the LAC whose heat value meets the preset condition is determined as the hot spot LAC.
  • the preset condition may include: the heat value is ranked in the first M, M is a preset positive integer, or the heat value is greater than or equal to a preset heat threshold. That is to say, when a positioning result is obtained, the LAC heat value corresponding to the positioning result is increased, for example, the heat value is increased by 1.
  • the “heat value” refers to the thermal quantization value of the positioning area, which directly reflects the activity heat of the mobile device in the positioning area.
  • the positioning result obtained by GPS or network positioning can be set to contribute more to the heat value than the positioning result obtained by offline positioning. Contribution.
  • the positioning result obtained by the offline positioning method increases the heat value of the LAC to which the positioning result belongs by 1
  • the positioning result obtained by the GPS or the network positioning method increases the heat value of the LAC to which the positioning result belongs by 2.
  • This step can also be implemented in other ways, such as using time series analysis.
  • the time series analysis method When the time series analysis method is adopted, the relationship between the positioning time and the positioning result of each day can be drawn, and the correlation calculation can be performed by using the relation graph, and the positioning result and the positioning time range satisfying the correlation requirement can be obtained, for example, 9:00 ⁇ can be obtained. Some positioning results in the 17:00 time period meet the correlation requirements, and some positioning results in the time period from 22:00 to 6:00 meet the correlation requirements.
  • the time series analysis method can also adopt methods such as modeling, the manner of determining the correlation function, and the like, and the time series analysis method is not specifically described herein.
  • the time series analysis method can obtain the X positioning results in a certain time period to meet the correlation requirement, and the LAC to which the X positioning results belong can be determined as the hotspot LAC in the certain time period.
  • This step may be performed periodically, that is, the active hotspot area is determined at intervals, or may be triggered based on an event, for example, when an application needs to use the active hotspot area, this step is performed.
  • the area corresponding to the hot spot LAC is determined as a hot spot area, and the mobile device is provided with a service based on the determined hot spot area.
  • the description of the hotspot area in the embodiment of the present invention may adopt a combination of the center point latitude and longitude of the hot spot area and the area radius, and may also adopt the administrative area information corresponding to the hot spot area.
  • the administrative division information can be accurate to counties, districts, villages, etc., and can also be accurate to streets, communities, business districts, and even buildings.
  • the module that determines the hot spot area may be encapsulated in the system layer, and an API (ie, a system interface) is provided to the application layer for the mobile application to invoke.
  • an API ie, a system interface
  • the mobile app pushes information based on the hotspot area of the mobile device.
  • a public service such as a public service call system interface can obtain information on food, entertainment, and the like within the hotspot area when the hotspot area of the mobile device is included in the "Qingchun Road, Haidian District, Beijing".
  • the weather forecasting APP invokes the system interface to obtain the hotspot area of the mobile device, including “Beijing Changping District”, and can push the weather information of Changping District of Beijing to the mobile device. and many more.
  • the mobile application preferentially updates the data of the mobile device hotspot area when updating data such as maps, locations, and the like. For example, if the map class APP calls the system interface to obtain the hotspot area of the mobile device for nearly one month, including "Beijing Changping District", then the map data of Changping District of Beijing may be preferably updated.
  • the hotspot area is used as a parameter to adjust the ranking of the search results.
  • the search engine obtains the user inputting the keyword "flower delivery” in the search box, and calls the system interface to obtain the hotspot area of the current time period of the mobile device, including "Qingchun Road, Haidian District, Beijing", then the "Qingchun, Haidian District, Beijing”
  • the road will be sorted ahead of the search results related to Zhichun Road, Haidian District, Beijing, so that users can see the flower delivery service on Zhichun Road in Haidian District, Beijing.
  • the locating area data includes the LAC data and the cell data.
  • the determined hot spot locating area may be a LAC or a cell. If the determined hot spot LAC does not overlap with the hot spot cell, the determined hot spot LAC and the hot spot cell are respectively used as the hot spot area. If the determined hotspot LAC and the hotspot cell overlap, the hotspot LAC or the hotspot cell may be used as the hotspot area. Since the accuracy of the cell is higher, the hotspot cell may be preferred as the hotspot area. Of course, it is also possible to determine whether to select a hotspot LAC or a hotspot cell according to the needs of the application. If the accuracy of the hotspot area required by the application is high, the hotspot cell may be selected as the hotspot area, otherwise the hotspot cell is selected as the hotspot area.
  • the positioning accuracy is usually poor. Generally, it is located at the county and district level, but the data volume of the LAC data is small. The positioning accuracy of the cell data is relatively high, and generally can be located in streets, communities, and even buildings, but the data amount of the cell data is large. Therefore, in order to save the storage space of the mobile device, the LAC data can be preset only in the positioning database when initially configuring the positioning database.
  • the LAC data is used to determine the hotspot LAC area
  • the mobile device obtains the cell data corresponding to the hotspot LAC area from the server, and stores the acquired cell data in the location database. In this way, if the mobile device is in the hotspot LAC area, the cell data can be used for higher precision positioning, thereby achieving the effect of gradual refinement.
  • FIG. 2 is a structural diagram of a device according to an embodiment of the present invention.
  • the device is disposed in a mobile device.
  • the device may include: an offline positioning unit 01, a recording unit 02, and an analysis unit 03, and may further include an acquiring unit. 04.
  • the offline positioning unit 01 is responsible for positioning using a positioning database locally preset by the mobile device, wherein the positioning database contains positioning area data.
  • the foregoing positioning area data may be preset in the positioning database, and may be manually configured or factory configured.
  • the location area data may also be acquired by the obtaining unit 04 from the server and stored in the location database.
  • the recording unit 02 is responsible for recording the positioning result, and can further record the positioning time.
  • the offline positioning unit 01 may adopt, but not limited to, the following two methods when performing positioning:
  • the first method is: determining the base station detected by the mobile device, querying the corresponding location information in the location database according to the location area identifier information corresponding to the detected base, and determining the location result of the mobile device by using the queried location information.
  • This method can be positioned periodically, for example, every preset time. It can also be executed when the located event is triggered. For example, if the operation of the user on the mobile device generates a positioning event, the positioning is performed once.
  • the positioning time recorded by the recording unit 02 is the time when the offline positioning unit 01 performs positioning.
  • the second mode when the mobile device is switched to the location area, the location information is used to query the location information in the location database, and the location information of the mobile device is used to determine the location result of the mobile device.
  • the positioning time recorded by the recording unit 02 is the time when the positioning unit 01 is currently located, or the time from the current positioning time to the time when the mobile device switches to another positioning area.
  • the location information obtained by querying the local database may be the latitude and longitude of the central point, or may be a combination of the latitude and longitude of the central point and the radius of the region, or may be a combination of the latitude and longitude of the central point and the contour information, or may be an administrative division.
  • Information such as the xx area of the xx city of xx province, except for the latitude and longitude of the center point, other location information is the location information.
  • the recording unit 02 may also record the positioning time and the positioning result obtained by using GPS or network positioning, and use it for subsequent determination of the hotspot area. That is, other targeting methods can be used as an aid to offline positioning.
  • the analyzing unit 03 is responsible for determining the hot spot positioning area of the mobile device according to the positioning result recorded by the recording unit 02, and determining the hot spot positioning area as the hot spot area.
  • the time zone may be divided to determine the hot spot area of the preset time period.
  • the preset time period can be in hours, days, weeks, months or even years For granularity.
  • the analyzing unit 03 may set the heat value of each positioning area according to the number of the positioning results in the preset time period, and determine the positioning area whose heat value meets the preset condition as the hot spot positioning area, where the preset condition may include: the heat value. Ranked in the top M, M is a preset positive integer, or the heat value is greater than or equal to the preset heat threshold.
  • the positioning result obtained by using GPS or network positioning mode may be set to contribute more to the heat value than the local preset position of the mobile device.
  • the contribution of the positioning result obtained by the database to the positioning (ie offline positioning mode) to the heat value, that is, when determining the heat value, the positioning result obtained by using the GPS or the network positioning method is greater than the positioning database locally preset by the mobile device.
  • the analyzing unit 03 may further determine the positioning result in the preset time period according to the positioning time and the positioning result; cluster the positioning result in the preset time period to obtain at least one class; and classify the class that meets the preset hotspot area standard
  • the location area is determined as a hotspot location area within a preset time period.
  • the hotspot area standard may be used but not limited to: the number of the positioning results is ranked in the first N, and N is a preset positive integer; or the number of the positioning results is greater than or equal to the preset number threshold.
  • the hotspot area criteria are defined to rule out errors caused by occasional activities.
  • the positioning result may not be temporally divided according to the positioning time, and the hot spot positioning area may be determined for all the positioning results.
  • the analysis unit 03 can also be implemented in other ways, such as using time series analysis.
  • time series analysis method When the time series analysis method is adopted, the relationship between the positioning time and the positioning result of each day can be drawn, and the correlation calculation can be performed by using the relation graph, and the positioning result and the positioning time range satisfying the correlation requirement can be obtained, for example, 9:00 ⁇ can be obtained.
  • the X positioning results in the 17:00 time period satisfy the correlation requirement
  • the X positioning results in the time period from 22:00 to 6:00 satisfy the correlation requirement.
  • the time series analysis method can also adopt methods such as modeling, the manner of determining the correlation function, and the like, and the time series analysis method is not specifically described herein.
  • the time series analysis method can be used to obtain X positioning results in a certain time period to meet the correlation requirement, and X is greater than or equal to a preset number threshold.
  • the location area corresponding to the positioning results may be determined as the hotspot area in the certain time period.
  • the description of the hotspot area in the embodiment of the present invention may adopt a combination of the center point latitude and longitude of the hot spot area and the area radius, and may also adopt the administrative area information corresponding to the hot spot area.
  • the administrative division information can be accurate to counties, districts, villages, etc., and can also be accurate to streets, communities, business districts, and even buildings.
  • the device can be packaged at the system layer and provide an API to the application layer for the mobile application to invoke.
  • the manner of utilizing the hotspot area may include, but is not limited to, the mobile application pushes information based on the hotspot area of the mobile device; when the mobile application updates data such as maps, locations, etc., the data of the hotspot area of the mobile device is preferentially updated; when the search result is provided to the user , using the hotspot area as a parameter to adjust the sorting of search results; and so on.
  • the location area data may include LAC data, and the corresponding hotspot location area is a hotspot LAC.
  • the location area may also include cell data, and the corresponding hotspot location area is a hotspot cell.
  • the locating area may also include LAC data and cell data, and the corresponding hotspot locating area may be a hotspot LAC or a hotspot cell.
  • the LAC data includes LAC identification information and corresponding location information
  • the cell data includes a Cellid (Cell ID) and corresponding location information.
  • LAC data When LAC data is used for positioning, the positioning accuracy is usually poor. Generally, it is located at the county and district level, but the data volume of the LAC data is small. The location data of the cell data is relatively high, and can generally be located in streets, communities, business districts and even buildings, but the data volume of the cell data is large. Therefore, in order to save the storage space of the mobile device, the LAC data can be preset only in the positioning database when initially configuring the positioning database. After the analyzing unit 03 determines the hotspot LAC of the mobile device, the acquiring unit 04 acquires the cell data corresponding to the hot spot LAC from the server, and stores the acquired cell data in the positioning database.
  • the method and apparatus provided by the present invention can have the following advantages:
  • the method for determining a hotspot area according to the present invention is based on the positioning result of the mobile device end, that is, the mobile device side uses a local preset positioning database for positioning, and the offline positioning method does not require a GPS module, and the mobile device does not need to upload the positioning result in real time. On the server side, the impact on mobile device performance and network resources is reduced.
  • the hotspot area determined in the present invention is an area corresponding to the LAC or the cell, and may be It is planar and does not require additional polymerization or the like.
  • the disclosed apparatus and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division, and the actual implementation may have another division manner.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of hardware plus software functional units.
  • the above-described integrated unit implemented in the form of a software functional unit can be stored in a computer readable storage medium.
  • the above software functional unit is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to perform the methods of the various embodiments of the present invention. Part of the steps.
  • the foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like, which can store program codes. .

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Abstract

一种确定热点区域的方法和装置，其中方法包括：移动设备本地预置定位数据库(101)，利用定位数据库进行定位，记录定位时间和定位结果(102)；其中所述定位数据库包含定位区域数据，所述定位区域数据包括定位区域标识及其对应的位置信息；依据所述定位时间和定位结果确定预设时间段的热点定位区域(104)，将所述热点定位区域确定为热点区域(105)。能够降低对网络资源和移动设备性能的影响。

Description

一种确定热点区域的方法和装置 【技术领域】
本发明涉及计算机应用技术领域，特别涉及一种确定热点区域的方法和装置。
【背景技术】
基于服务的目的性和针对性，现在越来越多的服务基于移动设备的位置信息来实现，特别是针对移动设备用户经常活动的位置区域，即热点区域。诸如：移动应用基于移动设备的热点区域进行信息推送；移动应用在更新地图、位置等数据时，优先更新移动设备热点区域的数据；用户在使用移动设备进行搜索时，热点区域作为参数调整搜索结果的排序；等等。
那么如何确定移动设备的热点区域就成为关键。目前常用的方式是在服务器端持续收集移动设备的定位结果，并基于定位结果确定各移动设备的热点区域。然而，这种方式需要移动设备采用GPS或网络定位的方式进行定位，并且持续不断地上传定位结果，对网络资源和移动设备的性能都会造成很大影响。另外，服务器端收集的移动设备的位置信息是点状的，而通常用户活动的热点区域应该是面状的，不能够直接地对热点区域进行反映。
【发明内容】
有鉴于此，本发明提供了一种确定热点区域的方法和装置，以便于降低对网络资源和移动设备性能的影响。
具体技术方案如下：
本发明提供了一种确定热点区域的方法，该方法包括：
利用移动设备本地预置的定位数据库进行定位，记录定位结果；其中所述定位数据库包含定位区域数据，所述定位区域数据包括定位区域标识及其对应的位置信息；
依据所述定位结果确定所述移动设备的热点定位区域，将所述热点定位区域确定为热点区域。
根据本发明一优选实施方式，所述利用移动设备本地预置的定位数据库进行定位包括：
确定所述移动设备探测到的基站，依据探测到的基站对应的定位区域在所述定位数据库中查询对应的位置信息，利用查询到的位置信息确定所述移动设备的定位结果。
根据本发明一优选实施方式，所述利用移动设备本地预置的定位数据库进行定位包括：
监听到所述移动设备发生定位区域的切换时，利用切换后的定位区域对应的标识信息在所述定位数据库中查询对应的位置信息，利用查询到的位置信息确定所述移动设备的定位结果。
根据本发明一优选实施方式，所述定位区域数据预先配置于所述定位数据库；或者，
所述移动设备从服务器端获取所述定位区域数据并存储于所述定位数据库。
根据本发明一优选实施方式，该方法还包括：
记录采用GPS或者网络定位得到的定位结果。
根据本发明一优选实施方式，所述定位区域数据包括位置区码LAC数据，所述热点定位区域为LAC；或者，
所述定位区域数据包括小区数据，所述热点定位区域为小区；或者，
所述热点区域数据包括LAC数据和小区数据，所述热点定位区域为LAC或小区。
根据本发明一优选实施方式，如果所述定位数据库包括LAC数据，则在确定出所述移动设备的热点LAC后，该方法还包括：从所述服务器端获取所述热点LAC对应的小区数据，并将获取的小区数据存储于所述定位数据库。
根据本发明一优选实施方式，依据所述定位结果确定所述移动设备的热点定 位区域包括：
依据定位结果的数量设置各定位区域的热度值，将热度值满足预设条件的定位区域确定为热点定位区域，所述预设条件包括：热度值排在前M个，M为预设的正整数，或者热度值大于或等于预设的热度阈值。
根据本发明一优选实施方式，在确定热度值时，采用GPS或网络定位方式得到的定位结果的权重大于利用移动设备本地预置的定位数据库进行定位得到的定位结果的权重。
根据本发明一优选实施方式，依据所述定位结果确定所述移动设备的热点定位区域包括：
对定位结果进行聚类，得到至少一个类；
将满足预设热点区域标准的类对应的定位区域确定为热点定位区域；其中，所述热点区域标准包括：包含定位结果数量排在前N个，所述N为预设正整数；或者，包含定位结果数量大于或等于预设数量阈值。
根据本发明一优选实施方式，依据所述定位结果确定所述移动设备的热点定位区域包括：
采用时间序列分析法，得到定位时间处于某时间段内的X个定位结果满足相关性要求，将所述X个定位结果对应的定位区域确定为所述某时间段内的热点定位区域，所述X大于或等于预设数量阈值。
根据本发明一优选实施方式，所述热点区域采用以下方式中的至少一种描述：
热点区域的中心点经纬度和区域半径的结合；
热点区域对应的行政区划信息。
本发明还提供了一种确定热点区域的装置，其特征在于，该装置包括：
离线定位单元，用于利用移动设备本地预置的定位数据库进行定位，其中所述定位数据库包含定位区域数据，所述定位区域数据包括定位区域标识及其对应的位置信息；
记录单元，用于记录定位结果；
分析单元，用于依据所述记录单元记录的定位结果，确定所述移动设备的热点定位区域，将所述热点定位区域确定为热点区域。
根据本发明一优选实施方式，所述离线定位单元在进行定位时，具体执行：
确定所述移动设备探测到的基站，依据探测到的基站对应的定位区域在所述定位数据库中查询对应的位置信息，利用查询到的位置信息确定所述移动设备的定位结果。
根据本发明一优选实施方式，所述离线定位单元在进行定位时，具体执行：监听到所述移动设备发生定位区域的切换时，利用切换后的定位区域对应的标识信息在所述定位数据库中查询对应的位置信息，利用查询到的位置信息确定所述移动设备的定位结果。
根据本发明一优选实施方式，所述定位区域数据预先配置于所述定位数据库；或者，
该装置还包括：获取单元，用于从服务器端获取所述定位区域数据并存储于所述定位数据库。
根据本发明一优选实施方式，所述记录单元，还用于记录采用GPS或网络定位方式得到的定位结果。
根据本发明一优选实施方式，所述定位区域数据包括位置区码LAC数据，所述热点定位区域为LAC；或者，
所述定位区域数据包括小区数据，所述热点定位区域为小区；或者，
所述热点区域数据包括LAC数据和小区数据，所述热点定位区域为LAC或小区。
根据本发明一优选实施方式，如果所述定位数据库包括LAC数据；则该装置还包括：获取单元，用于在所述分析单元确定出所述移动设备的热点LAC后，从所述服务器端获取所述热点LAC对应的小区数据，并将获取的小区数据存储于所述定位数据库。
根据本发明一优选实施方式，所述分析单元，具体用于依据定位结果的数量设置各定位区域的热度值，将热度值满足预设条件的定位区域确定为热点定位区域，所述预设条件包括：热度值排在前M个，M为预设的正整数，或者热度值大于或等于预设的热度阈值。
根据本发明一优选实施方式，在确定热度值时，采用GPS或网络定位方式得到的定位结果的权重大于利用移动设备本地预置的定位数据库进行定位得到的定位结果的权重。
根据本发明一优选实施方式，所述分析单元，具体用于：
对定位结果进行聚类，得到至少一个类；
将满足预设热点区域标准的类对应的定位区域确定为热点定位区域；其中，所述热点区域标准包括：包含定位结果数量排在前N个，所述N为预设正整数；或者，包含定位结果数量大于或等于预设数量阈值。
根据本发明一优选实施方式，所述分析单元，具体用于采用时间序列分析法，得到定位时间处于某时间段内的X个定位结果满足相关性要求，将所述X个定位结果对应的定位区域确定为所述某时间段内的热点定位区域，所述X大于或等于预设数量阈值。
根据本发明一优选实施方式，所述热点区域采用以下方式中的至少一种描述：
热点区域的中心点经纬度和区域半径的结合；
热点区域对应的行政区划信息。
由以上技术方案可以看出，本发明确定热点区域的方式是基于移动设备端的定位结果，即移动设备端利用本地预置的定位数据库进行定位，这种离线定位的方式无需GPS模块，也无需移动设备实时上传定位结果给服务器端，降低了对移动设备性能和网络资源的影响。
【附图说明】
图1为本发明实施例提供的确定热点区域的方法流程图；
图2为本发明实施例提供的装置结构图。
【具体实施方式】
为了使本发明的目的、技术方案和优点更加清楚，下面结合附图和具体实施例对本发明进行详细描述。
本发明的核心思想在于，在移动设备本地预置定位数据库，该定位数据库中包括定位区域数据，其中定位区域数据包括定位区域标识及其对应的位置信息。移动设备能够利用本地预置的定位数据库进行定位，记录定位结果。并且在移动设备端依据记录的定位结果确定热点定位区域，将热点定位区域确定为热点区域。
优选地，上述定位区域数据可以包括LAC数据，对应的热点定位区域为热点LAC。上述定位区域也可以包括小区(Cell)数据，对应的热点定位区域为热点小区。上述定位区域也可以包括LAC数据和小区数据，对应的热点定位区域可以为热点LAC或热点小区。其中LAC数据包括LAC标识信息及其对应的位置信息，小区数据包括Cellid(小区标识)及其对应的位置信息。这里的“小区”指的是移动通信中的小区概念，是基站信号的覆盖范围。
本发明实施例中涉及的“热点区域”指的是移动设备经常所处的区域，其反映了用户经常活动的地点范围。
图1为本发明实施例提供的确定热点区域的方法流程图，在该实施例中以定位区域数据为LAC数据，热点定位区域为热点LAC为例。对于定位区域数据为小区数据，热点定位区域为热点小区的实现方式与图1中流程类似。如图1中所示，该方法可以包括以下步骤：
在101中，移动设备本地预置定位数据库。
本步骤中可以将LAC数据预置于定位数据库，可以采用手工配置、出厂配置等方式，也可以采用从服务器端获取的LAC数据后存储于定位数据库的方式。
现有技术情况下，用于定位的数据主要存储于服务器端，在服务器端存 储的数据主要是基站级别的，数据量较大。为了降低对移动设备端的存储压力，本发明实施例中优选地，初始配置时，可以仅在移动设备端的定位数据库中存储LAC数据，LAC数据量相比较基站级别的数据大大降低了数据量，可以从千万级别缩减为万级别，完全可以在移动设备端进行存储。
服务器端基站级别的数据通常包括基站id(标识)、所属的LAC标识以及基站位置信息。本发明实施例中LAC数据可以是基于LAC标识对基站级别的数据进行合并后得到的。LAC数据可以包括LAC标识信息及其对应的位置信息，该位置信息可以包括LAC所覆盖区域的中心点位置信息，还可以包括LAC所覆盖区域的轮廓信息或半径信息。
在对基站数据进行合并时，可以采用聚类的方式。即将属于同一LAC的基站数据基于位置信息进行聚类，大多数情况下，属于同一LAC的基站数据会被聚类成同一类，记录该LAC对应类的中心点的位置信息，该位置信息可以是经纬度，也可以是所在的行政区划信息，例如在xx省xx市xx区，更进一步地，还可以记录LAC对应类的轮廓信息或半径信息。
在有些情况下，例如LAC覆盖的区域过大，则可能会产生同一LAC的基站数据会被聚类成多个类(本发明实施例中所述“多个”指代多于一个)，此时可以对得到的类分别判断是否符合预设的属性标准，如果不符合，则将该类过滤掉。记录该LAC对应的符合属性标准的类的中心点的位置信息，还可以进一步记录符合属性标准的类的轮廓信息。
其中，上述属性标准可以采用但不限于以下所列中之一或任意组合：
1)类内基站的创建时间在最近的预设时间范围内。这种情况是为了防止有些基站创建时间很久，有可能实际的基站已经不再使用，但数据库中的基站数据未及时更新，对于这种情况产生的类可以将其过滤掉，不进行记录。
2)类的覆盖面积大于或等于预设的面积标准。有些基站离散于其他大多数基站而分布成一小类，用户在该类所覆盖区域的概率相比较其他类通常要低得多，往往是一些在距离市区很远的某些地方，基于某种特殊的需求而 创建的基站，因此对于这种情况产生的类可以将其过滤掉。
3)类内基站的数量大于或等于预设的数量标准。通常对于用户较密集、需求量比较高的地方，通常会设置较多数量的基站。与上述第2)种情况类似的，有些基站离离散于其他大多数基站而分布成一小类，用户在该类所覆盖区域的概率相比较其他类通常要低得多，因此对于这种情况产生的类可以将其过滤掉。
也就是说，进行上述过滤后最终得到的类所覆盖的区域即为该LAC覆盖的区域。
在对基站数据基于位置信息进行聚类时，可以采用诸如K-means、K-medoids、DBSCAN(Density-Based Spatial Clustering of Applications with Noise，,具有噪声的基于密度的聚类方法)等聚类方法，本发明对聚类方式不加以限制。
在确定类的轮廓信息时，可以采用多种轮廓确定方法，在此以其中一种方式为例：将类中每一个基站数据作为一个位置点，确定类中一个位于该类中各点中最外侧的点作为第一轮廓点；确定与第一轮廓点相邻的、且与第一轮廓点相连形成直线后使得所有位置点均位于该直线上或直线的同一侧的第二轮廓点，将第二轮廓点送入轮廓点队列；从第二轮廓点开始，用同样的方法依次找到其他轮廓点，直到再次找到第一轮廓点并将第一轮廓点列入轮廓点队列为止。最终轮廓点队列中的位置点就是该类的轮廓，即位于该类所覆盖区域最外侧的采样点。
小区数据是服务器端根据定位数据得到的，将定位数据中属于同一小区的定位结果进行整合，在进行整合时，也可以采用对属于同一小区的定位结果进行聚类的方式。同样，在聚类后产生至少一个类，同样可以对这些类进行过滤。将最终得到的类覆盖的区域作为该小区对应的区域，该区域的位置信息可以包括中心点的位置信息，还可以包括该区域的轮廓信息或半径信息。其中聚类方式、过滤方式、轮廓信息的确定方式均与LAC数据中的处理类似， 不再赘述。其中中心点的位置信息可以采用经纬度进行描述，或者采用行政区划信息进行描述。然后记录Cellid及其对应的位置信息得到小区数据。
在102中，利用移动设备本地预置的定位数据库进行定位，记录定位时间和定位结果。
本步骤的实现可以采用但不限于以下两种方式：
第一种方式：确定移动设备当前探测到的基站，依据当前探测到的基站所属的LAC标识信息在定位数据库中查询对应的位置信息，利用查询到的位置信息确定移动设备的定位结果。
这种方式可以周期性进行定位，例如每隔预设的时间进行一次定位。也可以在被定位事件触发时执行，例如用户在移动设备上的操作产生了定位事件，则进行一次定位。
这种情况下，记录的定位时间就是执行本方式进行定位时的时间。
第二种方式：监听到移动设备发生LAC切换时，利用切换后的LAC对应的标识信息在定位数据库中查询对应的位置信息，利用查询到的位置信息确定移动设备的定位结果。
这种方式是在发生LAC切换时执行的定位方式。这种情况下，记录的定位时间可以是执行本方式进行定位时的时间，也可以是一个时间段，即从发生切换的时间到下次发生切换的时间。例如当监听到移动设备从LAC1切换到LAC2，那么利用LAC2的标识在定位数据库中查询对应的位置信息，利用该LAC2的位置信息确定移动设备的定位结果，此时的时间为t1。经过一段时间后，在t2又监听到从LAC2切换到LAC3，那么记录LAC2的位置信息对应的定位时间为t1至t2。也就是说，在t1至t2这段时间内，移动设备位于LAC2的区域范围内。
上述两种方式中，经查询本地数据库获得的位置信息可以是中心点的经纬度，也可以是中心点经纬度与区域半径的结合，也可以是中心点经纬度与轮廓信息的结合，也可以是行政区划信息，例如xx省xx市xx区，除了中心 点的经纬度之外，其他位置信息都是面状位置信息。
另外，上述两种方式是离线定位方式，无需消耗网络流量，也无需具有GPS模块。在本发明实施例中，进行定位的模块可以封装在系统层，并提供API供应用层调用。当需要进行离线定位时，调用该API以获得定位结果。
在103中，记录移动设备采用其他定位方式得到的定位时间和定位结果。
在本发明实施例中，诸如GPS或网络定位等其他定位方式获得的定位时间和定位结果也可以在移动设备端进行记录，并用于后续确定热点区域时使用。即其他定位方式可以作为离线定位的辅助。其中网络定位指的是定位逻辑在服务器端，由服务器端完成移动设备的定位处理后，通过网络将定位结果返回给移动设备的方式，诸如基站定位、wifi定位等都属于网络定位。
需要说明的是，上述102和103并没有固定的先后顺序，是两种各自独立的定位方式。且实际中，可以只执行102或只执行103。
在104中，依据记录的定位时间和定位结果，确定预设时间段的热点LAC。
由于通常用户的活动是有强烈的时间性的，即不同的时间段活动热点区域可能是不同的。例如在白天的活动热点区域为办公室，在晚上的活动热点区域为家。再例如，用户去年住在海淀区，那么其热点活动区域为海淀区，今年住在朝阳区，那么其热点活动区域为朝阳区。
那么在确定移动设备的热点区域时，可以依据时间段进行划分，确定预设时间段的热点区域。该预设时间段可以以小时、天、星期、月甚至年为粒度。
当然，在确定热点区域时，也可以不对时间段进行限制和划分。相应地，在102中，利用移动设备本地预置的定位数据库进行定位时，记录定位结果即可，而无需记录定位时间。在103中，记录移动设备采用其他定位方式得到的定位结果即可。在104中，依据记录的定位结果，确定热点LAC。
具体地，可以依据定位时间和定位结果，确定预设时间段内的定位结果； 对该预设时间段内的定位结果进行聚类，得到至少一个类；然后将满足预设热点区域标准的类对应的LAC确定为该预设时间段内的热点LAC，该热点LAC就是移动设备在该预设时间段内的活动热点区域。其中预设的热点区域标准可以采用但不限于：包含定位结果数量排在前N个，N为预设正整数；包含定位结果数量大于或等于预设的数量阈值。例如将包含定位结果数量最多的类确定为热点区域。定义热点区域标准是为了排除一些偶然性的活动所产生的误差。理想情况下，类中所有的定位结果都属于同一LAC，也有些偶然情况会引起误差，例如移动设备所处位置正好处于LAC切换的附近位置，导致移动设备可能接入不同LAC，对于这种情况，取类中大多数定位结果对应的LAC为热点LAC。
举个例子，预设两个时间段，一个时间段为：9:00～17:00；一个时间段为10:00～6:00。依据记录的定位时间和定位结果，从中找到定位时间在9:00～17:00内的定位结果，将这些定位结果进行聚类，假设得到三个类，一个类，这三个类对应的位置信息分别为：北京市海淀区知春路、北京市海淀区牡丹园和北京市海淀区北京大学。这三个类包含的定位结果数量分别为：88、10和2，那么可以将北京市海淀区知春路作为9:00～17:00时间段的活动热点区域。再从记录的定位时间和定位结果中找到定位时间在22:00～6:00内的定位结果，将这些定位结果进行聚类，假设也得到三个类，这三个类对应的位置信息分别为：北京市昌平区回龙观小区、北京市朝阳区三里屯、北京市海淀区民族大学。这三个类包含的定位结果数量分别为：91、3和7，那么可以将北京市昌平区回龙观小区作为22:00～6:00时间段内的活动热点区域。由于通常情况下，在9:00～17:00时间段内用户在公司办公，在22:00～6:00时间段内用户在家休息，因此采用上述方式就可以确定出用户的办公地点为北京市海淀区知春路，用户的住所为北京市昌平区回龙观小区。
再举个例子，预设时间段为近一个月，依据记录的定位时间和定位结果，从中找到定位时间在近一个月内的定位结果，将这些定位结果进行聚类，假 设得到十个类，包含定位结果数量排在前3个的类分别为：北京市海淀区知春路、北京市昌平区回龙观小区、北京市海淀区中关村。那么可以将这三个区域作为用户在近一个月内的活动热点区域。通过这种方式就可以逐渐得到用户热点区域的变化。
除了步骤104所描述的方式之外，还可以采用依据预设时间段内定位结果的数量设置各LAC的热度值，将热度值满足预设条件的LAC确定为热点LAC。这里预设条件可以包括：热度值排在前M个，M为预设正整数，或者热度值大于或等于预设的热度阈值。也就是说，当得到一个定位结果时，该定位结果对应的LAC热度值就有所增加，例如将热度值加1，当确定热点LAC时，可以将预设时间段内热度值最高的LAC确定为热点LAC。在本发明实施例中“热度值”指的是定位区域的热度量化值，其直接反映了移动设备在该定位区域的活动热度。
对于这种方式，由于GPS或网络定位等方式的定位精度较高，因此可以设置采用GPS或网络定位方式得到的定位结果对热度值的贡献度高于采用离线定位方式得到的定位结果对热度值的贡献度。例如，离线定位方式得到的定位结果对该定位结果所属LAC的热度值增加1，GPS或网络定位方式得到的定位结果对该定位结果所属LAC的热度值增加2。
本步骤还可以采用其他方式实现，诸如采用时间序列分析法。当采用时间序列分析法时，可以绘制每天的定位时间与定位结果的关系图，利用关系图进行相关性计算，可以得到满足相关性要求的定位结果以及定位时间范围，例如可以得到9:00～17:00时间段内的一些定位结果满足相关性要求，得到22：00～6:00时间段内的一些定位结果满足相关性要求。除了绘制关系图的方式之外，时间序列分析法还可以采用诸如建模的方式、确定相关函数的方式等等，在此不对时间序列分析法进行具体描述。总之，采用时间序列分析法可以得到某时间段内的X个定位结果满足相关性要求，可以将该X个定位结果所属的LAC确定为所述某时间段内的热点LAC。
本步骤可以是周期性执行的，即每隔一段时间确定出活动热点区域，也可以是基于事件触发的，例如当有应用需要使用活动热点区域时，执行本步骤。
在105中，将热点LAC对应的区域确定为热点区域，基于确定出的热点区域向移动设备提供服务。
本发明实施例中热点区域的描述可以采用热点区域的中心点经纬度和区域半径的结合，也可以采用热点区域对应的行政区划信息。该行政区划信息可以精确到县、区、村等，也可以精确到街道、社区、商圈、甚至楼宇。
本发明实施例中可以将确定热点区域的模块封装在系统层，并向应用层提供API(即系统接口)供移动应用进行调用。
在确定出热点区域后，可以有多种利用方式，可以包括但不限于：
移动应用基于移动设备的热点区域进行信息推送。例如，大众点评等生活服务类APP调用系统接口获取到移动设备的热点区域包括“北京市海淀区知春路”时，可以推送该热点区域范围内的美食、娱乐等信息。天气预报类APP调用系统接口获取到移动设备的热点区域包括“北京市昌平区”，则可以向移动设备推送北京市昌平区的天气信息。等等。
移动应用在更新地图、位置等数据时，优先更新移动设备热点区域的数据。例如地图类APP调用系统接口获取到移动设备近一个月的热点区域包括“北京市昌平区”，那么可以优选更新北京市昌平区的地图数据。
向用户提供搜索结果时，将热点区域作为参数调整搜索结果的排序。例如搜索引擎获取到用户在搜索框中输入关键词“鲜花快递”，调用系统接口获取到移动设备当前时间段的热点区域包括“北京市海淀区知春路”，那么可以将“北京市海淀区知春路”作为参数，将与北京市海淀区知春路相关的搜索结果的排序提前，这样用户就能够优先从搜索结果中看到北京市海淀区知春路上的鲜花快递服务。
除了定位区域数据包括LAC数据或小区数据的情况之外，还可以存在 定位区域数据包括LAC数据和小区数据的情况，对于这种情况，确定出的热点定位区域可以是LAC，也可以是小区。如果确定出的热点LAC与热点小区不存在重叠，则将确定的热点LAC和热点小区分别作为热点区域。如果确定的热点LAC和热点小区存在重叠，则可以采用热点LAC或者热点小区作为热点区域，由于小区的精度更高，因此可以优选热点小区作为热点区域。当然也可以根据应用的需要来确定是选择热点LAC还是热点小区。如果该应用需要的热点区域精度较高，则可以选择热点小区作为热点区域，否则选择热点小区作为热点区域。
当采用LAC数据进行定位时，通常定位精度较差，一般定位到县、区级别，但LAC数据的数据量较小。利用小区数据的定位精度较高，一般可以定位到街道、社区甚至楼宇，但小区数据的数据量较大。因此为了节省移动设备的存储空间，可以在初始配置定位数据库时，仅在定位数据库中预置LAC数据。当利用LAC数据确定出热点LAC区域时，移动设备再从服务器端获取该热点LAC区域对应的小区数据，将获取的小区数据存储于定位数据库。这样后续在进行定位时，如果移动设备在该热点LAC区域中，则可以采用小区数据做精度更高的定位，从而达到逐步求精的效果。
以上是对本发明提供的方法进行的详细描述，下面对本发明提供的装置进行详细描述。
图2为本发明实施例提供的装置结构图，该装置设置于移动设备中，如图2所示，该装置可以包括：离线定位单元01、记录单元02和分析单元03，还可以包括获取单元04。
离线定位单元01负责利用移动设备本地预置的定位数据库进行定位，其中定位数据库包含定位区域数据。上述的定位区域数据可以预置于定位数据库，可以采用手工配置、出厂配置等方式。也可以由获取单元04从服务器端获取定位区域数据后存储于定位数据库。
记录单元02负责记录定位结果，还可以进一步记录定位时间。
具体地，离线定位单元01在进行定位时，可以采用但不限于以下两种方式：
第一种方式：确定移动设备探测到的基站，依据探测到的基对应的定位区域标识信息在定位数据库中查询对应的位置信息，利用查询到的位置信息确定移动设备的定位结果。
这种方式可以周期性进行定位，例如每隔预设的时间进行一次定位。也可以在被定位事件触发时执行，例如用户在移动设备上的操作产生了定位事件，则进行一次定位。
这种情况下，记录单元02记录的定位时间就是离线定位单元01进行定位时的时间。
第二种方式：监听到移动设备发生定位区域的切换时，利用切换后的定位区域对应的标识信息在定位数据库中查询对应的位置信息，利用查询到的位置信息确定移动设备的定位结果。
这种情况下，记录单元02记录的定位时间为定位单元01本次定位的时间，或者为本次定位的时间至移动设备切换到其他定位区域的时间。
上述两种方式中，经查询本地数据库获得的位置信息可以是中心点的经纬度，也可以是中心点经纬度与区域半径的结合，也可以是中心点经纬度与轮廓信息的结合，也可以是行政区划信息，例如xx省xx市xx区，除了中心点的经纬度之外，其他位置信息都是面状位置信息。
除此之外，由于移动设备中可能还存在GPS模块或网络定位单元，那么记录单元02也可以记录采用GPS或网络定位方式得到的定位时间和定位结果，并用于后续确定热点区域时使用。即其他定位方式可以作为离线定位的辅助。
分析单元03负责依据记录单元02记录的定位结果，确定移动设备的热点定位区域，将热点定位区域确定为热点区域。
由于通常用户的活动是有强烈的时间性的，即不同的时间段活动热点区域可能是不同的。那么在确定移动设备的热点区域时，可以依据时间段进行划分，确定预设时间段的热点区域。该预设时间段可以以小时、天、星期、月甚至年 为粒度。具体地，分析单元03可以依据预设时间段内定位结果的数量设置各定位区域的热度值，将热度值满足预设条件的定位区域确定为热点定位区域，其中预设条件可以包括：热度值排在前M个，M为预设的正整数，或者热度值大于或等于预设的热度阈值。
分析单元03在依据预设时间段内定位结果的数量设置各定位区域的热度值时，可以设置采用GPS或网络定位方式得到的定位结果对热度值的贡献度大于利用移动设备本地预置的定位数据库进行定位(即离线定位方式)得到的定位结果对热度值的贡献度，即在确定热度值时，采用GPS或网络定位方式得到的定位结果的权重大于利用移动设备本地预置的定位数据库进行定位(即离线定位方式)得到的定位结果的权重。
分析单元03还可以依据定位时间和定位结果，确定预设时间段内的定位结果；对预设时间段内的定位结果进行聚类，得到至少一个类；将满足预设热点区域标准的类对应的定位区域确定为预设时间段内的热点定位区域。
其中热点区域标准可以采用但不限于：包含定位结果数量排在前N个，N为预设正整数；或者，包含定位结果数量大于或等于预设数量阈值。定义热点区域标准是为了排除一些偶然性的活动所产生的误差。
当然也可以不依据定位时间对定位结果进行时间上的划分，而针对所有定位结果来确定热点定位区域。
分析单元03还可以采用其他方式实现，诸如采用时间序列分析法。当采用时间序列分析法时，可以绘制每天的定位时间与定位结果的关系图，利用关系图进行相关性计算，可以得到满足相关性要求的定位结果以及定位时间范围，例如可以得到9:00～17:00时间段内的X个定位结果满足相关性要求，得到22：00～6:00时间段内的X个定位结果满足相关性要求。除了绘制关系图的方式之外，时间序列分析法还可以采用诸如建模的方式、确定相关函数的方式等等，在此不对时间序列分析法进行具体描述。总之，采用时间序列分析法可以得到某时间段内的X个定位结果满足相关性要求，X大于或等于预设的数量阈值， 可以将这些定位结果对应的定位区域确定为所述某时间段内的热点区域。
本发明实施例中热点区域的描述可以采用热点区域的中心点经纬度和区域半径的结合，也可以采用热点区域对应的行政区划信息。该行政区划信息可以精确到县、区、村等，也可以精确到街道、社区、商圈、甚至楼宇。
该装置可以封装在系统层，并向应用层提供API供移动应用进行调用。对热点区域的利用方式可以包括但不限于：移动应用基于移动设备的热点区域进行信息推送；移动应用在更新地图、位置等数据时，优先更新移动设备热点区域的数据；向用户提供搜索结果时，将热点区域作为参数调整搜索结果的排序；等等。
优选地，上述定位区域数据可以包括LAC数据，对应的热点定位区域为热点LAC。上述定位区域也可以包括小区(Cell)数据，对应的热点定位区域为热点小区。上述定位区域也可以包括LAC数据和小区数据，对应的热点定位区域可以为热点LAC或热点小区。其中LAC数据包括LAC标识信息及其对应的位置信息，小区数据包括Cellid(小区标识)及其对应的位置信息。
当采用LAC数据进行定位时，通常定位精度较差，一般定位到县、区级别，但LAC数据的数据量较小。利用小区数据的定位精度较高，一般可以定位到街道、社区、商圈甚至楼宇，但小区数据的数据量较大。因此为了节省移动设备的存储空间，可以在初始配置定位数据库时，仅在定位数据库中预置LAC数据。在分析单元03确定出移动设备的热点LAC后，获取单元04再从服务器端获取热点LAC对应的小区数据，并将获取的小区数据存储于定位数据库。
由以上描述可以看出，本发明提供的方法和装置可以具备以下优点：
1)本发明确定热点区域的方式是基于移动设备端的定位结果，即移动设备端利用本地预置的定位数据库进行定位，这种离线定位的方式无需GPS模块，也无需移动设备实时上传定位结果给服务器端，降低了对移动设备性能和网络资源的影响。
2)本发明中确定的热点区域为LAC或小区对应的区域，本身就可以是 面状的，无需进行额外的聚合等处理。
在本发明所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
上述以软件功能单元的形式实现的集成的单元，可以存储在一个计算机可读取存储介质中。上述软件功能单元存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或处理器(processor)执行本发明各个实施例所述方法的部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内，所做的任何修改、等同替换、改进等，均应包含在本发明保护的范围之内。

Claims (24)

  1. 一种确定热点区域的方法，其特征在于，该方法包括：
    利用移动设备本地预置的定位数据库进行定位，记录定位结果；其中所述定位数据库包含定位区域数据，所述定位区域数据包括定位区域标识及其对应的位置信息；
    依据所述定位结果确定所述移动设备的热点定位区域，将所述热点定位区域确定为热点区域。
  2. 根据权利要求1所述的方法，其特征在于，所述利用移动设备本地预置的定位数据库进行定位包括：
    确定所述移动设备探测到的基站，依据探测到的基站对应的定位区域在所述定位数据库中查询对应的位置信息，利用查询到的位置信息确定所述移动设备的定位结果。
  3. 根据权利要求1所述的方法，其特征在于，所述利用移动设备本地预置的定位数据库进行定位包括：
    监听到所述移动设备发生定位区域的切换时，利用切换后的定位区域对应的标识信息在所述定位数据库中查询对应的位置信息，利用查询到的位置信息确定所述移动设备的定位结果。
  4. 根据权利要求1所述的方法，其特征在于，所述定位区域数据预先配置于所述定位数据库；或者，
    所述移动设备从服务器端获取所述定位区域数据并存储于所述定位数据库。
  5. 根据权利要求1所述的方法，其特征在于，该方法还包括：
    记录采用GPS或者网络定位得到的定位结果。
  6. 根据权利要求1所述的方法，其特征在于，所述定位区域数据包括位置区码LAC数据，所述热点定位区域为LAC；或者，
    所述定位区域数据包括小区数据，所述热点定位区域为小区；或者，
    所述热点区域数据包括LAC数据和小区数据，所述热点定位区域为LAC 或小区。
  7. 根据权利要求6所述的方法，其特征在于，如果所述定位数据库包括LAC数据，则在确定出所述移动设备的热点LAC后，该方法还包括：从所述服务器端获取所述热点LAC对应的小区数据，并将获取的小区数据存储于所述定位数据库。
  8. 根据权利要求1至7任一权项所述的方法，其特征在于，依据所述定位结果确定所述移动设备的热点定位区域包括：
    依据定位结果的数量设置各定位区域的热度值，将热度值满足预设条件的定位区域确定为热点定位区域，所述预设条件包括：热度值排在前M个，M为预设的正整数，或者热度值大于或等于预设的热度阈值。
  9. 根据权利要求8所述的方法，其特征在于，在确定热度值时，采用GPS或网络定位方式得到的定位结果的权重大于利用移动设备本地预置的定位数据库进行定位得到的定位结果的权重。
  10. 根据权利要求1至7任一权项所述的方法，其特征在于，依据所述定位结果确定所述移动设备的热点定位区域包括：
    对定位结果进行聚类，得到至少一个类；
    将满足预设热点区域标准的类对应的定位区域确定为热点定位区域；其中，所述热点区域标准包括：包含定位结果数量排在前N个，所述N为预设正整数；或者，包含定位结果数量大于或等于预设数量阈值。
  11. 根据权利要求1至7任一权项所述的方法，其特征在于，依据所述定位结果确定所述移动设备的热点定位区域包括：
    采用时间序列分析法，得到定位时间处于某时间段内的X个定位结果满足相关性要求，将所述X个定位结果对应的定位区域确定为所述某时间段内的热点定位区域，所述X大于或等于预设数量阈值。
  12. 根据权利要求1至7任一权项所述的方法，其特征在于，所述热点区域采用以下方式中的至少一种描述：
    热点区域的中心点经纬度和区域半径的结合；
    热点区域对应的行政区划信息。
  13. 一种确定热点区域的装置，其特征在于，该装置包括：
    离线定位单元，用于利用移动设备本地预置的定位数据库进行定位，其中所述定位数据库包含定位区域数据，所述定位区域数据包括定位区域标识及其对应的位置信息；
    记录单元，用于记录定位结果；
    分析单元，用于依据所述记录单元记录的定位结果，确定所述移动设备的热点定位区域，将所述热点定位区域确定为热点区域。
  14. 根据权利要求13所述的装置，其特征在于，所述离线定位单元在进行定位时，具体执行：
    确定所述移动设备探测到的基站，依据探测到的基站对应的定位区域在所述定位数据库中查询对应的位置信息，利用查询到的位置信息确定所述移动设备的定位结果。
  15. 根据权利要求13所述的装置，其特征在于，所述离线定位单元在进行定位时，具体执行：监听到所述移动设备发生定位区域的切换时，利用切换后的定位区域对应的标识信息在所述定位数据库中查询对应的位置信息，利用查询到的位置信息确定所述移动设备的定位结果。
  16. 根据权利要求13所述的装置，其特征在于，所述定位区域数据预先配置于所述定位数据库；或者，
    该装置还包括：获取单元，用于从服务器端获取所述定位区域数据并存储于所述定位数据库。
  17. 根据权利要求13所述的装置，其特征在于，所述记录单元，还用于记录采用GPS或网络定位方式得到的定位结果。
  18. 根据权利要求13所述的装置，其特征在于，所述定位区域数据包括位置区码LAC数据，所述热点定位区域为LAC；或者，
    所述定位区域数据包括小区数据，所述热点定位区域为小区；或者，
    所述热点区域数据包括LAC数据和小区数据，所述热点定位区域为LAC或小区。
  19. 根据权利要求18所述的装置，其特征在于，如果所述定位数据库包括LAC数据；则该装置还包括：获取单元，用于在所述分析单元确定出所述移动设备的热点LAC后，从所述服务器端获取所述热点LAC对应的小区数据，并将获取的小区数据存储于所述定位数据库。
  20. 根据权利要求13至19任一权项所述的装置，其特征在于，所述分析单元，具体用于依据定位结果的数量设置各定位区域的热度值，将热度值满足预设条件的定位区域确定为热点定位区域，所述预设条件包括：热度值排在前M个，M为预设的正整数，或者热度值大于或等于预设的热度阈值。
  21. 根据权利要求20所述的装置，其特征在于，在确定热度值时，采用GPS或网络定位方式得到的定位结果的权重大于利用移动设备本地预置的定位数据库进行定位得到的定位结果的权重。
  22. 根据权利要求13至19任一权项所述的装置，其特征在于，所述分析单元，具体用于：
    对定位结果进行聚类，得到至少一个类；
    将满足预设热点区域标准的类对应的定位区域确定为热点定位区域；其中，所述热点区域标准包括：包含定位结果数量排在前N个，所述N为预设正整数；或者，包含定位结果数量大于或等于预设数量阈值。
  23. 根据权利要求13至19任一权项所述的装置，其特征在于，所述分析单元，具体用于采用时间序列分析法，得到定位时间处于某时间段内的X个定位结果满足相关性要求，将所述X个定位结果对应的定位区域确定为所述某时间段内的热点定位区域，所述X大于或等于预设数量阈值。
  24. 根据权利要求13至19任一权项所述的装置，其特征在于，所述热点区域采用以下方式中的至少一种描述：
    热点区域的中心点经纬度和区域半径的结合；
    热点区域对应的行政区划信息。
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