CN101887440A - Hot spot analytic system and method - Google Patents
Hot spot analytic system and method Download PDFInfo
- Publication number
- CN101887440A CN101887440A CN2009101390013A CN200910139001A CN101887440A CN 101887440 A CN101887440 A CN 101887440A CN 2009101390013 A CN2009101390013 A CN 2009101390013A CN 200910139001 A CN200910139001 A CN 200910139001A CN 101887440 A CN101887440 A CN 101887440A
- Authority
- CN
- China
- Prior art keywords
- hot spot
- information
- focus group
- spot region
- screening
- 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
Images
Abstract
The invention relates to a hot spot analytic system and a method. The hot spot analytic system comprises a database, a filtering module, a grouping module and an analyzing module, wherein the database stores a plurality of records, each record at least comprises one situation message, and the situation message at least comprises one time message and one position message; the filtering module filters to obtain a plurality of filter records according to the current situation message and records, wherein the current situation message at least comprises one current time message; the grouping module groups according to the position message of the filter record to obtain at least one hot spot group and generate a corresponding hot spot area for each hot spot group; and the analyzing module respectively generates an integral heat degree for each hot spot group according to the number of the filter records in each hot spot group and the size of the corresponding hot spot area, and provides at least one hot spot area message according to the integral heat degree of each hot spot group and the corresponding hot spot area thereof.
Description
Technical field
The invention relates to a kind of hot spot analytic system and method, but especially be particularly to a kind of hot spot analytic system and the method for focus of analyze demands so that hot spot region information to be provided.
Background technology
Because the elasticity of taxi makes taxi become one of the important vehicles in city with convenient.At present, the dial-a-cab of taxi normally must be called administrative center to taxi by the user, and administrative center selects by different mechanism and sends specific taxi to the specified place of user.
For instance, U.S. Patent Publication No. proposes for No. 20040177109 to link up behavior by the chauffeur that CCC utilizes communication network to be connected in series between taxi and the passenger.In addition, the Taiwan patent proposes one for I224743 number and sends module automatically, and its chauffeur place according to the user utilizes the specific rule of sending to select and send near vehicle.
In general, known technology focuses on that improving chauffeur flow process and vehicle selects and the technology of sending, and does not all have for the cabin factor of taxi or the problems such as waiting time that shorten the passenger and mentions.Yet, in some cases, when the zone of user present position belongs to the user who has many proposition dial-a-cab in remote or the zone simultaneously, because the taxi in the zone is limited, the time of user's average waiting taxi will be elongated, thereby causes the unhappy of user and inconvenience.On the other hand, if when having too many taxi in the zone, the situation that can cause also that taxi empty wagons number is too high, cabin factor is on the low side or rob the visitor takes place, and makes that the operation costs of taxi increase, business revenue reduces, and quite is not inconsistent economic benefit.Therefore, this case wishes to propose a kind of solution of effective analysis of central issue, as when being applied in taxi, can analyze the carrying focus of taxi, for taxi provides hot spot region information, and then improving the cabin factor of taxi, and reduce passenger's waiting time, can significantly reduce the operation costs of taxi, improve its economic benefit.
Summary of the invention
In view of this, the objective of the invention is to propose a kind of hot spot analytic system and method.System and method particularly suitable of the present invention but do not limit is applied in the analysis of central issue that taxi takes, in the time of further, also can be applicable to other various analysiss of central issue, for example common people tourist hot spot analysis, the analysis of central issue of food and drink shop, parking stall analysis of central issue, road traffic analysis of central issue or the like.
A kind of hot spot analytic system of the embodiment of the invention comprises a database, screening module, hive off a module and an analysis module.Database storage has many notes records, and wherein, each record comprises a contextual information at least, and contextual information comprises a time information and a positional information at least.The screening module is according to a present contextual information and a record, and screening obtains many screening records, and wherein, contextual information comprises a present temporal information at least at present.The module of hiving off is hived off according to the positional information of screening record, obtains at least one focus group, and be hot spot region that each focus group produces correspondence.Analysis module is according to the number and corresponding hot spot region size of screening record in each focus group, produce a whole temperature for each focus group respectively, and whole temperature and corresponding hot spot region thereof according to each focus group provide at least one hot spot region information.
A kind of analysis of central issue method of the embodiment of the invention.At first, provide a database.Database storage has many notes records, and wherein, each record comprises a contextual information at least, and contextual information comprises a time information and a positional information at least.Then, obtain a present contextual information, wherein, contextual information comprises a present temporal information at least at present.Afterwards, according to the record at present contextual information and the database, screening obtains many screening records, and hives off according to the positional information of screening record, obtains at least one focus group, and be hot spot region that each focus group produces correspondence.Afterwards, number and corresponding hot spot region size according to screening record in each focus group, produce a whole temperature for each focus group respectively, and, provide at least one hot spot region information according to the whole temperature of each focus group and corresponding hot spot region thereof.
In certain embodiments, can be according to the positional information of each screening record in each focus group, for each focus group with/or corresponding hot spot region name.
In certain embodiments, can produce a relative temperature to each focus group respectively according to the whole temperature of each focus group and each focus group and the distance of a current position information of contextual information at present.In addition, in certain embodiments, can according to the number of mobile device in the relative temperature of each focus group, the corresponding hot spot region, with the hot spot region of corresponding each focus group in event and participation number thereof, respectively to each focus group generation one real-time temperature.
Said method of the present invention can exist by program code means.When program code was loaded and carries out by machine, machine became in order to carry out device of the present invention.
For above-mentioned purpose of the present invention, feature and advantage can be become apparent, embodiment cited below particularly, and cooperate appended accompanying drawing, be described in detail as follows.
Description of drawings
Fig. 1 is a synoptic diagram that shows according to the hot spot analytic system of the embodiment of the invention.
Fig. 2 is a process flow diagram that shows according to the analysis of central issue method of the embodiment of the invention.
Fig. 3 is a process flow diagram that shows according to the focus screening technique of the embodiment of the invention.
Fig. 4 is a process flow diagram that shows according to the focus group/hot spot region naming method of the embodiment of the invention.
Fig. 5 is a process flow diagram that shows according to the temperature computing method of the embodiment of the invention.
Drawing reference numeral:
100～temperature analytic system;
110～database;
120～screening module;
130～the module of hiving off;
140～analysis module;
150～end device;
S210, S220 ..., S250～step;
S221, S222, S223, S224～step;
S410, S420, S430, S440～step;
S241, S242, S243, S244～step.
Embodiment
Fig. 1 shows the hot spot analytic system according to the embodiment of the invention.Hot spot analytic system 100 according to the embodiment of the invention goes for an electronic installation, and described electronic installation can be server, workstation, information station (KIOSK), computing machine, mobile computer, palmtop computer, industrial computer, personal digital aid (PDA), intelligent mobile phone, satellite navigation machine or other any end device that computing function is provided etc.
Hot spot analytic system 100 comprise at least a database 110, a screening module 120, hive off module 130, with an analysis module 140.Database 110 comprises many notes records, as the chauffeur record.The chauffeur record can be phone chauffeur record and roadside chauffeur record.Each record comprises a contextual information at least, as temporal information, positional information, and Weather information etc.What note is, the record in the database 110 can be to be sent to database 110 via a remote data base (not shown) or an end device 150 via a communication network to be stored, and described end device can also be a mobile device.In another embodiment, described system 100 more includes an operation-interface, in order to import described contextual information.
The module of hiving off 130 can be hived off screening record, thereby obtains at least one focus group.In certain embodiments, the module of hiving off 130 can be utilized the algorithm that hives off, the polymerization algorithm (Hierarchical Agglomerative Clustering Algorithm) that hives off as hierarchy type, come to hive off according to the position between current position information and each the screening record, and be that each focus group produces a corresponding hot spot region for the screening record.The generation of described hot spot region can have numerous embodiments, for example according to the position of all focuses in each focus group, calculate can contain all focuses in each focus group a regional extent as described hot spot region; Or according to the focus of position outermost in each focus group, its position of connecting is to iris out a regional extent as described hot spot region; Or, compare the hotspot location of each focus group and actual geographic area (or administrative region, contain specific landmark/the build zone in thing/highway section), to judge the actual geographic area that the position meets or distance is close (or administrative region, contain specific landmark/the build zone in thing/highway section) as described hot spot region etc.
In certain embodiments, hot spot analytic system 100 can more comprise a name module and a position model (not shown).Position model is the semantic structure of recording geographical position, as multiple tracks road unit, and as the definition of intersection, highway section, sight spot and/or terrestrial reference, and the annexation of road unit.The name module can be named for each focus group and corresponding hot spot region according to the position of each screening record in position model and each the focus group, and its details will be in the back explanation.
What deserves to be explained is, in certain embodiments, screening module 120 in the hot spot analytic system 100, the module of hiving off 130, analysis module 140, and the name module can be with the real work of software and hardware mode, and performed by a processing unit of electronic installation.In certain embodiments, screening module 120, the module of hiving off 130, analysis module 140, with the name module can be to distinguish independently electronic installation, and have signal communication to each other to carry out interaction.
Fig. 2 shows the analysis of central issue method according to the embodiment of the invention.Analysis of central issue method according to the embodiment of the invention goes for an electronic installation.As step S210, obtain present contextual information.What note is that in certain embodiments, contextual information is produced or received by an end device by electronic installation itself at present.At present contextual information can comprise temporal information, positional information, and Weather information etc.As step S220, according to the record in the present contextual information garbled data storehouse, to obtain screening record.Similarly, each record can comprise a contextual information at least, as temporal information, positional information, and Weather information etc.
Fig. 3 shows the focus screening technique according to the embodiment of the invention.As step S221, the present temporal information of foundation is by capturing a specific period in the time model.As previously mentioned, can write down the semantic structure of corresponding time in the time model, as the definition of the time point of multi-period and corresponding each period, timely intersegmental front and back and relation of inclusion.Each time point can correspond at least one period.For instance, the 08:20 of Monday can correspond to the period of the 08:00 to 09:00 of Monday; The period of the 08:00 to 09:00 of Monday can correspond to the spike period of all a whole mornings; The spike period of all a whole mornings can correspond to the spike period in morning day of duty; The spike period of all a whole mornings also can correspond to the period of all a whole mornings; The period of all a whole mornings can correspond to the period in morning day of duty; The period of all a whole mornings also can correspond to all periods of Monday; And all periods of Monday can correspond to all periods of day of duty.What must remind is, the semantic structure of time can be adjusted according to different demands, and this case is not limited thereto.As step S222, according to the record in the specific period garbled data storehouse that captures, to obtain screening record.Wherein, the contextual information of corresponding screening record is to fall among the specific period as temporal information.As step S223, the number of judging the screening record whether less than a prearranged number (as 300 or other suitable numeral).If the number of screening record is during less than prearranged number (step S223 not), process ends.If the number of screening record is during less than prearranged number (step S223 is), as step S224, according to the specific period by capturing another specific period in the time model.What note is, the purpose that captures another specific period is to relax the restriction of screening, in other words, and old segment length when specific of the time ratio contained of new specific period.For instance, be the 08:20 of Monday when the present time, and specific period that captures by time model for the first time when being period of 08:00 to 09:00 of Monday, the specific period that is captured by time model for the second time can be the spike period of all a whole mornings.After another specific period captured out, flow process was got back to step S222, according to the record in the specific period garbled data storehouse that captures, to obtain screening record.What note is that in certain embodiments, the more present Weather information that is write down in the present contextual information of foundation comes the record in the garbled data storehouse, to obtain screening record.Then,, utilize the algorithm that hives off, come to hive off, thereby obtain at least one focus group, and be hot spot region of each focus group generation correspondence for the screening record according to current position information and the position between each screening record as step S230.
As previously mentioned, each focus group can name respectively.Fig. 4 shows the focus group/hot spot region naming method according to the embodiment of the invention.As step S410,, find out included intersection in each focus group according to the contextual information of screening record in position module and the focus group.Similarly, the semantic structure that position model can recording geographical position, as multiple tracks road unit, as the definition of intersection, highway section, sight spot and/or terrestrial reference, and the annexation of road unit.Find out after the intersection,, find out the highway section that the intersection connects according to position module as step S420.As step S430, be recorded in the frequency of occurrences in each highway section according to the position calculation screening of screening record.As step S440, select the highest highway section of the frequency of occurrences of screening record, intersection, sight spot and/or terrestrial reference as the focus group and the title of hot spot region accordingly.
Refer again to Fig. 2,, calculate the temperature of each focus group as step S240.What note is, in this case, temperature can comprise whole temperature, relatively temperature, with real-time temperature.Fig. 5 shows the temperature computing method according to the embodiment of the invention.As step S241,, utilize following formula to calculate a whole temperature for each focus group respectively according to the number of screening record and the area size of each focus group in each focus group.
Wherein,
It is the whole temperature of the i of focus group; Num
iIt is the number of screening record among the i of focus group; Area
iIt is the hot spot region size of the i of focus group; T is the length of specific period; η
lBe an adjustment coefficient, it can be adjusted according to different application.
As step S242,, utilize following formula to calculate a relative temperature for each focus group respectively according to the whole temperature of each focus group and the distance of each a focus group and an end device (current position information).
Wherein, S
I, jBe the relative temperature of the i of focus group for portable terminal j; Dist
I, jBe the zone of the i of focus group and the distance between end device j.
As step S243,, utilize following formula to calculate a real-time temperature for each focus group respectively according to the number and the corresponding relative temperature of each focus group of end device in the zone of each focus group.
Wherein, S '
I, jBe the real-time temperature of the i of focus group for end device j; Dens
iIt is the number of the interior end device in zone of the i of focus group.Number that it should be noted that the interior end device in zone of each focus group can be learnt according to the position of each end device, and the position of each end device can be learnt by the present contextual information of indivedual transmission.
As previously mentioned, the incident of corresponding each focus group and participation number thereof can also be used for calculating the temperature of each focus group.In certain embodiments, incident can be to put for building by acquisition in the network or by the people in advance.In certain embodiments, incident is imported by end device, and is received by end device by communication network.Each incident can comprise the temporal information, location information of its generation, with the participation number etc.As step S244,, utilize following formula to adjust for the corresponding temperature in real time of each focus group according to the incident of corresponding each focus group.
Wherein, S "
I, jBe to adjust the real-time temperature of the after heat point i of group for end device j; Event
kIt is the participation number of incident k; ε
kThe error that is incident k is adjusted item; N is the number of incident; η
2Be an adjustment coefficient, it can be adjusted according to different application.
Incident that it should be noted that corresponding each focus group is meant that the temporal information of incident meets the specific period of screening record and the positional information of incident falls among the hot spot region of focus group.
What must remind is that the embodiment of Fig. 5 is that the real-time temperature of each focus group with respect to portable terminal calculated in explanation.Yet in certain embodiments, the corresponding whole temperature of each focus group, relative temperature all can be calculated respectively with real-time temperature, to carry out subsequent applications.
After each corresponding fever thermometer of focus group calculates, as step S250, according to the temperature of each focus group, as whole temperature, relatively temperature with/or real-time temperature and corresponding hot spot region thereof, produce at least one hot spot region information.In certain embodiments, can be according to the temperature of each focus group, as whole temperature, temperature be carried out rank with temperature in real time with focus group relatively, and the focus group of getting last set rank is as recommendation focus group.In certain embodiments, the title of hot spot region information and recommendation focus group can be sent to end device by communication network.What note is, in certain embodiments, when end device has an operation-interface or a display unit, the title and the position of hot spot region information and recommendation hot spot region information also can show in described operation-interface or display unit, and focus group can be shown with different colours according to different temperatures.
Therefore, can analyze the carrying focus by the hot spot analytic system and the method for this case, calculate the whole temperature of corresponding focus group, relatively temperature, with real-time temperature, think that taxi provides hot spot region information.
Method of the present invention, or specific kenel or its part can exist with the kenel of program code.Program code can be contained in tangible media, get (as embodied on computer readable) Storage Media as floppy disk, discs, hard disk or any other machine readable, also or be not limited to the computer program of external form, wherein, when program code by machine, when loading and carrying out as computing machine, this machine becomes in order to participate in device of the present invention.Program code also can pass through some transfer mediums, transmit as electric wire or cable, optical fiber or any transmission kenel, wherein, when program code by machine, when receiving, loading and carrying out as computing machine, this machine becomes in order to participate in device of the present invention.When the general service processing unit is done in fact, program code provides a class of operation to be similar to the unique apparatus of using particular logic circuit in conjunction with processing unit.
Though the present invention discloses as above with preferred embodiment; right its is not in order to limit the present invention; anyly be familiar with one of ordinary skill in the art; without departing from the spirit and scope of the present invention; when can doing a little change and retouching, so protection scope of the present invention defines and is as the criterion when looking the claim scope.
Claims (28)
1. hot spot analytic system, described system comprises:
One database stores many notes records, and wherein, each record comprises a contextual information at least, and described contextual information comprises a time information and a positional information at least;
One screening module in order to according to described these records in a present contextual information and the described database, is screened and is obtained many screening records, and wherein, described present contextual information comprises a present temporal information at least;
One module of hiving off in order to hive off according to the described positional information of described these screening records, obtains at least one focus group, and be the hot spot region that each described at least one focus group produces correspondence; And
One analysis module, in order to number and corresponding described hot spot region size according to these screening records described in each described at least one focus group, produce a whole temperature for each described at least one focus group respectively, and described whole temperature and corresponding described hot spot region thereof according to each described at least one focus group provide at least one hot spot region information.
2. hot spot analytic system as claimed in claim 1, described system more comprises:
One time model, in order to write down the semantic structure of corresponding time, wherein, described semantic structure includes the definition of the time point of a plurality of periods, corresponding each described these period, and described these the time intersegmental front and back and relation of inclusion; And wherein,
Described screening module more comprises in order to described present temporal information and described time model according to described present contextual information, capture the one first corresponding specific period, and the described first specific period of foundation is screened described these records in the described database, to obtain described these screening records.
3. hot spot analytic system as claimed in claim 2, it is characterized in that, described screening module more comprises in order to judge that whether the described number that these screen record is less than a prearranged number, and when the number of described these screening records during less than described prearranged number, the described semantic structure of foundation and the described first specific period captured for one second specific period, and the described second specific period of foundation is screened described these records in the described database, to obtain described these screening records, segment length when wherein, the time ratio contained of the described second specific period described first is specific.
4. hot spot analytic system as claimed in claim 1, it is characterized in that, described contextual information more includes a Weather information, and described present contextual information more includes a present Weather information, and described screening module more comprises in order to according to the described present Weather information in the described present contextual information, screens from described database and obtain described these screening records.
5. hot spot analytic system as claimed in claim 1 is characterized in that, described analysis module more comprises in order to carrying out rank according to the described whole temperature of each described at least one focus group, and provides at least one hot spot region information according to rank order.
6. hot spot analytic system as claimed in claim 1 is characterized in that, described system more comprises via a communication network and an end device and communicating, to receive from information that described end device is transmitted as described present contextual information; And, wherein
Described analysis module more comprises in order to via described communication network, described at least one hot spot region information is sent to described end device.
7. hot spot analytic system as claimed in claim 1, it is characterized in that, described present contextual information more comprises a current position information, and the described module of hiving off more comprises in order to according to position and distance between described current position information and each described these screening record, described these screening records is hived off.
8. hot spot analytic system as claimed in claim 7 is characterized in that, described system more includes a time module and a location module, in order to present temporal information and the current position information that produces described present contextual information.
9. hot spot analytic system as claimed in claim 7, it is characterized in that, described system more includes a mobile device, and described mobile device more includes a location module, and the positional information that can locate system communication and produce described mobile device via a communication network and is with the described current position information as described present contextual information.
10. hot spot analytic system as claimed in claim 7, it is characterized in that, described analysis module more comprises in order to according to the described whole temperature of each described at least one focus group and the distance of each described at least one focus group and described current position information, respectively each described at least one focus group is produced a relative temperature, and described relative temperature and corresponding described hot spot region thereof according to each described at least one focus group provide described at least one hot spot region information.
11. hot spot analytic system as claimed in claim 7, it is characterized in that, described system more includes a plurality of mobile devices, and each described these mobile device more includes a corresponding location module, can and produce the positional information of each described these mobile device via a communication network and a location system communication, and the positional information of the specific mobile device in described these mobile devices system is as the described current position information of described present contextual information;
Wherein, described analysis module more comprises in order to according to the described whole temperature of each described at least one focus group and the distance of each described at least one focus group and described current position information, respectively each described at least one focus group produced a relative temperature; And
Wherein, described analysis module more comprises in order to the number according to these mobile devices described in the described relative temperature of each described at least one focus group and the corresponding described hot spot region thereof, respectively each described at least one focus group is produced a real-time temperature, according to the described real-time temperature and the corresponding described hot spot region thereof of each described at least one focus group, provide described at least one hot spot region information again.
12. hot spot analytic system as claimed in claim 11, it is characterized in that, described contextual information more comprises the incident of having drawn together and participation number thereof, and described analysis module more comprises according to institute's event and participation number thereof in the described hot spot region of each described at least one focus group correspondence, adjusts the described real-time temperature of each described at least one focus group.
13. hot spot analytic system as claimed in claim 1 is characterized in that, described system more comprises:
One position model, in order to write down the semantic structure in corresponding geographic position, wherein said semantic structure comprises the definition of multiple tracks road unit, and the annexation of described these road units, and described these road units comprise wherein arbitrary such as intersection, highway section, sight spot and terrestrial reference; And
One name module is in order to according to described position model, for naming pairing described hot spot region in each described at least one focus group.
14. hot spot analytic system as claimed in claim 13, it is characterized in that, described name module more comprises in order to according at least one intersection in each pairing described hot spot region of described at least one focus group and the multichannel section that is connected thereof, calculate the frequency of occurrences that described these screenings are recorded in each described these highway section, and select the highest described highway section, intersection, sight spot or the terrestrial reference of the described frequency of occurrences of described these screening records, think that the described hot spot region of correspondence is named.
15. an analysis of central issue method is characterized in that, is applicable to an electronic installation, described method comprises the following steps:
One database is provided, stores many notes records, wherein, each record comprises a contextual information at least, and described contextual information comprises a time information and a positional information at least;
Obtain a present contextual information, wherein, described present contextual information comprises a present temporal information at least;
According to described these records in described present contextual information and the described database, screening obtains many screening records;
Described positional information according to described these screening records is hived off, and obtains at least one focus group, and be the hot spot region that each described at least one focus group produces correspondence;
According to the number and corresponding described hot spot region size of these screening records described in each described at least one focus group, produce a whole temperature for each described at least one focus group respectively; And
Described whole temperature and corresponding described hot spot region thereof according to each described at least one focus group provide at least one hot spot region information.
16. analysis of central issue method as claimed in claim 15 is characterized in that described method more comprises the following steps:
One time model is provided, and in order to write down the semantic structure of corresponding time, wherein, described semantic structure includes the definition of the time point of a plurality of periods, corresponding each described these period, and described these the time intersegmental front and back and relation of inclusion;
According to the described present temporal information and the described time model of described present contextual information, capture the one first corresponding specific period; And
The described first specific period of foundation is screened described these records in the described database, to obtain described these screening records.
17. analysis of central issue method as claimed in claim 16 is characterized in that described method more comprises the following steps:
Whether the number of judging described these screening records is less than a prearranged number;
When the number of described these screening records during, captured for one second specific period according to the described semantic structure and the described first specific period less than described prearranged number; And
The described second specific period of foundation is screened described these records in the described database, screens records to obtain described these,
Segment length when wherein, the time ratio contained of the described second specific period described first is specific.
18. analysis of central issue method as claimed in claim 17, it is characterized in that, described contextual information more includes a Weather information, and described present contextual information more includes a present Weather information, and described method comprises more that according to the described present Weather information in the described present contextual information screening obtains described these screening records from described database.
19. analysis of central issue method as claimed in claim 15 is characterized in that, described method more comprises according to the described whole temperature of each described at least one focus group carries out rank, and provides at least one hot spot region information according to rank order.
20. analysis of central issue method as claimed in claim 15, it is characterized in that, described method more comprises via a communication network and an end device and communicating, to receive from information that described end device is transmitted as described present contextual information: and, via described communication network, described at least one hot spot region information is sent to described end device.
21. analysis of central issue method as claimed in claim 15, it is characterized in that, described present contextual information more comprises a current position information, and described method more comprises according to position and distance between described current position information and each described these screening record, comes described these screening records are hived off.
22. analysis of central issue method as claimed in claim 21 is characterized in that, the present temporal information of described present contextual information and current position information system are produced by a time module and a location module of described electronic installation.
23. analysis of central issue method as claimed in claim 21, it is characterized in that, described method comprises that more a mobile device locatees system communication via a communication network with one by a location module, and the positional information that produces described mobile device is with the described current position information as described present contextual information.
24. analysis of central issue method as claimed in claim 21 is characterized in that described method more comprises the following steps:
According to the described whole temperature of each described at least one focus group and the distance of each described at least one focus group and described current position information, respectively each described at least one focus group is produced a relative temperature; And
Described relative temperature and corresponding described hot spot region thereof according to each described at least one focus group provide described at least one hot spot region information.
25. analysis of central issue method as claimed in claim 21 is characterized in that described method more comprises the following steps:
Receive the described present contextual information of the specific mobile device in a plurality of mobile devices, wherein, each described these mobile device includes a corresponding location module, can and produce the positional information of each described these mobile device via a communication network and a location system communication, and the positional information of described specific mobile device system is as the described current position information of described present contextual information;
According to the described whole temperature of each described at least one focus group and the distance of each described at least one focus group and described current position information, respectively each described at least one focus group is produced a relative temperature;
According to the number of these mobile devices described in the described relative temperature of each described at least one focus group and the corresponding described hot spot region thereof, respectively each described at least one focus group is produced a real-time temperature; And
Described real-time temperature and corresponding described hot spot region thereof according to each described at least one focus group produce described at least one recommendation hot spot region.
26. analysis of central issue method as claimed in claim 25, it is characterized in that, described contextual information more comprises the incident of having drawn together and participation number thereof, and method step more comprises an incident and the participation number thereof that is taken place according in the corresponding hot spot region of each focus group, adjusts the real-time temperature of each focus group.
27. analysis of central issue method as claimed in claim 15 is characterized in that, more comprises the following steps:
One position model is provided, in order to write down the semantic structure in corresponding geographic position, wherein said semantic structure comprises the definition of multiple tracks road unit, and the annexation of described these road units, and described these road units comprise wherein arbitrary such as intersection, highway section, sight spot and terrestrial reference; And
According to described position model, for naming pairing hot spot region in each focus group.
28. analysis of central issue method as claimed in claim 27 is characterized in that, more comprises the following steps:
According at least one intersection in each pairing hot spot region of focus group and the multichannel section that is connected thereof, calculate the frequency of occurrences that described these screenings are recorded in each described these highway section; And
Select the highest described highway section, intersection, sight spot or the terrestrial reference of the described frequency of occurrences of described these screening records, think that the described hot spot region of correspondence is named.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2009101390013A CN101887440B (en) | 2009-05-13 | 2009-05-13 | Hot spot analytic system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2009101390013A CN101887440B (en) | 2009-05-13 | 2009-05-13 | Hot spot analytic system and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101887440A true CN101887440A (en) | 2010-11-17 |
| CN101887440B CN101887440B (en) | 2012-05-30 |
Family
ID=43073366
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2009101390013A Expired - Fee Related CN101887440B (en) | 2009-05-13 | 2009-05-13 | Hot spot analytic system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101887440B (en) |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102388374A (en) * | 2011-09-28 | 2012-03-21 | 华为技术有限公司 | Method and device for data storage |
| CN103389093A (en) * | 2012-05-07 | 2013-11-13 | 腾讯科技（深圳）有限公司 | Travel route generation method and system |
| CN103530916A (en) * | 2012-07-05 | 2014-01-22 | 昆达电脑科技(昆山)有限公司 | Navigation device, traveling record system and method recording traveling information |
| CN103646020A (en) * | 2012-03-30 | 2014-03-19 | 三星电子株式会社 | Situation-aware recommendation using correlation |
| CN103902636A (en) * | 2012-12-30 | 2014-07-02 | 腾讯科技（深圳）有限公司 | Method and server for pushing information based on filtering and clustering method |
| CN103944932A (en) * | 2013-01-18 | 2014-07-23 | 阿里巴巴集团控股有限公司 | Method for searching and determining active zone, and server |
| CN104103271A (en) * | 2013-04-05 | 2014-10-15 | 国际商业机器公司 | Method and system for adapting speech recognition acoustic models |
| CN104102637A (en) * | 2013-04-02 | 2014-10-15 | 高德软件有限公司 | Method and device for generating hot spot region |
| CN104766467A (en) * | 2010-11-23 | 2015-07-08 | 互动网数位科技股份有限公司 | Taxi-calling system with pairing function and method thereof |
| CN105027177A (en) * | 2013-01-01 | 2015-11-04 | 通腾发展德国公司 | Vehicle management system |
| CN106448199A (en) * | 2016-09-21 | 2017-02-22 | 山东科技大学 | Traffic control method based on text mining |
| CN108009188A (en) * | 2017-08-16 | 2018-05-08 | 北京嘀嘀无限科技发展有限公司 | Thermodynamic chart methods of exhibiting, system, terminal and server |
| CN109542943A (en) * | 2018-11-28 | 2019-03-29 | 吉林建筑大学城建学院 | A kind of heat metering management service platform of central heating Internet of things system |
| CN109636441A (en) * | 2018-11-06 | 2019-04-16 | 北京奇虎科技有限公司 | Advertisement placement method and device |
| TWI666951B (en) * | 2016-09-30 | 2019-07-21 | 香港商阿里巴巴集團服務有限公司 | Method and device for determining hotspot area based on geographic location data |
| CN110636524A (en) * | 2019-09-23 | 2019-12-31 | 中国联合网络通信集团有限公司 | Personal hotspot naming method, mobile terminal and personal hotspot naming system |
| CN113112069A (en) * | 2021-04-13 | 2021-07-13 | 北京阿帕科蓝科技有限公司 | Population distribution prediction method, population distribution prediction system and electronic equipment |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI678675B (en) * | 2017-05-12 | 2019-12-01 | 宏碁股份有限公司 | Method, server, and computer program product for ride hotspot prediction |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI224743B (en) * | 2003-08-01 | 2004-12-01 | Leadtek Informations Co Ltd | System and method for automatically dispatching driving-vehicle |
| CN100476742C (en) * | 2007-02-09 | 2009-04-08 | 华中科技大学 | Load balancing method based on object storage device |
| CN101183393B (en) * | 2007-12-21 | 2010-06-23 | 腾讯科技（深圳）有限公司 | Information attention update method and device |
| CN100547625C (en) * | 2008-01-31 | 2009-10-07 | 浙江工业大学 | Method for analysis of prototype run route in a kind of urban transportation |
-
2009
- 2009-05-13 CN CN2009101390013A patent/CN101887440B/en not_active Expired - Fee Related
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104766467A (en) * | 2010-11-23 | 2015-07-08 | 互动网数位科技股份有限公司 | Taxi-calling system with pairing function and method thereof |
| CN102388374A (en) * | 2011-09-28 | 2012-03-21 | 华为技术有限公司 | Method and device for data storage |
| CN103646020A (en) * | 2012-03-30 | 2014-03-19 | 三星电子株式会社 | Situation-aware recommendation using correlation |
| CN103389093A (en) * | 2012-05-07 | 2013-11-13 | 腾讯科技（深圳）有限公司 | Travel route generation method and system |
| CN103389093B (en) * | 2012-05-07 | 2016-08-03 | 腾讯科技（深圳）有限公司 | Travel route generates method and system |
| CN103530916A (en) * | 2012-07-05 | 2014-01-22 | 昆达电脑科技(昆山)有限公司 | Navigation device, traveling record system and method recording traveling information |
| CN103902636A (en) * | 2012-12-30 | 2014-07-02 | 腾讯科技（深圳）有限公司 | Method and server for pushing information based on filtering and clustering method |
| CN103902636B (en) * | 2012-12-30 | 2018-04-27 | 腾讯科技（深圳）有限公司 | Method and server based on filter clusters method pushed information |
| CN105027177A (en) * | 2013-01-01 | 2015-11-04 | 通腾发展德国公司 | Vehicle management system |
| US10262535B2 (en) | 2013-01-01 | 2019-04-16 | Tomtom Telematics B.V. | Vehicle management system |
| CN103944932A (en) * | 2013-01-18 | 2014-07-23 | 阿里巴巴集团控股有限公司 | Method for searching and determining active zone, and server |
| CN103944932B (en) * | 2013-01-18 | 2017-07-14 | 阿里巴巴集团控股有限公司 | Search for, determine the method and server of active regions |
| CN104102637B (en) * | 2013-04-02 | 2017-09-29 | 高德软件有限公司 | A kind of method and device of generation hot spot region |
| CN104102637A (en) * | 2013-04-02 | 2014-10-15 | 高德软件有限公司 | Method and device for generating hot spot region |
| CN104103271A (en) * | 2013-04-05 | 2014-10-15 | 国际商业机器公司 | Method and system for adapting speech recognition acoustic models |
| CN104103271B (en) * | 2013-04-05 | 2017-05-10 | 国际商业机器公司 | Method and system for adapting speech recognition acoustic models |
| CN106448199A (en) * | 2016-09-21 | 2017-02-22 | 山东科技大学 | Traffic control method based on text mining |
| TWI666951B (en) * | 2016-09-30 | 2019-07-21 | 香港商阿里巴巴集團服務有限公司 | Method and device for determining hotspot area based on geographic location data |
| US10943364B2 (en) | 2016-09-30 | 2021-03-09 | Advanced New Technologies Co., Ltd. | Method and device for determining areas of interest based on geolocation data |
| US11087490B2 (en) | 2016-09-30 | 2021-08-10 | Advanced New Technologies Co., Ltd. | Method and device for determining areas of interest based on geolocation data |
| CN108009188A (en) * | 2017-08-16 | 2018-05-08 | 北京嘀嘀无限科技发展有限公司 | Thermodynamic chart methods of exhibiting, system, terminal and server |
| CN109636441A (en) * | 2018-11-06 | 2019-04-16 | 北京奇虎科技有限公司 | Advertisement placement method and device |
| CN109636441B (en) * | 2018-11-06 | 2023-12-19 | 三六零科技集团有限公司 | Advertisement putting method and device |
| CN109542943A (en) * | 2018-11-28 | 2019-03-29 | 吉林建筑大学城建学院 | A kind of heat metering management service platform of central heating Internet of things system |
| CN110636524A (en) * | 2019-09-23 | 2019-12-31 | 中国联合网络通信集团有限公司 | Personal hotspot naming method, mobile terminal and personal hotspot naming system |
| CN110636524B (en) * | 2019-09-23 | 2022-07-19 | 中国联合网络通信集团有限公司 | Personal hotspot naming method, mobile terminal and personal hotspot naming system |
| CN113112069A (en) * | 2021-04-13 | 2021-07-13 | 北京阿帕科蓝科技有限公司 | Population distribution prediction method, population distribution prediction system and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101887440B (en) | 2012-05-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101887440B (en) | Hot spot analytic system and method | |
| TWI393378B (en) | Hotspot analysis systems and methods, and computer program products thereof | |
| Zhu et al. | Understanding spatio-temporal heterogeneity of bike-sharing and scooter-sharing mobility | |
| Lathia et al. | Measuring the impact of opening the London shared bicycle scheme to casual users | |
| US9183497B2 (en) | Performance-efficient system for predicting user activities based on time-related features | |
| Bacon et al. | Using real-time road traffic data to evaluate congestion | |
| Wang et al. | A big data approach for smart transportation management on bus network | |
| CN104380293A (en) | Providing information about relevant elements from maps history based on location | |
| CN101243478A (en) | Method and system for using cellular data for transportation planning and engineering | |
| CN105894358A (en) | Commuting order identification method and device | |
| Szeto et al. | A time-dependent logit-based taxi customer-search model | |
| Almannaa et al. | Dynamic linear models to predict bike availability in a bike sharing system | |
| CN104077915A (en) | Riding trend prediction device and method | |
| CN103365848A (en) | Method, device and system for inquiring videos | |
| CN110400462B (en) | Track traffic passenger flow monitoring and early warning method and system based on fuzzy theory | |
| Lv et al. | Mobility pattern recognition based prediction for the subway station related bike-sharing trips | |
| Ma et al. | Public transportation big data mining and analysis | |
| CN104657457A (en) | Data processing method for video evaluation of users, video recommendation method and devices | |
| Tempelmeier et al. | Data4urbanmobility: Towards holistic data analytics for mobility applications in urban regions | |
| Samaras et al. | Requirements and architecture design principles for a smart city experiment with sensor and social networks integration | |
| CN116911568A (en) | Intelligent operation management method and system for public transportation | |
| Meenaloshini et al. | Smart car parking system in smart cities using IR | |
| CN110033613B (en) | Smart city management method and system based on regional traffic synchronism | |
| CN101366063B (en) | Apparatus and method for providing customized public transportation information in dmb terminal | |
| Petkovics et al. | Crowdsensing solutions in smart cities: Introducing a horizontal architecture |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20120530 Termination date: 20200513 |