CN104133818A - Automobile historical data analysis method and automobile historical data analysis system based on Internet of vehicles - Google Patents
Automobile historical data analysis method and automobile historical data analysis system based on Internet of vehicles Download PDFInfo
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Abstract
The invention discloses an automobile historical data analysis method and an automobile historical data analysis system based on Internet of vehicles. A data collecting module 101 uses the Internet of vehicles 01 for obtaining mass automobile historical data, and the automobile historical data is stored into a vehicle use and tracking information list in a classified way through a first layer data analysis module 102 and a vehicle use and tracking information analysis module 103; further, the grading early warning information of each factor of the vehicle use and tracking information list is analyzed and decided through a grading early warning analysis module 104 and a risk analysis module 105; different data factors are correlated by aiming at different target people groups for analyzing and determining risk prompt information; and the risk prompt information is displayed to the target people groups through a display module 106. The method and the system provided by the invention have the advantages that fine automobile data service and consulting service can be simultaneously provided for five kinds of the target people groups including individuals, used-car sellers, insurance companies, automobile manufacturers and 4S shops; the vehicle information completeness and the value evaluation precision are high; the system development cost is reduced; the development efficiency is improved; and the expandability is high.
Description
Technical field
The present invention relates to automobile industry data analysis field, in particular to a kind of automobile historical data analysis method and system based on car networking.
Background technology
Within 2012, China continues to hold a post or title for the 4th time first of the world with 1,930 ten thousand new car sales volume, can claim China to step into automotive society completely.Domestic automobile recoverable amount has reached 1.14 hundred million at present, coming 10 years, and expectation can rise to 300,000,000.Professional person points out, last year 4800000 of less thaies Second-hand Vehicle Transaction amount but just 1/4th of new car sales volume, not as good as 1/10th of U.S.'s used car same period, " Qian Jing " spacious wealthy large market that this fully shows Chinese used car is contained.Along with the quantity of China's private car is more and more; automobile becomes the major part of city dweller's family's property gradually; how better to protect one's own property and become the main task of each family; China will be maximum most potential car insurance market in the world; estimate 2013-2017; Automobile Insurance in China professional income average growth rate per annum is about 26.4%, 2016 annual income will reach 11,294 hundred million yuan.On the other hand, show according to the car networking market intelligence report book of up-to-date distribution, within 2013, global car networking market scale is estimated to reach 218.2 hundred million dollars, car networking has become the huge gold mine in one, Internet of Things field, from 2005 so far, Chinese car on-line customer number rises to 500,000 families from 50,000, and expects 2015, this numeral will be 1,000 ten thousand families, account for 10% of user vehicle sum at that time nearly.
But car networking is through development for many years, successfully car working application is very limited, and used car market, still in traditional trade mode, cannot form the commercial applications of extensive maturation.Want to realize the true value of car networking and application thereof, carry out the car data business based on telecommunications network and internet, just must be based upon a car and network in optimum network ecosystem, " vehicle data excavates and operation " is to provide the key foundation of all services.Along with the development in technology and epoch, " the large data of automobile " are not limited in massive structured data, and it also comprises non-structured data such as blog, clickstream data, machine and sensing data and social media etc.Finding data is no longer a difficult problem, how to analyze data and is only a maximum difficult problem, must change from the structural data analysis thinking of market survey the thinking of data mining into.The ultimate challenge that large data analysis faces is exactly the professional that famine is skilled in technique, and analysis tool of new generation and traditional B I and the needed skilled technical ability of data warehouse are not quite similar.According to the data of U.S.'s Dow Jones risk resource (Dow Jones VentureSource), in two years in the past, 11.7 hundred million dollars have flowed to 119 database software companies.Last year, SAP market value has exceeded Siemens, become the highest listed company of German market value, and such achievement part has benefited from the commercialization of its database software HANA.Also real formation not of the soil of the large data of China, the cultural label of " similar Mr. ", " probably neat " exists always, and the instrumental value of data mining is not admitted completely, and the development of hardware and software needs maturation.
Summary of the invention
Along with vehicle class and quantity constantly increase, and the new services relevant to vehicle and application continue to bring out, and simple data analysing method can not meet the demand of fierce automobile industry competition.Vehicle production manufacturer, dealer's (comprising used car dealer), insurance company, consumer have all proposed more requirements targetedly to vehicle data analysis.Day by day open in information Internet era, existing car data analytical approach all demonstrates weak point at kind, real-time, the information opening of Data Collection.For example, the data analysis pattern of 4 S auto shop is, the limited data recording capability possessing by automobile 4S shop itself is that the application of being correlated with is prepared, from these data, excavate some useful customer informations, useful customer information is analyzed, draw corresponding analysis rule, carry out simple data analysis.Meanwhile, be client according to the limited client historical data figure by car situation and vehicle maintenance maintenance status in the past and maintain prediction.But the information of vehicles of 4 S auto shop pattern is to be more the service of vehicle production producer and 4S shop, and for other parts of automobile industry, such as concerning crucial crowd---consumer, be opaque substantially, cannot obtain the valuable reference information of vehicle.On the other hand, domestic vehicle used car market environment is still immature, lacks the comprehensive and accurate tracking of information of vehicles and record and the relevant service such as transaction risk and feasibility analysis.The situation lagging behind in order to change current car data service and analytical approach, meet the become more meticulous demand of different customer groups to car data analysis, the invention provides a kind of automobile historical data analysis method and system based on car networking, at least to address the above problem.
According to an aspect of the present invention, provide a kind of automobile historical data analysis method based on car networking, having comprised: network and obtain automobile mass historical data by car; Described automobile mass historical data is carried out to ground floor data analysis, remove duplicate message, error message and garbage; Described data after ground floor data analysis are carried out to second layer data analysis, and classification storage at least one vehicle uses and trace information list; Described described vehicle after second layer data analysis is used with trace information list and carries out the 3rd layer data analysis, and vehicle uses and the grading forewarning system information of each key element of trace information list described in analysis decision; Described vehicle is used with trace information list and grading forewarning system information and carries out the 4th layer data analysis, for the associated different Data Elements of different target crowd, Analysis deterrmination indicating risk information; Utilize description intuitively and visual mode that described vehicle use and at least one item in trace information list, described grading forewarning system information, described indicating risk information are presented to described target group.
Preferably, described vehicle uses and the key element of trace information list comprises: 1) vehicle essential information, comprises at least one of following information: information is recorded, scraps in brand vehicle, outward appearance and color, Motor Number, the date of production, annual test; 2) vehicle Transaction Information, comprises at least one of following information: owner information, vehicular applications, vehicle mileage, Transaction Information; 3) vehicle maintenance information, comprises at least one of following information: conventional maintenance, call back message, maintenance record; 4) car accident information, comprises at least one of following information: insurance continuation, accident information, insurance history, illegal information.
Preferably, described in analysis decision, vehicle use comprises with the method for the grading forewarning system information of each key element of trace information list: described each key element is formulated to grading forewarning system rule, and wherein, early warning is divided into high, medium and low three ranks; According to the grading forewarning system information of each key element described in the decision-making of described grading forewarning system rule analysis.
Preferably, described for the associated different Data Elements of different target crowd, the method of Analysis deterrmination indicating risk information comprises: formulate at least one indicating risk item for described each target group, described indicating risk item comprises at least one indicating risk information; Formulate at least one correlation rule for described indicating risk item; Determine the described indicating risk information of described indicating risk item according to described Association Rule Analysis.
Preferably, described target group comprises at least one item of following target group: individual, second-hand car trader, insurance company, automobile production manufacturer, 4S shop.
Preferably, the described automobile historical data analysis method based on car networking also comprises, by car network Real-time Obtaining upgrade or newly-increased automobile historical data, carry out in real time described ground floor and second layer data analysis, and re-start described the 3rd layer and the 4th layer data analysis under the condition of setting, upgrade grading forewarning system information and indicating risk information; Wherein, described in re-start the setting of described the 3rd layer and the 4th layer data analysis condition be to exceed setting value apart from the last time of analyzing, or described vehicle uses with the renewal ratio of trace information list and is greater than setting value.
According to another aspect of the present invention, provide a kind of automobile historical data analysis system based on car networking, having comprised: 1) data acquisition module, obtains automobile mass data for networking by car; 2) ground floor data analysis module, for the described automobile mass historical data obtaining by described data acquisition module is carried out to ground floor data analysis, removes duplicate message, error message and garbage; 3) vehicle uses and trace information analysis module, for to carrying out second layer data analysis by the data after the analysis of described ground floor data analysis module, classifies and stores at least one vehicle use and trace information list; 4) grading forewarning system analysis module, for described vehicle is used with trace information list and carries out the 3rd layer data analysis, uses with each key element of trace information list and carries out grading forewarning system analysis described vehicle; 5) venture analysis module, be used for using with trace information list and carry out the 4th layer data analysis by the grading forewarning system information after the analysis of described grading forewarning system analysis module by the described vehicle after described vehicle use and the analysis of trace information analysis module, for the associated different Data Elements of different target crowd, analyze and export indicating risk information; 6) present module, for utilizing description intuitively and visual mode that at least one item of following information is presented to described target group: described vehicle uses and trace information list, described grading forewarning system information, described indicating risk information.
Preferably, described grading forewarning system analysis module comprises: 1) early warning rule unit, formulate grading forewarning system rule for described vehicle being used with each key element of trace information list, and wherein, early warning is divided into high, medium and low three ranks; 2) early warning decision unit, for according to the grading forewarning system information of each key element described in the grading forewarning system rule analysis decision-making of described early warning rule unit.
Preferably, described venture analysis module comprises: 1) indicating risk item unit, and for formulating at least one indicating risk item for described each target group, described indicating risk item comprises at least one indicating risk information; 2) risk association rule unit, for formulating at least one correlation rule for the described indicating risk item of described indicating risk item unit; 3) indicating risk determining unit, for determining the described indicating risk information of the described indicating risk item of described indicating risk item unit according to the described correlation rule of described risk association rule unit.
Preferably, described automobile historical data analysis system also comprises: 1) described data acquisition module, also or newly-increased automobile historical data that upgrade for the Real-time Obtaining of networking by car; 2) described ground floor data analysis module, also carry out in real time described ground floor data analysis for the automobile historical data described renewal or newly-increased that described data acquisition module is obtained, remove duplicate message, error message and garbage in automobile historical data described renewal or newly-increased; 3) described vehicle uses and trace information analysis module, also, for to carrying out second layer data analysis by the automobile historical data described renewal or newly-increased after the analysis of described ground floor data analysis module, upgrades vehicle and uses and trace information list; 4) described grading forewarning system analysis module, also, for again the vehicle after described renewal being used with each key element of trace information list and carries out grading forewarning system analysis under the condition setting, upgrades grading forewarning system information; Wherein, the condition of described setting is to exceed setting value apart from the last time of analyzing, or described vehicle uses and the renewal ratio of trace information list is greater than setting value; 5) described venture analysis module, also carries out the 4th layer data analysis for the grading forewarning system information after vehicle use and trace information list and described renewal to after described renewal, upgrades indicating risk information.
By the present invention, can be simultaneously for individual, second-hand car trader, insurance company, automobile production manufacturer and 4S shop five class customer groups provide respectively become more meticulous car data business and consulting service targetedly, information of vehicles integrality and value assessment degree of accuracy are high, reduce system development costs, avoid the overlapping development for different customer groups' part of module, improve development efficiency, extensibility is strong, and can form new car data subservice and new service mode, have broad application prospects and good economic return.
brief description of the drawings
Accompanying drawing described herein is used to provide a further understanding of the present invention, forms the application's a part, and schematic description and description of the present invention is used for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is the schematic diagram that the present invention is based on the automobile historical data analysis system of car networking;
Fig. 2 is that in the embodiment of the present invention 1, vehicle uses and the relevance explanation of four category informations of trace information list;
Fig. 3 is the schematic diagram of grading forewarning system analysis module 104 in the embodiment of the present invention 1;
Fig. 4 is the schematic diagram of the embodiment of the present invention 1 risk analysis module 105;
Fig. 5 is according to the schematic diagram of the automobile historical data analysis method based on car networking of the embodiment of the present invention 2;
Embodiment
Hereinafter describe the present invention in detail with reference to accompanying drawing and in conjunction with two embodiment.It should be noted that, in the situation that not conflicting, the feature in embodiment and embodiment in the application can combine mutually.
According to the embodiment of the present invention 1, provide a kind of automobile historical data analysis system based on car networking, as shown in Figure 1.In embodiments of the present invention, this system utilizes car networking 01 to obtain magnanimity car data by data acquisition module 101, is used with trace information analysis module 103 classification of automobile historical data is stored as to vehicle use and trace information list by ground floor data analysis module 102 and vehicle; Further, use and the grading forewarning system information of each key element of trace information list by grading forewarning system analysis module 104 and venture analysis module 105 analysis decision vehicles, and for the associated different Data Elements Analysis deterrmination indicating risk information of different target crowd, and present to target group by presenting module 106.Concrete steps are as follows:
1) data acquisition module 101 utilizes car networking 01 to obtain magnanimity car data.Wherein, the magnanimity car data obtaining can be from the home server/database 04 of automobile itself, department of remote server/database 03 enterprises and institutions relevant with automobile (as individual and the enterprise customer etc. of vehicle production producer, 0vehicle marketing enterprise, insurance company, vehicle management department and vehicle), and the communication mode obtaining comprises telecommunications network (wired, wireless), internet and mobile Internet etc.
2) ground floor data analysis module 102 carries out ground floor data analysis to the automobile mass historical data obtaining, and removes duplicate message, error message and garbage.
3) vehicle uses with trace information analysis module 103 data after the analysis of ground floor data analysis module is carried out to second layer data analysis, and classification storage at least one vehicle uses and trace information list.It has that the quality of data is high, operational efficiency is high and the three large features such as extendability is strong.The data that gather are after the careful screening of category, arrange and storage at least one vehicle use and trace information list, information list comprises vehicle essential information, vehicle Transaction Information, vehicle maintenance information and four types of car accident information, and each large type can be divided into several data attributes, degree of association degree when can effectively telling like this data analysis and using, and improve the speed in the time that data are extracted and apply.This analysis module can provide comprehensive vehicle data, break away from that the data that exist in current system are single, a little less than the degree of association, the problem that data mining potentiality are low, can realize vehicle from dispatching from the factory, sell, maintain, transaction, accident, the complete data recording such as scrap, thereby reach real-time follow-up, inquiry and feedback to vehicle-state, all information provides reference, mechanical condition, transaction value etc. that reasonable assessment vehicle is current can to manufacturer, vehicle administration office, insurance company, used car trade both sides etc.Vehicle uses with four category informations of trace information list as follows, and the relevance of four category informations as shown in Figure 2.
---vehicle essential information
Whether consistent with the information of dispatching from the factory various information when the detailed registration of vehicle of system dispatches from the factory, check relevant information for user.Main essential information comprises vehicle brand, model, date of manufacture, vehicle appearance information, annual test record and most important engine number (Vehicle Identical Number) and scraps record etc.
---vehicle Transaction Information
The related data information of registration of vehicle in the time of all previous transaction, thus realize reviewing and checking vehicle transaction and circulation history.Major transaction information comprises: successive owner information, use mileage and service time, vehicle registration and territory of use, all previous vehicle exchange hour etc.
---vehicle maintenance information
Whether registration of vehicle maintains the emm message in shop brand 4S shop and third party, reflection vehicle be correlated with maintenance work and vehicle pair on time.Main emm message comprises: record, general maintenance record etc. are recalled by conventional emm message and maintenance content, vehicle official.
---car accident information
The continuity of registration of vehicle purchase insurance and accident record and the maintenance being caused by accident, other lose damage recorded informations to also have vehicle, reflect the degree of impairment of vehicle in all previous accident, and follow-up reparation situation.Main insurance information comprises: insurance purchase information, accident record and maintenance record, also have vehicle to lose and other damage record.
4) grading forewarning system analysis module 104(Fig. 3) vehicle is used with trace information list and carries out the 3rd layer data analysis, vehicle is used with each key element of trace information list and carries out grading forewarning system analysis.Wherein: early warning rule unit 1041 uses with each key element of trace information list and formulates grading forewarning system rule described vehicle, and early warning is divided into high, medium and low three ranks; Early warning decision unit is according to the grading forewarning system information of each key element described in the grading forewarning system rule analysis decision-making of described early warning rule unit.For example, the early warning rule of car accident key element is the damaged condition to vehicle according to accident, as the early warning of structural damage is decided to be high-level, whether early warning decision unit belongs to structural damage according to this rule analysis car accident, if so, the grading forewarning system information of the current car accident key element of decision-making is high-level.
5) venture analysis module 105(Fig. 4) vehicle is used with trace information list and grading forewarning system information and carries out the 4th layer data analysis, for the associated different Data Elements of different target crowd, analyze and export indicating risk information.Wherein, at least one indicating risk item formulated for each target group in indicating risk item unit 1051, and indicating risk item comprises at least one indicating risk information; At least one correlation rule is formulated for each indicating risk item in risk association rule unit 1052; Indicating risk determining unit 1053 is determined indicating risk information according to correlation rule.Venture analysis module is used with trace information analysis module 103 and grading forewarning system analysis module 104 and is prepared vehicle essential information, Transaction Information, emm message and accident information to carry out data statistics and analysis as data by vehicle, explores and study the potential rules such as vehicle brand value, vehicle transaction value, vehicle trouble and problem, car accident and vehicle safety from the data of magnanimity.For different target groups, utilize the analytical approachs such as Data classification, estimating and forecasting and association, seek with it closely bound up data rule, export one or more indicating risk information for each indicating risk item.Wherein, target group can be individual, second-hand car trader, insurance company, automobile production manufacturer and 4S shop etc.
For example, there are two traffic hazards in a certain the automobile that consumer pays close attention to, venture analysis module 105 has been formulated two indicating risk items " possibility having an accident future " and " on the impact in vehicle life-span " and corresponding correlation rule for this consumer demand.Indicating risk determining unit 1053 can be found the advanced warning grade of two accidents of vehicle according to the vehicle use of this car and the car accident element information in trace information list, and time of origin, place, the information such as vehicle damage information, use relevant repair message and the corresponding advanced warning grade that can find two accidents to the maintenance key element in trace information list by associated vehicle, can also find other associated information and advanced warning grade, by the various features of two accidents of association analysis, two indicating risk items " possibility having an accident future " and " on the impact in vehicle life-span " are carried out to estimating and forecasting, output indicating risk information.
6) present module, for utilizing description intuitively and visual mode that vehicle is used with trace information list, grading forewarning system information, indicating risk information and presents to target customers according to customer demand.
Preferably, the automobile historical data analysis system of the present embodiment 1 is further comprising the steps of:
1) data acquisition module 101 by car network Real-time Obtaining upgrade or newly-increased automobile historical data;
2) ground floor data analysis module 102 to upgrade or newly-increased automobile historical data carry out in real time ground floor data analysis, remove duplicate message, error message and garbage in automobile historical data described renewal or newly-increased;
3) vehicle uses with trace information analysis module 103 that upgrade or newly-increased automobile historical data is carried out to second layer data analysis, upgrades vehicle and uses and trace information list;
4) grading forewarning system analysis module 104 again uses with each key element of trace information list and carries out grading forewarning system analysis the vehicle after upgrading under the condition of setting, and upgrades grading forewarning system information; Wherein, the condition of setting is to exceed setting value apart from the last time of analyzing, or vehicle uses and the renewal ratio of trace information list is greater than setting value;
5) venture analysis module 105 is used the grading forewarning system information with trace information list and after upgrading to carry out the 4th layer data analysis to the vehicle after upgrading, and upgrades indicating risk information.
According to the embodiment of the present invention 2, a kind of automobile historical data analysis method based on car networking is provided, process flow diagram is as shown in Figure 5.In embodiments of the present invention, the magnanimity car data that utilizes car to network to obtain is first by ground floor data analysis and second layer data analysis process, and analyzing stored is that many vehicles use and trace information list; Further, by the 3rd layer data analysis and the 4th layer data analytic process, the grading forewarning system information of each key element of the use of analysis decision vehicle and trace information list, and for the associated different Data Elements Analysis deterrmination indicating risk information of different target crowd.In the time having target group to inquire about because of particular demands, provide corresponding analysis result according to this particular demands.Concrete steps are as follows:
1) utilize car networking 01 to obtain magnanimity automobile historical data.
2) the automobile mass historical data obtaining is carried out to ground floor data analysis, remove duplicate message, error message and garbage.
3) data after the analysis of ground floor data analysis module are carried out to second layer data analysis, classification storage at least one vehicle uses and trace information list, information list comprises vehicle essential information, vehicle Transaction Information, vehicle maintenance information and four types of car accident information, and each large type can be divided into again several data attributes.
4) vehicle is used with trace information list and carries out the 3rd layer data analysis, vehicle is used with each key element of trace information list and carries out grading forewarning system analysis.Wherein, vehicle uses with each key element of trace information list and has formulated grading forewarning system rule (early warning is divided into high, medium and low three ranks), according to the grading forewarning system information of the each key element of grading forewarning system rule analysis decision-making.
5) vehicle is used with trace information list and grading forewarning system information and carries out the 4th layer data analysis, for the associated different Data Elements of different target crowd, analyze and export indicating risk information.Wherein, formulate at least one indicating risk item for each target group, indicating risk item comprises at least one indicating risk information, and formulates at least one correlation rule for each indicating risk item, determines one or more indicating risk information according to correlation rule.
6) in the time having target group to inquire about because of particular demands, provide corresponding analysis result according to this particular demands.In the present embodiment, target group is second-hand car trader, is considering whether to purchase a used car, wishes to obtain grading forewarning system information and the indicating risk information of this used car.When he has checked after these information, find that this chassis has once by the inferior grade early warning information of water logging and slight indicating risk information, and then the further historical information such as the relevant maintenance of inquiry, thereby whether final decision purchases the price of this used car and purchase.
The method and system that the present invention proposes can be simultaneously for individual, second-hand car trader, insurance company, automobile production manufacturer and 4S shop five class target groups provide become more meticulous car data business and consulting service, information of vehicles integrality and value assessment degree of accuracy are high, reduce system development costs, improve development efficiency, extensibility is strong, and can form new business model, have broad application prospects and good economic return.
Obviously, those skilled in the art should be understood that, above-mentioned of the present invention each module or each step can realize with general calculation element, they can concentrate on single calculation element, or be distributed on the network that multiple calculation elements form, alternatively, they can be realized with the executable program code of calculation element, thereby, they can be stored in memory storage and be carried out by calculation element, and in some cases, can carry out shown or described step with the order being different from herein, or they are made into respectively to each integrated circuit modules, or the multiple modules in them or step are made into single integrated circuit module to be realized.Like this, the present invention is not restricted to any specific hardware and software combination.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.
Claims (10)
1. the automobile historical data analysis method based on car networking, is characterized in that, comprising:
Network and obtain automobile mass historical data by car;
Described automobile mass historical data is carried out to ground floor data analysis, remove duplicate message, error message and garbage;
Described data after ground floor data analysis are carried out to second layer data analysis, and classification storage at least one vehicle uses and trace information list;
Described described vehicle after second layer data analysis is used with trace information list and carries out the 3rd layer data analysis, and vehicle uses and the grading forewarning system information of each key element of trace information list described in analysis decision;
Described vehicle is used with trace information list and grading forewarning system information and carries out the 4th layer data analysis, for the associated different Data Elements of different target crowd, Analysis deterrmination indicating risk information;
Utilize description intuitively and visual mode that at least one item of following information is presented to described target group: described vehicle uses and trace information list, described grading forewarning system information, described indicating risk information.
2. method according to claim 1, is characterized in that, described vehicle uses and the key element of trace information list comprises:
Vehicle essential information, comprises at least one of following information: brand vehicle, outward appearance and color, Motor Number, the date of production, annual test record, scrap information;
Vehicle Transaction Information, comprises at least one of following information: owner information, vehicular applications, vehicle mileage, Transaction Information;
Vehicle maintenance information, comprises at least one of following information: conventional maintenance, call back message, maintenance record;
Car accident information, comprises at least one of following information: insurance continuation, accident information, insurance history, illegal information.
3. method according to claim 1, is characterized in that, vehicle uses with the method for the grading forewarning system information of each key element of trace information list and comprises described in analysis decision:
Described each key element is formulated to grading forewarning system rule, and wherein, early warning is divided into high, medium and low three ranks;
According to the grading forewarning system information of each key element described in the decision-making of described grading forewarning system rule analysis.
4. method according to claim 1, is characterized in that, described for the associated different Data Elements of different target crowd, the method for Analysis deterrmination indicating risk information comprises:
Formulate at least one indicating risk item for described each target group, described indicating risk item comprises at least one indicating risk information;
Formulate at least one correlation rule for described indicating risk item;
Determine the described indicating risk information of described indicating risk item according to described Association Rule Analysis.
5. method according to claim 1, is characterized in that, described target group comprises at least one of following target group:
Individual, second-hand car trader, insurance company, automobile production manufacturer, 4S shop.
6. method according to claim 1, is characterized in that, described automobile historical data analysis method also comprises:
By car network Real-time Obtaining upgrade or newly-increased automobile historical data, carry out in real time described ground floor and second layer data analysis, and re-start described the 3rd layer and the 4th layer data analysis under the condition of setting, upgrade grading forewarning system information and indicating risk information; Wherein, described in re-start the setting of described the 3rd layer and the 4th layer data analysis condition be to exceed setting value apart from the last time of analyzing, or described vehicle uses with the renewal ratio of trace information list and is greater than setting value.
7. the automobile historical data analysis system based on car networking, is characterized in that, comprising:
Data acquisition module, obtains automobile mass data for networking by car;
Ground floor data analysis module, for the described automobile mass historical data obtaining by described data acquisition module is carried out to ground floor data analysis, removes duplicate message, error message and garbage;
Vehicle uses and trace information analysis module, for to carrying out second layer data analysis by the data after the analysis of described ground floor data analysis module, classifies and stores at least one vehicle use and trace information list;
Grading forewarning system analysis module, for described vehicle is used with trace information list and carries out the 3rd layer data analysis, uses with each key element of trace information list and carries out grading forewarning system analysis described vehicle;
Venture analysis module, be used for using with trace information list and carry out the 4th layer data analysis by the grading forewarning system information after the analysis of described grading forewarning system analysis module by the described vehicle after described vehicle use and the analysis of trace information analysis module, for the associated different Data Elements of different target crowd, analyze and export indicating risk information;
Present module, for utilizing description intuitively and visual mode that at least one item of following information is presented to described target group: described vehicle uses and trace information list, described grading forewarning system information, described indicating risk information.
8. method according to claim 7, is characterized in that, described grading forewarning system analysis module comprises:
Early warning rule unit, formulates grading forewarning system rule for described vehicle being used with each key element of trace information list, and wherein, early warning is divided into high, medium and low three ranks;
Early warning decision unit, for according to the grading forewarning system information of each key element described in the grading forewarning system rule analysis decision-making of described early warning rule unit.
9. method according to claim 7, is characterized in that, described venture analysis module comprises:
Indicating risk item unit, for formulating at least one indicating risk item for described each target group, described indicating risk item comprises at least one indicating risk information;
Risk association rule unit, for formulating at least one correlation rule for the described indicating risk item of described indicating risk item unit;
Indicating risk determining unit, for determining the described indicating risk information of the described indicating risk item of described indicating risk item unit according to the described correlation rule of described risk association rule unit.
10. method according to claim 7, is characterized in that, described automobile historical data analysis system also comprises:
Described data acquisition module, also or newly-increased automobile historical data that upgrade for the Real-time Obtaining of networking by car;
Described ground floor data analysis module, also carry out in real time described ground floor data analysis for the automobile historical data described renewal or newly-increased that described data acquisition module is obtained, remove duplicate message, error message and garbage in automobile historical data described renewal or newly-increased;
Described vehicle uses and trace information analysis module, also, for to carrying out second layer data analysis by the automobile historical data described renewal or newly-increased after the analysis of described ground floor data analysis module, upgrades vehicle and uses and trace information list;
Described grading forewarning system analysis module, also, for again the vehicle after described renewal being used with each key element of trace information list and carries out grading forewarning system analysis under the condition setting, upgrades grading forewarning system information; Wherein, the condition of described setting is to exceed setting value apart from the last time of analyzing, or described vehicle uses and the renewal ratio of trace information list is greater than setting value;
Described venture analysis module, also carries out the 4th layer data analysis for the grading forewarning system information after vehicle use and trace information list and described renewal to after described renewal, upgrades indicating risk information.
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