CN105975792A - Big-data-based dermatoglyph analysis and processing device and method - Google Patents
Big-data-based dermatoglyph analysis and processing device and method Download PDFInfo
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Abstract
The invention discloses a big-data-based dermatoglyph analysis and processing device and method. The device comprises a control module and a database module. The method comprises the steps that dermatoglyph information data, psychological behavior data and behavior characteristic data are collected, and modeling is performed according to the collected data to obtain a statistical analysis model; data analysis is performed according to the statistical analysis model, and a self-adaptation model is obtained according to the analysis result; corresponding data obtained by collection of the statistical analysis model on the basis of the self-adaptation model is processed; the method further comprises the steps that iterative analysis is performed on the collected data, and the statistical analysis model and the self-adaptation model are optimized. By adopting a big data method on the basis of computer software and the internet technology, a large amount of data of testee can be easily processed. By adopting the big data method, execution is efficient, one round analysis can be completed within a short period of time, and no noise factor is introduced. The models can be constantly evolved through unique data accumulation and iterative optimization.
Description
Technical field
The present invention relates to computer realm, particularly to fingerprint analysing processing meanss based on big data, method.
Background technology
Dermatoglyph psychology refers to a comprehensive branch of learning based on dermatoglyphics, psychology, cranial nerve science, hereditism and behavioristics.Its achievement is also an important tool of auxiliary psychological study.And after the development that experienced by for many years and sector application, dermatoglyph psychology be widely used in children education, psychological counselling, enter a higher school choose a job, occupational planning, the various fields such as personnel training.
The psychologic research method of dermatoglyph is exactly the method for the statistical classification that tradition psychological study is applied.It is exactly generally with tens to up to a hundred subjectss as sample populations, the psychology of the subjects that the characteristic according to dermatoglyph and experiment are paid close attention to and Behavioral feature carry out correlation research, thus it is consistent for providing the performance in certain psychology with Behavioral feature of the subjects with which skin grain character.The evaluation of psychology and Behavioral feature then realizes typically by subjective testing topic.So, it is the formation of the psychologic kernel model of dermatoglyph by accumulation progressively, i.e. includes dermatoglyph information and psychology, the association relation model of Behavioral feature.There is such kernel model, it is possible to instruct psychological study personnel or psychologist to understand the psychological and behavioral characteristics of target subjects in all directions.
But the shortcoming that current model exists following several respects:
The sample size of the most tested colony is the least: in the social environment of nowadays numerous and complicated, and the rule that tens the most hundreds of subjects colonies are presented cannot reliably expand to more to be had in the target group of using value and meaning.The result that hundreds of thousands, the tested colony of the highest millions of order of magnitude are presented is the most statistically significant.
The change of the most tested colony causes the problem implied: in the various achievements in research delivered at present, test each time is all using small group together with space clustering of time as tested, the student of such as one several class of school, some old men of one nursing house, some athletes of a physical culture training forces etc..And the goal in research tested each time is different.So, if the result of all researchs is combined into a systematized model, from the strict sense from the point of view of necessarily there is certain deviation.The root of this deviation is that each single achievement in research is to produce with under the space-time environment isolated independently of one another.
3. the efficiency of research is the lowest.Some traditional research method can follow the tracks of the situation that a tested colony collects the some months even time of several years the development and change of its psychology and behavior.Process and the result, such as subjects that can there is the experiment of many uncertain such environmental effects during this is very long reduce, the noise factor etc. that different growth environments is brought.So may result in the research of several years to put into and have no effect, or credible result degree is inadequate.
And big data are for solving the problem of psychological field, there is some Special Significance following:
First, refer to that tested Population is the hugest, be usually with million magnitude startings；
Second, it is that the quantity of information collected is the hugest, generally many than the quantity of tested colony magnitudes；
3rd, it is simply that the source of the various data for analyzing is various, the hereditary information of such as subjects, subjective evaluation and test data, social network data, consuming behavior data etc..
Summary of the invention
The technical problem to be solved in the present invention is, by big data analysis, process, and the psychologic device of dermatoglyph, method, it is possible to the sample size solving tested colony is less, the change of tested colony and the low problem for the treatment of effeciency.
Solve above-mentioned technical problem, the invention provides a kind of fingerprint analysing processing means based on big data, including: control module and DBM,
Described control module, in order to gather dermatoglyph information data, Psychology and behavior data and behavior characteristics data, and is modeled according to the data collected, obtains unified Analysis model；Described control module also in order to, carry out data analysis according to unified Analysis model, analysis result obtains adaptive model；Described DBM, in order to deposit and to synchronize dermatoglyph information data, Psychology and behavior data, behavior characteristics data；The data left in DBM, when setting up model, are called by described control module, set up unified Analysis model further according to the data called, and are analyzed unified Analysis model, obtain adaptive model；Also include model evaluation module, gather the parameter of data in order to assess the analysis result in unified Analysis model and adaptive model adjusting in DBM according to demand, and the structure of unified Analysis model and parameter in control module.
Further, described control module includes: dermatoglyph data acquisition module, in order to gather the dermatoglyph information of subjects and to be uploaded to background server by the webserver；Test and appraisal and tested profile module, in order to gather the Psychology and behavior data of subjects by the way of test and appraisal under online and/or line；External data collection module, in order to obtain behavior characteristics data to the internet access behavior of subjects.
Further, described DBM includes:
Dermatoglyph data base, in order to organize and to store the dermatoglyph information data collected；
Test and appraisal and tested profile module data base, in order to organize and to store the Psychology and behavior data of subjects；
External data base, in order to organize and to store the behavior characteristics data of subjects.
Further, APU also includes data integration and cleaning module, in order to the dermatoglyph information data that will collect in control module and behavior characteristics data, according to unified Analysis model be framework carry out organizing and being stored in data base time, carry out data integration, cleaning, and the constraints of data in the above-mentioned control module of labelling in unified Analysis model.
Further, APU also includes data analysis module, in order to perform multi-dimensional data analysis according to the data acquisition system in unified Analysis model as object, obtain the concrete classification of each dimensional concept, and the incidence relation between different dimensions and causal rule.
Further, described control module also includes, optimizes acquisition module, in order to revise the granularity in gatherer process, and adjusts collection target.
Further, described unified Analysis model and adaptive model also in order to be iterated analyzing to collection data, are optimized by described model evaluation module；Optimization process includes, adjusts the parameter in above-mentioned model, and adjusts above-mentioned model concept, mutual relation.
The invention allows for the unified Analysis model that fingerprint analysing based on big data processes, described unified Analysis model includes: meta-model layer, integrated model layer and analysis model layer,
In described meta-model layer, the basic metadata of definition unified Analysis model；
In described integrated model layer, according to dermatoglyph information data and Psychology and behavior data, according to subjects using time and space as index, carry out the complete portrait data of subjects；
In analyzing model layer, according to the complete portrait data in the basic metadata in described meta-model layer and integrated model layer, obtain analyzing model set.
Present invention also offers a kind of fingerprint analysing processing method based on big data, including:
Gather dermatoglyph information data, Psychology and behavior data and behavior characteristics data, and be modeled according to the data collected, obtain unified Analysis model；
Carry out data analysis according to unified Analysis model, obtain adaptive model according to analysis result；
By described adaptive model, the corresponding data collected in described unified Analysis model is processed；
Also include, be iterated described collection data analyzing, described unified Analysis model and adaptive model are optimized.
Further, described adaptive model is set up as follows:
Subjects's multi-dimensional data is obtained according to described unified Analysis model；
According to the behavior characteristics in multi-dimensional data, carry out the self adaptation change of analysis conclusion, validity and the dependency of subjects；
Adaptive model is set up based on different targets or application scenarios in above-mentioned processing procedure.
Beneficial effects of the present invention:
1) due to dermatoglyph psychological analysis processing meanss based on big data in the present invention, including: control module and DBM, wherein said control module, in order to gather dermatoglyph information data, Psychology and behavior data and behavior characteristics data, and be modeled according to the data collected, obtain unified Analysis model；By using based on computer software and the big data method of Internet technology, can easily process the data of ten million magnitude subjects.
2) due to described control module also in order to, carry out data analysis according to unified Analysis model, analysis result obtains adaptive model.Described control module whether subjective evaluation and test or external data, be all the process of a persistence, and the most limited by regions, therefore from macroscopically, and time and spatially can form a normality.The analysis result so drawn is the most more meaningful.
3) due to described DBM, in order to deposit and to synchronize dermatoglyph information data, Psychology and behavior data, behavior characteristics data；The data left in DBM, when setting up model, are called by described control module, set up unified Analysis model further according to the data called, and are analyzed unified Analysis model, obtain adaptive model；Also include model evaluation module, gather the parameter of data in order to assess the analysis result in unified Analysis model and adaptive model adjusting in DBM according to demand, and the structure of unified Analysis model and parameter in control module.The method of big data performs efficiently.Even if data volume is the hugest, it is also possible to complete one within a very short time and take turns analysis, so noise factor will not be introduced.And the ability of unique data accumulation and iteration optimization makes model constantly to evolve.
4) owing to dermatoglyph psychological analysis processing methods based on big data in the present invention are by using based on computer software and the big data method of Internet technology, the data of ten million magnitude subjects can easily be processed.
5) owing to described collection data to be iterated analysis, described unified Analysis model and adaptive model are optimized.The method using big data performs efficiently, even if data volume is the hugest, it is also possible to complete one within a very short time and take turns analysis, so noise factor will not be introduced.And the ability of unique data accumulation and iteration optimization makes model constantly to evolve.
6) include due to described unified Analysis model: meta-model layer, integrated model layer and analysis model layer, in the data collected because source is complicated, when it cannot be managed uniformly and be analyzed, need to build a unified Data Analysis Model, simultaneously along with data source and the variation of data form, the extended capability of model is also required to be protected.
Accompanying drawing explanation
Fig. 1 is the fingerprint analysing processing means structural representations based on big data in one embodiment of the invention.
Fig. 2 is the control module internal structure schematic diagram in Fig. 1.
Fig. 3 is the DBM internal structure schematic diagram in Fig. 1.
Fig. 4 is the fingerprint analysing processing means structural representations based on big data in one embodiment of the present invention.
Fig. 5 is the fingerprint analysing processing means structural representations based on big data in another preferred embodiment of the present invention.
Fig. 6 is the unified Analysis model structure schematic diagram that in one embodiment of the invention, fingerprint analysings based on big data process.
Fig. 7 is fingerprint analysing process flow schematic diagrams based on big data in one embodiment of the invention.
Detailed description of the invention
For making the object, technical solutions and advantages of the present invention clearer, below in conjunction with specific embodiment, and referring to the drawings, the present invention is described in more detail.
Fig. 1 is the fingerprint analysing processing means structural representations based on big data in one embodiment of the invention.
Fingerprint analysing processing means structures based on big data in the present embodiment include following content, in the present embodiment, fingerprint analysing processing meanss based on big data, including: control module 101 and DBM 100,
Described control module 101, in order to gather dermatoglyph information data, Psychology and behavior data and behavior characteristics data, and is modeled according to the data collected, obtains unified Analysis model；The function of described control module 101 is provide the collection of big data and analyze the foundation of model, first the basic skills realizing big data is exactly from the extensive gather data of multiple channel, then it is incorporated under a unified system or model, data are operated by the instrument recycling various statistics and data mining, if thus find in it dry model and rule.The described dermatoglyph information data collected, can analyze the character trait of people, learning capacity, mode of thinking, Intelligent Characteristics, personality characteristics etc. by the fingerprint of people, palmmprint and foot stricture of vagina information, and target is that people can be best understood from and recognize oneself.From the perspective of psychometry, dermatoglyph information data has high reliability and higher validity.Reason is, the dermatoglyph information of people is hereditary information, the most constant, especially finger print information, is not affected by time and environment, and the result of repetitive measurement is all consistent, so reliability is high.After the development that experienced by for many years and sector application, dermatoglyph information data be widely used in children education, psychological counselling, enter a higher school choose a job, occupational planning, the various fields such as personnel training.The collection of described Psychology and behavior data, such as by the exercise question of subjective testing, allows user's answer answer result is automatically uploaded to high in the clouds or background server.The collection of described behavior characteristics data, collects some daily behavior data of user, such as purchase data, investment data, trip data, Social behaviors data etc. by the internet use record relevant to subjects.Realize this mode to first have to participate in the subjects of research the mandate of internet, applications is provided, dock related system the most again and automatically obtain data.The mental status data of subjects's degree of depth are obtained by the way of psychological counselling.These data also can upload to high in the clouds by software system.
In certain embodiments, based on Ouath agreement, obtain third party and authorize and after certification, carry out subjects's network and access record, the acquisition of data.
In certain embodiments, carry out subjects by parsing URL address and access service, acquire access record and subjects's behavioral data.
In certain embodiments, by web crawlers, Larbin, Nutch, Heritrix, WebSPHINX, Mercator, PolyBot etc., the behavioral data of subjects is captured.
In certain embodiments, described collection dermatoglyph information data includes but is not limited to, finger print information, palmprint information etc., and uploads to cloud database.
In certain embodiments, described unified Analysis model includes: meta-model layer, integrated model layer and analysis model layer, in described meta-model layer, and the basic metadata of definition unified Analysis model；Such as, personal information is correlated with:
{ sex }, { birthday }, { blood group }, { educational background }, { specialty }, { occupation }
For another example, intelligence is correlated with:
{ language }, { memory }, { logic }, { space imagining ability }
In described integrated model layer, according to dermatoglyph information data and Psychology and behavior data, according to subjects using time and space as index, carry out the complete portrait data of subjects；
Integrated model layer builds and is divided into three levels, the tissue of the core data of first level is aiming at single-subject person；Second level is exactly to become long data the day after tomorrow of the person that organizes single-subject；3rd level is exactly the socialization's information organizing subjects.
In analyzing model layer, according to the complete portrait data in the basic metadata in described meta-model layer and integrated model layer, obtain analyzing model set.In described analysis model layer, have a lot of independent analysis models, formed and analyze model set.
Described control module 101 also in order to, carry out data analysis according to unified Analysis model, analysis result obtains adaptive model.In certain embodiments, based on unified Analysis pattern and various analytical tool, device can draw a series of significant conclusion by constantly processing with analytical data.These conclusions all towards certain class or a few class goal in research or application scenarios, just constitute adaptive model.
Described DBM 100, in order to deposit and to synchronize dermatoglyph information data, Psychology and behavior data, behavior characteristics data.
In certain embodiments, described DBM 100 includes the distributed data base service management system of at least one master control node and multiple back end, wherein said master control node is typically in order to run on the database service at least one back end by order and/or the configuration file management from user, and receive the database access request from applications, and therewith received database access request is sent to the database service that purpose database service is asked with execution；Described back end, in order to by from the management instruction management in above-mentioned master control node and configuration operation database service example thereon and resource associated there.
In certain embodiments, DBM 100 is distributed data base system, those skilled in the art can understand, generally use less computer system, every computer can individually be placed on a place, every computer all may have a complete copy copy in data base management system, or copied part copy, and there is the data base of oneself local, the many computers being positioned at different location are interconnected by network, collectively constitute complete, an overall large database concentrated in logic, be physically distributed.
The data left in DBM 100, when setting up model, are called by described control module 101, set up unified Analysis model further according to the data called, and are analyzed unified Analysis model, obtain adaptive model.Control module 101 further comprises and set up model, the data left in DBM 100 are called, as the basis setting up unified Analysis model.The most just analyzing described unified Analysis model, obtain adaptive model, described self adaptation carries out self-adaptative adjustment according to different scenes and dimension.
Also include model evaluation module 102, gather the parameter of data in order to assess the analysis result in unified Analysis model and adaptive model adjusting in DBM according to demand, and the structure of unified Analysis model and parameter in control module 101.The mode of described assessment includes but not limited to: iterative analysis, Optimized model.In this course, can heuristically adjust the parameter in described unified Analysis model, even adjust model concept and mutual relation, here it is the process of Optimized model.This process needs repeated multiple times carrying out, in order to obtain more meaningful result.Here an important key is exactly the reliability demonstration of result.
Described iteration includes: a) consider that the collection of whole system continues and automatization is carried out, so data volume is constantly increasing, say, that the colony of subjects is constantly expanding；B) can be with the bigger incompatible checking of data set in next round by last round of analysis result；If certain result is meaningful when c) concrete analysis judges, then in more large data sets, just should show higher score, the most higher statistic correlation；Just checking and optimization process can be united by above-mentioned iteration thinking so that whole evaluation process is the most efficient.In control module 101, it is substantially carried out following operation:
Gather dermatoglyph information data, Psychology and behavior data and behavior characteristics data, and be modeled according to the data collected, obtain unified Analysis model；
Carrying out data analysis according to unified Analysis model, analysis result obtains adaptive model；
When setting up model, the data left in DBM are called, set up unified Analysis model further according to the data called, and unified Analysis model is analyzed, obtain adaptive model.
In DBM 100, deposit and synchronize dermatoglyph information data, Psychology and behavior data, behavior characteristics data.
In model evaluation module 102, analysis result in assessment unified Analysis model and adaptive model according to demand adjustment DBM gather the parameter of data, and the structure of unified Analysis model and parameter in control module.
Fig. 2 is the control module internal structure schematic diagram in Fig. 1.
Described control module 101 in the present embodiment includes: dermatoglyph data acquisition module 1011, test and appraisal and tested profile module 1012 and external data collection module 1013.
In certain embodiments, dermatoglyph data acquisition module 1011 is by gathering the fingerprint of subjects, palmmprint, iris information, facial information etc., as the foundation of dermatoglyph data acquisition.
In certain embodiments, test and appraisal and tested profile module 1012 include but not limited to, by answer a question in subjectivity evaluation and test and user's consultation process related data obtained, and its data of subjects.Test includes but not limited to: character trait test, learning capacity test, mode of thinking test, Intelligent Characteristics test, personality spy test are levied.Test result is deposited by options or by the way of judging item in local or high in the clouds.
In certain embodiments, test and appraisal and tested profile module 1012 include but not limited to, based on name to up to a hundred, subjects is sample populations, the psychology of the subjects that the characteristic according to dermatoglyph and experiment are paid close attention to and Behavioral feature carry out correlation research, thus it is consistent for providing the performance in certain psychology with Behavioral feature of the subjects with which skin grain character.
In certain embodiments, test and appraisal and tested profile module 1012 include but not limited to, are inscribed the evaluation sample realizing psychology and Behavioral feature by subjective testing, and the data in direct collecting sample are as test and appraisal and the Data Source of tested profile module 1012.
In certain embodiments, described external data collection module 1013 includes internet access behavioral data, the such as user behavioral data in social networks, electricity business, video website etc..External data collection is carried out by the way of accessing URL or third party's mandate.
Fig. 3 is the DBM internal structure schematic diagram in Fig. 1.
Described DBM includes: dermatoglyph data base 1001, test and appraisal and tested profile module data base 1002, external data base 1003.
In certain embodiments, dermatoglyph data base 1001, the field in the table set up the collection demand according to dermatoglyph data is deposited respectively, it is simple to call when setting up unified Analysis model in control module 101.
In certain embodiments, test and appraisal and tested profile module data base 1002, by setting up the table in sample pattern or test result and rope, control module 101 directly invokes.
Wherein, dermatoglyph data base 1001, in order to organize and to store the dermatoglyph information data collected；I.e. deposit the dermatoglyph information in dermatoglyph data acquisition module 1011.
Test and appraisal and tested profile module data base 1002, in order to organize and to store the Psychology and behavior data of subjects；I.e. deposit the evaluating result in test and appraisal and tested profile module data base 1002 or sample data.
External data base 1003, in order to organize and to store the behavior characteristics data of subjects, i.e. depositing the data that user produces on the internet, the such as user behavioral data in social networks, electricity business, video website etc., wherein the acquisition mode of data needs third party to authorize.
Fig. 4 is the fingerprint analysing processing means structural representations based on big data in one embodiment of the present invention.
The present embodiment provides a kind of fingerprint analysing processing means based on big data include: control module 101 and DBM 100,
Described control module 101, in order to gather dermatoglyph information data, Psychology and behavior data and behavior characteristics data, and is modeled according to the data collected, obtains unified Analysis model；
Described control module 100 also in order to, carry out data analysis according to unified Analysis model, analysis result obtains adaptive model；
Described DBM 100, in order to deposit and to synchronize dermatoglyph information data, Psychology and behavior data, behavior characteristics data；
The data left in DBM, when setting up model, are called by described control module 101, set up unified Analysis model further according to the data called, and are analyzed unified Analysis model, obtain adaptive model；
Also include model evaluation module 102, gather the parameter of data in order to assess the analysis result in unified Analysis model and adaptive model adjusting in DBM according to demand, and the structure of unified Analysis model and parameter in control module.
Preferred as in the present embodiment, described control module 101 includes:
Dermatoglyph data acquisition module 1011, in order to gather the dermatoglyph information of subjects and to be uploaded to background server by the webserver；
Test and appraisal and tested profile module 1012, in order to gather the Psychology and behavior data of subjects, to obtain behavior characteristics data with the internet access behavior to subjects by the way of test and appraisal under online and/or line；
External data collection module 1013, in order to obtain behavior characteristics data to the internet access behavior of subjects.
Preferred as in the present embodiment, described DBM 100 includes:
Dermatoglyph data base 1001, in order to organize and to store the dermatoglyph information data collected；Test and appraisal and tested profile module data base 1002, in order to organize and to store the Psychology and behavior data behavior characteristics data of subjects；External data base 1003, in order to organize and to store the behavior characteristics data of subjects.
Preferred as in the present embodiment, it is also possible to include subjects's basic information database 1004, in order to organize and to deposit the essential information of subjects, include but not limited to: the information such as name, sex, birthday, blood group, educational background, specialty, occupation.
Preferred as in the present embodiment, APU also includes data integration and cleaning module 1014, in order to the dermatoglyph information data that will collect in control module and behavior characteristics data, according to unified Analysis model be framework carry out organizing and being stored in data base time, carry out data integration, cleaning, and the constraints of data in the above-mentioned control module of labelling in unified Analysis model.Include for the invention provides a kind of fingerprint analysing processing means based on big data: control module 101 and DBM 100,
Described control module 101, in order to gather dermatoglyph information data, Psychology and behavior data and behavior characteristics data, and is modeled according to the data collected, obtains unified Analysis model；
Described control module 100 also in order to, carry out data analysis according to unified Analysis model, analysis result obtains adaptive model；Described DBM 100, in order to deposit and to synchronize dermatoglyph information data, Psychology and behavior data, behavior characteristics data；The data left in DBM, when setting up model, are called by described control module 101, set up unified Analysis model further according to the data called, and are analyzed unified Analysis model, obtain adaptive model；Also include model evaluation module 102, gather the parameter of data in order to assess the analysis result in unified Analysis model and adaptive model adjusting in DBM according to demand, and the structure of unified Analysis model and parameter in control module.
Preferred as in the present embodiment, described control module 101 includes:
Dermatoglyph data acquisition module 1011, in order to gather the dermatoglyph information of subjects and to be uploaded to background server by the webserver；Test and appraisal and tested profile module 1012, in order to gather the Psychology and behavior data of subjects, to obtain behavior characteristics data with the internet access behavior to subjects by the way of test and appraisal under online and/or line；External data collection module 1013, in order to obtain behavior characteristics data to the internet access behavior of subjects.
Preferred as in the present embodiment, described DBM 100 includes:
Dermatoglyph data base 1001, in order to organize and to store the dermatoglyph information data collected；
Test and appraisal and tested profile module data base 1002, in order to organize and to store the Psychology and behavior data behavior characteristics data of subjects；
External data base 1003, in order to organize and to store the behavior characteristics data of subjects.
Preferred as in the present embodiment, it is also possible to include subjects's basic information database 1004, in order to organize and to deposit the essential information of subjects, include but not limited to: the information such as name, sex, birthday, blood group, educational background, specialty, occupation.
Preferred as in the present embodiment, APU also includes data integration and cleaning module 1014, in order to the dermatoglyph information data that will collect in control module and behavior characteristics data, according to unified Analysis model be framework carry out organizing and being stored in data base time, carry out data integration, cleaning, and the constraints of data in the above-mentioned control module of labelling in unified Analysis model.(remove, revise and supplement) is carried out for cognizable noise data.
The data that will collect above by control module 100, are that framework carries out organizing and being stored in data base according to unified Analysis model.
Relative mechanical in above-mentioned steps, but it is crucial that to do the work of some data cleansings, in order to follow-up analysis process can be more smooth and easy, and result is more accurate.Clean data and mainly remove unnecessary data, revise vicious data and supplement necessary data.
In certain embodiments, the model in unified Analysis model can retrain with logical consistency, to ensure the analyticity of data in the constraint of flag data necessity.If violating logical consistency and being necessary, it is necessary to revise data；If illegal logical consistency but dispensable, then data can be removed as one sees fit；If necessary, but shortage of data, then be accomplished by supplementary data.
Preferred as in the present embodiment, the described unified Analysis model in unified Analysis model data 1005 includes: meta-model layer, integrated model layer and analyze model layer,
In described meta-model layer, the basic metadata of definition unified Analysis model.Specifically, meta-model layer defines the basic element of user profile whole data model concept.For a tested individual, if needing to describe his dermatoglyph information, it is necessary to finger, Finger print, crestal line quantity, palm ADT angle etc.；If needing to describe his individual essential information, it is necessary to the information such as name, sex, birthday, blood group, educational background, specialty, occupation；If needing to assess his intelligent characteristic and level, it is necessary to the information such as language, memory, logic, space imagining ability；If needing to describe his personality feature, it is necessary to introversive, export-oriented, intuition, sensation, the information such as rationality, perception.
In certain embodiments, can be by above-mentioned concept be defined at described meta-model layer.
It addition, also include the event that out of Memory, such as tested individual are experienced in developmental process, it is necessary to the data such as time, place, environment, event category are expressed, and above-mentioned concept needs also exist for clear defined in meta-model layer.
In the present embodiment, the definition for each concept will include how to quantify corresponding information, in order to analyzes the execution of system.
Specifically, such as, the date storage method of crestal line quantity, a certain character trait tendency and marking etc..These concept definitions accurately have been had, it is possible to express the model of following integrated layer without ambiguous ground at described meta-model layer.
In described integrated model layer, according to dermatoglyph information data and Psychology and behavior data, according to subjects using time and space as index, carry out the complete portrait data of subjects；The system of concept set up based on above-mentioned meta-model layer, it is possible to set up the model system with subjects as core at integrated model layer.The structure of described model system is divided into three levels:
The tissue of the core data of first level is aiming at single-subject person, core data mainly includes the individual essential information defined in meta-model layer, dermatoglyph information, and the information such as congenital intelligence, personality characteristics, the learning types and the style gone out by dermatoglyph information inference.Core data illustrates single-subject congenital the had attribute of person, will not change over time and change.
Second level is exactly to become long data the day after tomorrow of the person that organizes single-subject.Become the day after tomorrow long data can be described by time, space and the critical events that subjects is experienced.Such as one adult of 30 years old experienced by defined in developmental psychology some stages from be born instantly on time dimension be certainly, and (stage of different theory definition is the most different, as long as using the theory of a set of significant authority, in 8 stages of the life span development of such as Sven-Gan Eriksson, this has complete definition at meta-model layer)；Spatial Dimension may experience the transition of living environment several times, such as, from the local of birth to the city gone to school again to the city (description of spatial information this to growth environment can also be realized by concept defined in meta-model) of work；It is finally that some affect events that subjects's body and mind grows up and are also required to organize, such as parental separation or history of disease that some are more serious etc..Become the source main subjectivity exactly test and appraisal of long data the day after tomorrow and seek advice from accumulated subjects's file data by user.
3rd level is exactly the socialization's information organizing subjects.Mainly include social behavior and the social relations data of subjects.Work in the social behavior such as consumption on network and amusement behavior, and daily life, move, the behavior such as tourism.Social behavior can be embodied in a series of label and be associated with subjects, such as Duo Shou party, donkey friend, workaholic etc..Social relations is exactly the social relation network that the household of subjects, friend, colleague etc. set up.
In certain embodiments, if the data of several subjectss in relational network are also in data base, then just directly they can be set up association.The data that the internet access behavior of the Data Source of socialization's information mainly subjectivity evaluation and test and subjects's file data and user produces.
In described analysis model layer, according to the complete portrait data in the basic metadata in described meta-model layer and integrated model layer, obtain analyzing model set.
In above-mentioned analysis model layer, one is analyzed model is in order to one, multiple or a series of dermatoglyph information research or analysis target are custom-designed, so having a lot of independent analysis models in analyzing model layer, forms analysis model set.Such as, a target is to analyze the social behavior's performance in the case of having the people of certain special Finger print to experience parental separation before pre school age.So building the analysis model for this target when, it is accomplished by integrated model layer extracting and there are three aspect particular communitys (has certain special Finger print, time dimension is pre school age, and critical events is parental separation) subjects's data, be organized into a simplified model.
In certain embodiments, described simplified model, it is simply that removing the information unrelated with this goal in research, the model that integrated layer compared by the model obtained is simpler, in order that analyzing result more rapidly and effectively.
Preferred as in the present embodiment, APU also includes data analysis module 1016, in order to perform multi-dimensional data analysis according to the data acquisition system in unified Analysis model as object, obtain the concrete classification of each dimensional concept, and the incidence relation between different dimensions and causal rule.Described dimension is exactly the different aspects defined of the meta-model layer in unified Analysis model more.Such as, the dermatoglyph information of a subjects is exactly a dimension, and his congenital intelligent characteristic is again a dimension, and his personality feature is also a dimension etc..Multidimensional analysis seeks to find out cause and effect inherent between these different dimensions or incidence relation.Such as, how the crowd with any stricture of vagina type feature in unique advantage in terms of a certain or certain several congenital intelligence, thus can affect the feature that even shapes one's character.Included but not limited to by the technological means analyzing above-mentioned relation: multivariate statistics, time series analysis, cluster result, machine learning etc..Such as, dermatoglyph information for a subjects is exactly a dimension, his congenital intelligent characteristic is again a dimension, his personality feature is also an analysis target of a dimension, the method that generally can use multivariate statistics, simple correlation analysis is carried out as independent variable, intelligent characteristic as dependent variable using stricture of vagina type feature；Or can also carry out, using stricture of vagina type and intelligent characteristic as independent variable, the correlation analysis being combined as dependent variable using character trait.
In certain embodiments, if the analysis of dependency can not draw significant conclusion, then the method re-using cluster result carries out more sophisticated category to congenital intelligence or personality characteristics.
Preferred as in the present embodiment, the described adaptive model in dermatoglyph knowledge model data base 1006 is set up as follows:
Subjects's multi-dimensional data is obtained according to described unified Analysis model；
According to the behavior characteristics in multi-dimensional data, carry out the self adaptation change of analysis conclusion, validity and the dependency of subjects；
Adaptive model is set up based on different targets or application scenarios in above-mentioned processing procedure.
Based on unified Analysis pattern and various analytical tool, a series of significant conclusion can be drawn by constantly processing with analytical data.Those conclusions all towards certain class or a few class goal in research or application scenarios, just constitute adaptive model.Such as, in the application scenarios of children education, there is the child being in pre school age of a few kinds of dermatoglyphic patternses, on the premise of not meeting with domestic calamity or disease puzzlement, there is some special behavior characteristics: active, like risk etc..The self-adaptive features of this process is then embodied in, and along with processing being continuously increased of data, some conclusion can be enhanced, and namely Relevance scores improves, and validity improves；Some then may be weakened, and Relevance scores reduces, validity reduction etc..It is accomplished by adjusting parameter, structure or thoroughly being rejected after the validity of conclusion is reduced to some threshold value (typical such as 50%).So it is possible not only to remove inaccurate factor, it is also possible to reserve more space for new conclusion.Therefore, adaptive model just can improve constantly quality in such adaptive process.
Further, described unified Analysis model and adaptive model also in order to be iterated analyzing to collection data, are optimized by described model evaluation module 102；
Optimization process includes, adjusts the parameter in above-mentioned model, and adjusts above-mentioned model concept, mutual relation.Described optimization process includes the Establishing process of adaptive model, obtains subjects's multi-dimensional data according to described unified Analysis model；According to the behavior characteristics in multi-dimensional data, carry out the self adaptation change of analysis conclusion, validity and the dependency of subjects；Adaptive model is set up based on different targets or application scenarios in above-mentioned processing procedure.
Further, described control module is arranged at mobile terminal or PC end in order to gathering the harvester of dermatoglyph information, so can facilitate the information to subjects, as long as subjects can be realized as the collection of dermatoglyph information by mobile phone.Described DBM is uploaded to high in the clouds or locally stored by the Internet in order to organizing and to deposit collection data, based on the big data collected, carries out storing mode towards high in the clouds.
In certain embodiments, the model in unified Analysis model can retrain with logical consistency, to ensure the analyticity of data in the constraint of flag data necessity.If violating logical consistency and being necessary, it is necessary to revise data；If illegal logical consistency but dispensable, then data can be removed as one sees fit；If necessary, but shortage of data, then be accomplished by supplementary data.
Preferred as in the present embodiment, the described unified Analysis model in unified Analysis model data 1005 includes: meta-model layer, integrated model layer and analyze model layer,
In described meta-model layer, the basic metadata of definition unified Analysis model.Specifically, meta-model layer defines the basic element of user profile whole data model concept.For a tested individual, if needing to describe his dermatoglyph information, it is necessary to finger, Finger print, crestal line quantity, palm ADT angle etc.；If needing to describe his individual essential information, it is necessary to the information such as name, sex, birthday, blood group, educational background, specialty, occupation；If needing to assess his intelligent characteristic and level, it is necessary to the information such as language, memory, logic, space imagining ability；If needing to describe his personality feature, it is necessary to introversive, export-oriented, intuition, sensation, the information such as rationality, perception.
In certain embodiments, can be by above-mentioned concept be defined at described meta-model layer.
It addition, also include the event that out of Memory, such as tested individual are experienced in developmental process, it is necessary to the data such as time, place, environment, event category are expressed, and above-mentioned concept needs also exist for clear defined in meta-model layer.
In the present embodiment, the definition for each concept will include how to quantify corresponding information, in order to analyzes the execution of system.
Specifically, such as, crestal line quantity and the measurement of ADT and date storage method, a certain character trait tendency and marking etc..These concept definitions accurately have been had, it is possible to express the model of following integrated layer without ambiguous ground at described meta-model layer.
In certain embodiments, if the data of several subjectss in relational network are also in data base, then just directly they can be set up association.The data that the internet access behavior of the Data Source of socialization's information mainly subjectivity evaluation and test and subjects's file data and user produces.
In described analysis model layer, according to the complete portrait data in the basic metadata in described meta-model layer and integrated model layer, obtain analyzing model set.
In above-mentioned analysis model layer, one is analyzed model is in order to one, multiple or a series of dermatoglyph information research or analysis target are custom-designed, so having a lot of independent analysis models in analyzing model layer, forms analysis model set.Such as, a target is to analyze the social behavior's performance in the case of having the people of certain special Finger print to experience parental separation before pre school age.So building the analysis model for this target when, it is accomplished by integrated model layer extracting and there are three aspect particular communitys (has certain special Finger print, time dimension is pre school age, and critical events is parental separation) subjects's data, be organized into a simplified model.
In certain embodiments, described simplified model, it is simply that removing the information unrelated with this goal in research, the model that integrated layer compared by the model obtained is simpler, in order that analyzing result more rapidly and effectively.
Preferred as in the present embodiment, APU also includes data analysis module 1016, in order to perform multi-dimensional data analysis according to the data acquisition system in unified Analysis model as object, obtain the concrete classification of each dimensional concept, and the incidence relation between different dimensions and causal rule.Described dimension is exactly the different aspects defined of the meta-model layer in unified Analysis model more.Such as, the dermatoglyph information of a subjects is exactly a dimension, and his congenital intelligent characteristic is again a dimension, and his personality feature is also a dimension etc..Multidimensional analysis seeks to find out cause and effect inherent between these different dimensions or incidence relation.Such as, how the crowd with any stricture of vagina type feature in unique advantage in terms of a certain or certain several congenital intelligence, thus can affect the feature that even shapes one's character.Included but not limited to by the technological means analyzing above-mentioned relation: multivariate statistics, time series analysis, cluster result, machine learning etc..Such as, dermatoglyph information for a subjects is exactly a dimension, his congenital intelligent characteristic is again a dimension, his personality feature is also an analysis target of a dimension, the method that generally can use multivariate statistics, simple correlation analysis is carried out as independent variable, intelligent characteristic as dependent variable using stricture of vagina type feature；Or can also carry out, using stricture of vagina type and intelligent characteristic as independent variable, the correlation analysis being combined as dependent variable using character trait.
In certain embodiments, if the analysis of dependency can not draw significant conclusion, then the method re-using cluster result carries out more sophisticated category to congenital intelligence or personality characteristics.
Fig. 5 is the fingerprint analysing processing means structural representations based on big data in one embodiment of the present invention.
Described control module also includes, optimizes acquisition module 1015, in order to revise the granularity in gatherer process, and adjusts collection target.The unified Analysis model in unified Analysis model database 1005 in the present embodiment, defines the basic element of user profile whole data model concept at meta-model layer；
Meta-model layer is defined as follows basic element:
If desired describe dermatoglyph information, then need finger, Finger print, crestal line quantity, palm ADT angle etc.；
If desired describe his individual essential information, then need information such as { name, sex, birthday, blood group, educational background, specialty, occupations }；If desired his intelligent characteristic and level are assessed, it is necessary to information such as { language, memory, logic, space imagining abilities }；Personality feature is if desired described, it is necessary to the information such as { introversive, export-oriented, intuition, sensation, rationality, perception }.
Further, described unified Analysis model and adaptive model also in order to be iterated analyzing to collection data, are optimized by described model evaluation module 102；
Optimization process includes, adjusts the parameter in above-mentioned model, and adjusts above-mentioned model concept, mutual relation.Described optimization process includes the Establishing process of adaptive model, obtains subjects's multi-dimensional data according to described unified Analysis model；According to the behavior characteristics in multi-dimensional data, carry out the self adaptation change of analysis conclusion, validity and the dependency of subjects；Adaptive model is set up based on different targets or application scenarios in above-mentioned processing procedure.
Further, described control module is arranged at mobile terminal or PC end in order to gathering the harvester of dermatoglyph information, so can facilitate the information to subjects, as long as subjects can be realized as the collection of dermatoglyph information by mobile phone.Described DBM is uploaded to high in the clouds or locally stored by the Internet in order to organizing and to deposit collection data, based on the big data collected, carries out storing mode towards high in the clouds.
Fig. 6 is the unified Analysis model structure schematic diagram that in one embodiment of the invention, fingerprint analysings based on big data process.
In the present embodiment, described unified Analysis model includes: meta-model layer 600, integrated model layer 601 and analysis model layer 602,
In described meta-model layer 600, the basic metadata of definition unified Analysis model；At the basic element of user profile whole data model concept defined in described meta-model layer.Such as a tested individual, his dermatoglyph information is if desired described, it is necessary to finger, Finger print, crestal line quantity, palm ADT angle etc.；The most such as, his individual essential information is if desired described, it is necessary to the information such as name, sex, birthday, blood group, educational background, specialty, occupation；For another example, his intelligent characteristic and level are if desired assessed, it is necessary to the information such as language, memory, logic, space imagining ability；For another example, his personality feature is if desired described, it is necessary to introversive, export-oriented, intuition, sensation, the information such as rationality, perception.
In described integrated model layer 601, according to dermatoglyph information data and Psychology and behavior data, according to subjects using time and space as index, carry out the complete portrait data of subjects；The system of concept set up based on meta-model layer, it is possible to set up the integrated model layer with subjects as core at integrated model layer.
The tissue of the core data of first level is aiming at single-subject person, wherein core data mainly includes the individual essential information defined in meta-model layer, dermatoglyph information, and the information such as congenital intelligence, personality characteristics, the learning types and the style gone out by dermatoglyph information inference.Core data illustrates single-subject congenital the had attribute of person, will not change over time and change.
Second level is exactly to become long data the day after tomorrow of the person that organizes single-subject.
3rd level is exactly the socialization's information organizing subjects.
In analyzing model layer 602, according to the complete portrait data in the basic metadata in described meta-model layer and integrated model layer, obtain analyzing model set.In analyzing model layer 602, one is analyzed model is in order to one or a series of research or analysis target are custom-designed, so having a lot of independent analysis models in analyzing model layer, forms analysis model set.
Fig. 7 is fingerprint analysing process flow schematic diagrams based on big data in one embodiment of the invention.
S700 gathers dermatoglyph information data, Psychology and behavior data and behavior characteristics data, and is modeled according to the data collected, and obtains unified Analysis model；
S701 carries out data analysis according to unified Analysis model, obtains adaptive model according to analysis result；
In certain embodiments, based on unified Analysis pattern and various analytical tool, a series of significant conclusion can be drawn by constantly processing with analytical data.These conclusions all towards certain class or a few class goal in research or application scenarios, just constitute adaptive model.Such as, adaptive model can include but not limited to, the aspect such as child-parent education, enter a higher school employment, interpersonal communication, enterprises recruit persons for jobs, blood group, Occupational assessment, Psychological Evaluation and psychological counselling, body and mind spirit growth.
Integrated model layer builds and is divided into three levels, the tissue of the core data of first level is aiming at single-subject person；Second level is exactly to become long data the day after tomorrow of the person that organizes single-subject；3rd level is exactly the socialization's information organizing subjects.
In analyzing model layer, according to the complete portrait data in the basic metadata in described meta-model layer and integrated model layer, obtain analyzing model set.In described analysis model layer, have a lot of independent analysis models, formed and analyze model set.
The corresponding data collected in described unified Analysis model is processed by S702 by described adaptive model；
Described collection data are iterated analyzing by S703, are optimized described unified Analysis model and adaptive model.
It can be seen that in the present embodiment by use based on computer software and the big data method of Internet technology, can easily process the data of ten million magnitude subjects.Owing to carrying out data analysis according to unified Analysis model, analysis result obtains adaptive model.So whether subjective evaluation and test or external data, it is all the process of a persistence, and the most limited by regions, therefore from macroscopically, time and spatially can form a normality.The analysis result so drawn is the most more meaningful.Owing to described collection data to be iterated analyze, described unified Analysis model and adaptive model are optimized.The method using big data performs efficiently, even if data volume is the hugest, it is also possible to complete one within a very short time and take turns analysis, so noise factor will not be introduced.And the ability of unique data accumulation and iteration optimization makes model constantly to evolve.
Those of ordinary skill in the field it is understood that more than; the described specific embodiment being only the present invention, is not limited to the present invention, all within the spirit and principles in the present invention; the any modification, equivalent substitution and improvement etc. done, should be included within the scope of the present invention.
Claims (10)
1. a fingerprint analysing processing means based on big data, it is characterised in that including: control module
And DBM,
Described control module, in order to gather dermatoglyph information data, Psychology and behavior data and behavior characteristics number
According to, and be modeled according to the data collected, obtain unified Analysis model；
Described control module also in order to, carry out data analysis according to unified Analysis model, analysis result obtains
Adaptive model；
Described DBM, in order to deposit and to synchronize dermatoglyph information data, Psychology and behavior data, behavior
Characteristic；
The data left in DBM, when setting up model, are called by described control module,
Set up unified Analysis model further according to the data called, and unified Analysis model is analyzed, obtain
Adaptive model；
Also include model evaluation module, in order to assess the analysis knot in unified Analysis model and adaptive model
Fruit also adjusts the parameter gathering data in DBM according to demand, and unified Analysis in control module
The structure of model and parameter.
Fingerprint analysing processing means based on big data the most according to claim 1, it is characterised in that
Described control module includes:
Dermatoglyph data acquisition module, in order to gather the dermatoglyph information of subjects and to be uploaded by the webserver
To background server；
Test and appraisal and tested profile module, in order to gather subjects's by the way of test and appraisal under online and/or line
Psychology and behavior data；
External data collection module, in order to obtain behavior characteristics number to the internet access behavior of subjects
According to.
Fingerprint analysing processing means based on big data the most according to claim 1, it is characterised in that
Described DBM includes:
Dermatoglyph data base, in order to organize and to store the dermatoglyph information data collected；
Test and appraisal and tested profile module data base, in order to organize and to store the Psychology and behavior data of subjects；
External data base, in order to organize and to store the behavior characteristics data of subjects.
Fingerprint analysing processing means based on big data the most according to claim 1, it is characterised in that
Also include data integration and cleaning module, in order to the dermatoglyph information data that will collect in control module and
Behavior characteristics data, according to unified Analysis model be framework carry out organizing and being stored in data base time, enter
Line data set becomes, cleans, and the constraint of data in the above-mentioned control module of labelling in unified Analysis model
Condition.
Fingerprint analysing processing means based on big data the most according to claim 1, it is characterised in that
Also include data analysis module, in order to perform many according to the data acquisition system in unified Analysis model as object
Dimension data is analyzed, and obtains the concrete classification of each dimensional concept, and the incidence relation between different dimensions
And causal rule.
Fingerprint analysing processing means based on big data the most according to claim 1, it is characterised in that
Described control module also includes, optimizes acquisition module, in order to revise the granularity in gatherer process, and adjusts
Whole collection target.
Fingerprint analysing processing means based on big data the most according to claim 1, it is characterised in that
Described model evaluation module also in order to be iterated analyzing to gathering data, to described unified Analysis model and
Adaptive model is optimized；
Optimization process includes, adjusts the parameter in above-mentioned model, and adjusts above-mentioned model concept, mutually
Relation.
Fingerprint analysing processing means based on big data the most according to claim 1, its feature exists
In, described unified Analysis model includes: meta-model layer, integrated model layer and analysis model layer,
In described meta-model layer, the basic metadata of definition unified Analysis model；
In described integrated model layer, according to dermatoglyph information data and Psychology and behavior data, according to subjects
Using time and space as index, carry out the complete portrait data of subjects；
In analyzing model layer, according in the basic metadata in described meta-model layer and integrated model layer
Complete portrait data, obtain analyzing model set.
9. a fingerprint analysing processing method based on big data, it is characterised in that including:
Gather dermatoglyph information data, Psychology and behavior data and behavior characteristics data, and according to collecting
Data be modeled, obtain unified Analysis model；
Carry out data analysis according to unified Analysis model, obtain adaptive model according to analysis result；
By described adaptive model, the corresponding data collected in described unified Analysis model is carried out
Process.
Fingerprint analysing processing method based on big data the most according to claim 9, its feature exists
In, also include, be iterated described collection data analyzing, to described unified Analysis model and self adaptation
Model is optimized.
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