CN111581304B - Method for automatically drawing family map based on social population familial relationship - Google Patents
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- CN111581304B CN111581304B CN202010418831.6A CN202010418831A CN111581304B CN 111581304 B CN111581304 B CN 111581304B CN 202010418831 A CN202010418831 A CN 202010418831A CN 111581304 B CN111581304 B CN 111581304B
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention discloses a method for automatically drawing a family map based on social population familial relationship, which comprises the following steps: step 1: aggregating the same administrative villages; step 2: generating family information for each surname; and step 3: acquiring all account number sets; and 4, step 4: with the owner as a starting point, the family maps are connected through the relation of exhaustive personnel in the method; and 5: all the householders are merged to a first level in the current family; step 6: searching the closest relation according to the exhaustive sequence to be used as the first level of the family for processing; and 7: uniformly associating the current personnel and the relationship of the descendant families to the parent family; and 8: a family information is automatically associated for all people. The method carries out multi-dimensional mining modeling by deeply analyzing the social population data in a specific range, merges by using a family as a unit, and automatically merges the groups with family genetic characteristics to the same family by using a recursive exhaustive personnel relationship branch.
Description
Technical Field
The invention relates to the technical field of drawing of social population familial relations, in particular to a method for automatically drawing a family map based on the social population familial relations.
Background
In the prior art, family maps are drawn for social population family relations by adopting technical means of 'manual registration and making book- > manual drawing and marking- > computer copying', carpet type investigation and registration are carried out by 'human sea' tactics, the maps are drawn manually through inquiry and registration of basic conditions, and finally the maps are gathered and recorded into a computer for filing again. The specific method used in most scenarios is, as shown in fig. 1: 1. the regional scope of the population group to be analyzed is defined, and the smallest regional unit is divided; 2. the minimum regional units are used for checking one by one, the inquiry and survey are carried out one by one for families or groups, and meanwhile, the known situations are registered and registered; 3. manually drawing in a paper file through the queried population family relationship, and labeling the direct relationship and the basic information (name and identity card) of personnel; 4. and when the investigation of one regional unit is finished, recording the paper records into a computer one by one, and recording and drawing the paper records again to be used as electronic filing records. In the process, the problems of omission, errors, handwriting recognition and the like are difficult to avoid through a large amount of manual records, the accuracy of work results is greatly influenced, the efficiency is low, and the period is too long.
The disadvantages of the prior art are the following: 1. the data general situation in the investigation range is not known, and the working period cannot be reasonably estimated; 2. standard data are not used as reference, the expression of the object to be checked is completely relied on, and the accuracy of the control data is difficult to realize; 3. the larger the region range of investigation is, the higher the labor, period and cost are required to be invested; 4. manual recording and drawing are carried out, the error probability is high, and the tracing and timely error correction are difficult; 5. the possibility of secondary errors exists in secondary input, and error guidance is possibly made for later data utilization; 6. lack of scientific sociological relationship analysis, the fact that the pen is actually dropped does not have sufficient data testimony, and does not have rigorous scientific persuasion when applied to related fields.
Disclosure of Invention
The invention aims to provide a method for automatically drawing a family map based on social population familial relationship, which solves the problems of the original pure manual registration, input, groping and hand drawing modes, avoids the uncertainty of human factors, fills the blank of basic data lacking in specifications and standards, realizes accurate and rapid automatic merging and map drawing by unified and standard data analysis and mining, effectively improves the utilization value and the working efficiency of data, effectively utilizes data resources to analyze the data and embodies the data value.
In order to solve the technical problems, the invention provides the following technical scheme:
a method for automatically drawing a family map based on social population familial relationship comprises the following steps:
step 1: in a designated area, aggregating the same administrative villages, traversing on the basis of the administrative villages, and declaring as: village list vilagelist;
step 2: traversing a village list villageList, screening through a village main key, acquiring surname information of all people under the current village, and aggregating surnames to declare surname List; meanwhile, family information is generated for each surname, a family naming rule is set as 'administrative division name + surname + family', and each surname automatically corresponds to a family;
and step 3: screening all personnel account information under the current condition by administrative villages and surnames to obtain all account number sets, and declaring the account number sets to be familyNoList;
and 4, step 4: traversing famityNoList, analyzing all personnel relations in the current house number, taking the owner as a starting point, connecting family maps through the relation of exhausted personnel in the method, wherein the exhaust sequence is 1. the owner is- >2. the owner is father- >3. the owner is grandfather- >4. the owner is tertiary- >5. the owner is brother- >6. the owner is brother- >7. the owner is son- > the owner is nephew- >9. the owner is grandson- >10. other relatives- >11. no owner personnel; firstly, traversing to an ancestor through an owner relationship, wherein the ancestor at least comprises a father, a grandfather and a grandfather; secondly, extending to the siblings, wherein the siblings at least comprise brothers and cousin; then exhausting to descendants, wherein the descendants at least comprise children, nephew and grandchildren; finally, processing the personnel without relatives and householders;
and 5: under the default condition, all the householders are merged to a first level in the current family, if the relationship of the householder and the father exists in the current family relationship, the current householder is changed into a second level, the householder and the father are set into the first level, and similarly, if the relationship of the householder and the grandfather exists, the householder and the father are changed into the second level;
step 6: when the family relationship does not have the family main relationship, searching the closest relationship according to the exhaustive sequence to be used as the first level of the family for processing;
and 7: when the relationships of all the persons are exhausted, the relationship between the current person and the family of the descendant is uniformly associated to the family of the father to realize automatic association;
and 8: after all the steps are finished, whether people which are not merged to the family still exist is judged, if yes, family information is automatically associated for all people and exists as an independent family.
In the above, the same administrative village is aggregated in the step 1: the method is characterized in that aggregation is carried out on villages/communities in the smallest administrative unit, N village/community sets are aggregated in the range of a designated area, and each region set comprises N surname sets.
In the above, the surname in step 2 is polymerized: an omnibearing data model is established by mining the data relationship of social population to cover the basic information of people, such as surnames, names, alias names, sexes, identity card numbers, ages, places of birth and places of continence; personnel family information, such as family type, family number, family relationship and family register address; parent spouse information such as father name identity card number, mother name identity card number, spouse name identity card number; region address information, such as current address, household address, and birth address; migration change information, such as migration in and out, marital change, last family of the newborn, and family migration; government administration management information, such as home units, jurisdictions, public security, civil administration; and (3) performing aggregation calculation on the data main body by analyzing and mining direct and indirect relations among all data variables, and finally, connecting all relevant data in series by using a family theme and merging N branches taking a user owner as a unit on the main line to form a family data chain.
In the above, the step 2 of aggregating the surnames further includes: in a village/community set of regional aggregation, the family names are aggregated, groups with the same family names are automatically aggregated into N family sets, and each family set comprises N family sets.
In the foregoing, the migrating the change information in step 2 further includes: and (4) migration information aggregation, which is to aggregate the information based on the population migration information, acquire the information before migration change, and aggregate the information with the set after family aggregation again to form a data chain for association.
In the above, the current account number in step 4 is: the method refers to that in each surname set, the family 'house number' is used for carrying out polymerization again, N family sets are automatically polymerized in each surname set, and each family set comprises independent personnel.
In the above, step 8 is followed by: based on each subset of the aggregation calculation, the personnel individuals in the minimum set are taken as subjects, calculation is carried out item by item through the account number, the relationship with the account, the father information, the information before change/migration and the like, aggregation data with different sizes of the family, surname and region are connected through the relationship of the two personnel individuals, and the maximum merging and integration among the sets are realized through exhaustive and recursive analysis.
Compared with the prior art, the invention has the following beneficial effects: 1. according to the method, through deep analysis of social population data in a specific range, multi-dimensional mining modeling is performed by referring to geographic information, surname information, family account information, personnel migration change information, marital registration information and the like, merging is performed by taking an account as a unit, recursive exhaustive personnel relationship branches are performed, and groups with family genetic characteristics are automatically merged to the same account; 2. in each family unit, carrying out all-around analysis by taking a householder as a center, wherein the all-around analysis comprises direct family relations (such as parents, brothers, children and grandchildren), spouse relations, sibling family relations (tertiary and couthers), and the like, and a family atlas of a tree structure is automatically drawn in a 'father-son' connecting line mode; 3. according to the method, the biological genetic characteristics are referenced, and people who do not conform to the biological genetic relationship in the same family, such as people with the same exterior names in the vegetation, the harvest, the holding, the immigration with the mother, the foreign immigration and the like, are automatically marked, so that more comprehensive data variables are provided for the group biological genetic research; 4. in the method, a rapid merging method is provided for people with known relations in different families, and the family relation analysis is respectively carried out upwards and downwards according to known relation points, so that the rapid merging of the families with points and faces is realized; 5. the method carries out multidimensional series connection on population in a specific region range by taking social relation as a link, can quickly analyze the Y chromosome population data with male genetic characteristics, and can be scientifically and effectively used in the fields of criminal investigation solving, ancestor seeking relatives and the like. 6. The method solves the problems of the original pure manual registration, input, groping and hand drawing modes, avoids the uncertainty of human factors, fills the blank of basic data lacking in specifications and standards, realizes accurate and rapid automatic merging and map drawing by unifying standard data analysis and mining, effectively improves the utilization value and the working efficiency of data, effectively utilizes data resources to analyze the data and embodies the data value; 7. by data processing of the method, the data overview of the target area can be clearly obtained, such as: the number of administrative villages, the number of surnames, the number of families, the number of population, the number of males and the like provide data reference for work deployment planning; 8. the method realizes maximum association and combination of data through data merging, and saves a large amount of time, labor, financial resources and other costs for population investigation and registration; by means of multi-dimensional data modeling, the effect of point-to-surface is achieved in the process of map drawing, and the working efficiency of family merging association is improved; 9. the method is full-flow electronic automatic recording, completely avoids the problems of error registration, error association, error combination, wrongly written characters and the like in a manual leading traditional mode, and ensures the accuracy and the effectiveness of data; 10. based on the processing of the method, the working target can be accurately and quickly achieved, the working efficiency is improved by geometric multiples, and the automatic merging and atlas drawing can be completed only in 15-30 minutes on the basis of population data of each million population; 11. the method fully refers to the genetic characteristics of the gene, automatically marks out the population relation individuals which do not meet the genetic characteristics, and provides scientific data basis for the application in the actual field such as public security, judicial expertise and the like.
Drawings
FIG. 1 is a schematic diagram of a family mapping method based on the family relationship of the social population in the prior art.
FIG. 2 is a schematic diagram of an exhaustive analysis process of the relationship between persons according to the present invention.
FIG. 3 is a schematic diagram of a personnel relationship analysis process according to the present invention.
FIG. 4 is a schematic diagram of the method of the present invention.
FIG. 5 is a diagram illustrating an example of data calculation results in the method structure of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1-2, the present invention provides a method for automatically drawing a family map based on social population familial relationship, which comprises the following steps: the method comprises the following steps:
step 1: in a designated area, aggregating the same administrative villages, traversing on the basis of the administrative villages, and declaring as: village list vilagelist;
step 2: traversing a village list villageList, screening through a village main key, acquiring surname information of all people under the current village, and aggregating surnames to declare surname List; meanwhile, family information is generated for each surname, a family naming rule is set as 'administrative division name + surname + family', and each surname automatically corresponds to a family;
and step 3: screening all personnel account information under the current condition by administrative villages and surnames to obtain all account number sets, and declaring the account number sets to be familyNoList;
and 4, step 4: ergodic famityNoList, analyzing all the personnel relations in the current house number, taking the family as a starting point, connecting family maps through the relation of exhausted personnel in the method, wherein the exhausting order is' 1. the owner- >2. the owner, father- >3. the owner, grandfather- >4. the owner, uncle- >5. the owner, brother- >6. the owner, brother- >7. the owner, son- >9. the owner, grandson- >10. other relatives- >11. no owner, firstly traversing upwards the ancestor through the owner relation (father, uncle), secondly extending to the grandfather, father brother), then exhausting to son, grandson, grandfather, grandson, and finally processing no family relation and no family relation;
and 5: under the default condition, all the householders are merged to a first level in the current family, if the relationship of the householder and the father exists in the current family relationship, the current householder is changed into a second level, the householder and the father are set into the first level, and similarly, if the relationship of the householder and the grandfather exists, the householder and the father are changed into the second level;
step 6: when the family relationship does not have the family main relationship, searching the closest relationship according to the exhaustive sequence to be used as the first level of the family for processing;
and 7: when the relationships of all the persons are exhausted, the relationship between the current person and the family of the descendant is uniformly associated to the family of the father to realize automatic association;
and 8: after all the steps are finished, whether people which are not merged to the family still exist is judged, if yes, family information is automatically associated for all people and exists as an independent family.
The structure of the method of the invention, as shown in fig. 4, comprises the following steps:
and the surnames in the step 2 are polymerized: the method comprises the steps of establishing an omnibearing data model by mining social population data relationship, covering basic information of personnel (such as family names, alias names, sexes, identity numbers, ages, places of birth, native places and the like), family information of personnel (such as family types, family numbers, relationship with a family owner, family addresses and the like), parent spouse information (such as father name identity numbers, mother name identity numbers, spouse name identity numbers and the like), region address information (such as current addresses, family addresses, birth addresses and the like), migration change information (such as immigration, marital change, new-born family, family migration and the like), government administration information (such as attribution units, administration units, public security, civil administration and the like), performing aggregation calculation on data main bodies by analyzing and mining direct and indirect relationships among data variables, and finally performing series connection on all associated data by family topics, and merging the N branches on the main line with the householder as the unit to form a family data chain.
The same administration village is aggregated in the step 1: aggregating with the minimum administrative unit of village/community, aggregating the specified area range into N village/community sets, wherein each region set comprises N surname sets;
the step 2 of aggregating the surnames further comprises the following steps: in a village/community set of regional aggregation, the family names are aggregated, groups with the same family names are automatically aggregated into N family sets, and each family set comprises N family sets;
the current account number in the step 4 is as follows: the method is characterized in that the family 'house number' is used for carrying out polymerization again in each surname set, N family sets are automatically polymerized in each surname set, and each family set comprises independent personnel;
the migrating change information in step 2 further includes: and (4) migration information aggregation, which is to aggregate the information based on the population migration information, acquire the information before migration change, and aggregate the information with the set after family aggregation again to form a data chain for association.
The step 8 is followed by: the data merging part is, as shown in fig. 5, based on each subset of the aggregation calculation, calculating item by item from the individual person in the minimum set by the account number, the relationship with the account, the parent information, the information before change/migration, and the like, and connecting the aggregation data of different sizes of the family, the surname, and the region by the relationship of the two individual persons, so as to realize the maximum merging integration between each set through exhaustive and recursive analysis.
The invention has the following beneficial effects: 1. according to the method, through deep analysis of social population data in a specific range, multi-dimensional mining modeling is performed by referring to geographic information, surname information, family account information, personnel migration change information, marital registration information and the like, merging is performed by taking an account as a unit, recursive exhaustive personnel relationship branches are performed, and groups with family genetic characteristics are automatically merged to the same account; 2. in each family unit, carrying out all-around analysis by taking a householder as a center, wherein the all-around analysis comprises direct family relations (such as parents, brothers, children and grandchildren), spouse relations, sibling family relations (tertiary and couthers), and the like, and a family atlas of a tree structure is automatically drawn in a 'father-son' connecting line mode; 3. according to the method, the biological genetic characteristics are referenced, and people who do not conform to the biological genetic relationship in the same family, such as people with the same exterior names in the vegetation, the harvest, the holding, the immigration with the mother, the foreign immigration and the like, are automatically marked, so that more comprehensive data variables are provided for the group biological genetic research; 4. in the method, a rapid merging method is provided for people with known relations in different families, and the family relation analysis is respectively carried out upwards and downwards according to known relation points, so that the rapid merging of the families with points and faces is realized; 5. the method carries out multidimensional series connection on population in a specific region range by taking social relation as a link, can quickly analyze the Y chromosome population data with male genetic characteristics, and can be scientifically and effectively used in the fields of criminal investigation solving, ancestor seeking relatives and the like. 6. The method solves the problems of the original pure manual registration, input, groping and hand drawing modes, avoids the uncertainty of human factors, fills the blank of basic data lacking in specifications and standards, realizes accurate and rapid automatic merging and map drawing by unifying standard data analysis and mining, effectively improves the utilization value and the working efficiency of data, effectively utilizes data resources to analyze the data and embodies the data value; 7. by data processing of the method, the data overview of the target area can be clearly obtained, such as: the number of administrative villages, the number of surnames, the number of families, the number of population, the number of males and the like provide data reference for work deployment planning; 8. the method realizes maximum association and combination of data through data merging, and saves a large amount of time, labor, financial resources and other costs for population investigation and registration; by means of multi-dimensional data modeling, the effect of point-to-surface is achieved in the process of map drawing, and the working efficiency of family merging association is improved; 9. the method is full-flow electronic automatic recording, completely avoids the problems of error registration, error association, error combination, wrongly written characters and the like in a manual leading traditional mode, and ensures the accuracy and the effectiveness of data; 10. based on the processing of the method, the working target can be accurately and quickly achieved, the working efficiency is improved by geometric multiples, and the automatic merging and atlas drawing can be completed only in 15-30 minutes on the basis of population data of each million population; 11. the method fully refers to the genetic characteristics of the gene, automatically marks out the population relation individuals which do not meet the genetic characteristics, and provides scientific data basis for the application in the actual field such as public security, judicial expertise and the like.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (3)
1. A method for automatically drawing a family map based on social population familial relationship is characterized by comprising the following steps:
step 1: in a designated area, aggregating the same administrative villages, traversing on the basis of the administrative villages, and declaring as: village list vilagelist;
step 2: traversing a village list villageList, screening through a village main key, acquiring surname information of all people under the current village, and aggregating surnames to declare surname List; meanwhile, family information is generated for each surname, a family naming rule is set as 'administrative division name + surname + family', and each surname automatically corresponds to a family;
and step 3: screening all personnel account information under the current condition by administrative villages and surnames to obtain all account number sets, and declaring the account number sets to be familyNoList;
and 4, step 4: traversing famityNoList, analyzing all personnel relations in the current house number, taking the owner as a starting point, connecting family maps through the relation of exhausted personnel in the method, wherein the exhaust sequence is 1. the owner is- >2. the owner is father- >3. the owner is grandfather- >4. the owner is tertiary- >5. the owner is brother- >6. the owner is brother- >7. the owner is son- > the owner is nephew- >9. the owner is grandson- >10. other relatives- >11. no owner personnel; firstly, traversing to an ancestor through an owner relationship, wherein the ancestor at least comprises a father, a grandfather and a grandfather; secondly, extending to the siblings, wherein the siblings at least comprise brothers and cousin; then exhausting to descendants, wherein the descendants at least comprise children, nephew and grandchildren; finally, processing the personnel without relatives and householders;
and 5: under the default condition, all the householders are merged to a first level in the current family, if the relationship of the householder and the father exists in the current family relationship, the current householder is changed into a second level, the householder and the father are set into the first level, and similarly, if the relationship of the householder and the grandfather exists, the householder and the father are changed into the second level;
step 6: when the family relationship does not have the family main relationship, searching the closest relationship according to the exhaustive sequence to be used as the first level of the family for processing;
and 7: when the relationships of all the persons are exhausted, the relationship between the current person and the family of the descendant is uniformly associated to the family of the father to realize automatic association;
and 8: after all the steps are finished, judging whether personnel which are not merged to the family still exist, if so, automatically associating family information for all the personnel, and using the family information as an independent family to exist;
the step 8 is followed by: based on each subset of aggregation calculation, taking personnel in the minimum set as subjects, calculating item by item through the account number, the relationship with the account, the father information and the information before change/migration, connecting aggregation data of different sizes of family-surname-regions through the relationship of two personnel individuals, and realizing the maximum merging and integration among the sets through exhaustive and recursive analysis;
the same administration village is aggregated in the step 1: aggregating with the minimum administrative unit of village/community, aggregating the specified area range into N village/community sets, wherein each region set comprises N surname sets;
and the surnames in the step 2 are polymerized: an omnibearing data model is established by mining the data relationship of social population to cover the basic information of people, such as surnames, names, alias names, sexes, identity card numbers, ages, places of birth and places of continence; personnel family information, such as family type, family number, family relationship and family register address; parent spouse information such as father name identity card number, mother name identity card number, spouse name identity card number; region address information, such as current address, household address, and birth address; migration change information, such as migration in and out, marital change, last family of the newborn, and family migration; government administration management information, such as home units, jurisdictions, public security, civil administration; analyzing and mining direct and indirect relations between each data variable, performing aggregation calculation on a data main body, finally connecting all relevant data in series by using a family theme, and merging N branches taking a user owner as a unit on the main line to form a family data chain;
the current account number in the step 4 is as follows: the method refers to that in each surname set, the family 'house number' is used for carrying out polymerization again, N family sets are automatically polymerized in each surname set, and each family set comprises independent personnel.
2. The method of claim 1, wherein aggregating the last names in step 2 further comprises: in a village/community set of regional aggregation, the family names are aggregated, groups with the same family names are automatically aggregated into N family sets, and each family set comprises N family sets.
3. The method of claim 2, wherein migrating change information in step 2 further comprises: and (4) migration information aggregation, which is to aggregate the information based on the population migration information, acquire the information before migration change, and aggregate the information with the set after family aggregation again to form a data chain for association.
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| CN112925784B (en) * | 2021-03-29 | 2023-10-10 | 广州市规划和自然资源自动化中心(广州市基础地理信息中心) | Multi-scale spatialization method for real population data |
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Inventor after: Qin Ye Inventor before: Li Zhihua Inventor before: Qin Ye |