CN114003743A - Graph database system based on leveling system, construction method, device and medium - Google Patents
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Abstract
The invention discloses a graph database system based on an leveling system, a construction method, equipment and a medium, wherein the system comprises an information acquisition module, a database and a database, wherein the information acquisition module is used for acquiring background information of a specific group; the background information comprises case information, track information and basic information; the basic information comprises name information, age information, gender information, native place information, relatives information, work unit information and face image information; the character relation extraction module is used for extracting the relation characteristics of the background information and constructing a character relation graph; and the graph database module is used for storing the background information and the character relation graph. The security system staff can obtain corresponding background information and character relation pictures by searching the staff names or pictures, the view angle of case analysis is widened, potential clues are further excavated, potential illegal relatives are found, case handling ideas are conveniently cleared, and case handling efficiency is improved.
Description
Technical Field
The invention relates to the technical field of graph databases, in particular to a graph database system based on an leveling system, a construction method, equipment and a medium.
Background
With the widespread use of internet technology, the scale of data generated by various industries has seen explosive growth. Nowadays, data becomes an important information resource, the field of the peace system is no exception, and the data also has a large amount of valuable knowledge data. The potential value of the data is not effectively utilized because the data lacks a good correlation form and a friendly and intuitive visualization is displayed to the user, thereby blocking further mining and application of the data. At present, familial crimes cannot draw enough attention of related departments, the knowledge data of the leveling system covers a large amount of personnel information, and mining and analyzing the personnel relationship information based on the knowledge data of the leveling system is urgent.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a graph database system based on an leveling system, a construction method, equipment and a medium, which are used for mining the character relationship of a specific person based on a leveling system knowledge graph.
First aspect
The invention provides a graph database system based on an leveling system, which comprises:
the information acquisition module is used for acquiring background information of a specific group; the background information comprises case information, track information and basic information; the basic information comprises name information, age information, gender information, native place information, relatives information, work unit information and face image information;
the figure relation extraction module is used for extracting the relation characteristics of the background information and constructing a figure relation graph;
and the graph database module is used for storing the background information and the character relation graph.
Preferably, the system further comprises an updating module for completing the updating of the database module when the context information of the specific group changes.
Preferably, the system further comprises a retrieval module; the retrieval module comprises a first retrieval unit;
the first retrieval unit is to:
acquiring a picture to be processed;
comparing the picture with face image information stored in a graph database module, calculating a similarity value, and sequencing the similarity values from large to small;
outputting the similarity value of N before ranking, corresponding face image information and a corresponding character relation graph; wherein N is a natural number.
Preferably, comparing the picture with the face image information stored in the graph database module specifically comprises:
preprocessing the picture;
carrying out gray level processing on the preprocessed picture to obtain a gray level picture;
extracting the characteristics of the gray level picture to obtain characteristic information;
and comparing the characteristic information with the face image information stored in the graph database module.
Preferably, the retrieval module further comprises a second retrieval unit;
the second retrieval unit is to:
acquiring names of a plurality of persons;
performing word segmentation processing on the names of the plurality of people;
carrying out fragment retrieval in a graph database;
and outputting the background information of the plurality of people and the corresponding character relation graph.
Preferably, the system further comprises a display module for displaying the output results of the first retrieval unit and the second retrieval unit in a form of a graph.
Second aspect of the invention
The invention provides a construction method of a graph database system based on an leveling system, which comprises the following steps:
acquiring background information of a specific group; the background information comprises case information, track information and basic information; the basic information comprises name information, age information, gender information, native place information, relatives information, work unit information and face image information; the relative information is obtained through a social network;
extracting the relation characteristics of the background information to construct a character relation graph;
and storing the background information and the character relation graph into a graph database.
Third aspect of the invention
The invention provides a construction device of a graph database system based on an leveling system, which comprises a memory and a processor, wherein the memory is used for storing a graph database; the memory is used for storing executable program codes;
the processor is configured to read the executable program code stored in the memory to execute the method for constructing a leveling system based graph database system according to the second aspect.
Fourth aspect of the invention
The present invention provides a storage medium storing the executable program code of the third aspect.
The invention has the beneficial effects that:
the background information of the specific crowd can be obtained, and the corresponding character relation graph is deduced through the character relation extraction module. The security system staff can obtain corresponding background information and character relation pictures by searching the staff names or pictures, the view angle of case analysis is widened, potential clues are further excavated, potential illegal relatives are found, case handling ideas are conveniently cleared, and case handling efficiency is improved.
Drawings
In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
FIG. 1 is a block diagram of a first embodiment of the present invention;
FIG. 2 is a schematic flow chart of a second embodiment of the present invention;
fig. 3 is a hardware architecture diagram of a fifth embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and therefore are only examples, and the protection scope of the present invention is not limited thereby.
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
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 some, not all, embodiments of the present invention. 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.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Example one
The embodiment of the invention provides a graph database system based on an leveling system, as shown in fig. 1, comprising:
the information acquisition module is used for acquiring background information of a specific group; wherein, the background information comprises case information, track information and basic information; the basic information comprises name information, age information, gender information, native place information, relatives information, work unit information and face image information;
the character relation extraction module is used for extracting the relation characteristics of the background information and constructing a character relation graph;
the graph database module is used for storing background information and a character relation graph;
and the updating module is used for finishing updating the database module when the background information of the specific group changes.
The background information can be obtained through intranet data and internet data of the safety system. The safety system intranet data comprise text data such as case writing records, personnel travel tracks, vehicle tracks, hotel accommodations, case information, civil aviation, railways, traffic management, civil administration information and the like. The internet data comprises a search platform and information of a short message, a WeChat, a QQ and other network social platform.
The character relation extraction module comprises a knowledge extraction module and a knowledge fusion module. And the knowledge extraction module is used for extracting entities, attributes and relationships from the mass multi-source heterogeneous data. For example, in a news report, "10 am, 25 year old plum ladies have a rear-end collision accident with 47 year old mr. on the XX road, the specific information is XXX, and casualties are not happened fortunately". In the direct information provided by the unstructured text, the mutual relationship of two entity people, namely 'li ms' and 'mr' and 'automobile rear-end collision' can be extracted. If further association is carried out, the entity vehicles of the two vehicles and the association relationship between the vehicle and the entity people-vehicle owner can be extracted. Of course, attribute information describing characteristics of the physical person may be extracted for "age 25" and "age 47". In the embodiment of the invention, the knowledge extraction module can accurately identify the name of a person, the name of a place, the name of an organization, the identity card number, the mobile phone number and the like by utilizing an NLP algorithm of entity identification and combining machine learning and a rule engine. The knowledge fusion module is used for integrating the entities, the attributes and the relationships extracted by the knowledge extraction module, and has the functions of entity disambiguation, coreference resolution, entity alignment, entity attribute value judgment and the like. Where entity disambiguation refers to the fact that the same vocabulary may represent different entities, it is necessary to infer from context which word represents which entity based on semantics. For example, two persons named Zhang III can be distinguished according to their application certificates or age attributes. Coreference resolution refers to which object is referred by the same pronoun, and can also be inferred through context semantics. Entity alignment refers to how different descriptions of the same entity are directed to the same entity, such as mapping "the monkey King" and "the monkey King" to "the monkey King"; the attribute value judgment of the entity refers to attribute description difference obtained by the same entity from a plurality of sources, and is determined by the confidence degree of a knowledge source.
In the embodiment of the invention, the bottom layer of the graph database module adopts an optimized mixed storage technology integrating Hbase, elastic search and Phoenix secondary indexes, and the storage layer and the calculation layer are designed by using a distributed architecture, so that the lateral expansibility of the graph database module is improved, the storage and calculation performance of the system can be easily improved by adding nodes, and the graph database module can be updated rapidly.
In the embodiment of the invention, the staff of the peace system acquires the background information of a specific crowd and deduces a corresponding character relation graph through a character relation extraction module. Through the analysis of the human-object relationship graph, the view angle of case analysis can be widened, potential clues are further mined, and potential illegal relationship persons are found.
The embodiment of the invention also comprises a retrieval module; the retrieval module comprises a first retrieval unit;
the first retrieval unit is configured to:
acquiring a picture to be processed;
comparing the image with the face image information stored in the graph database module, calculating a similarity value, and sequencing the similarity values from large to small;
outputting the similarity value of N before ranking, corresponding face image information and a corresponding character relation graph; wherein N is a natural number.
The comparison between the image and the face image information stored in the graph database module specifically comprises the following steps:
preprocessing the picture;
carrying out gray level processing on the preprocessed picture to obtain a gray level picture;
extracting the characteristics of the gray level picture to obtain characteristic information;
and comparing the characteristic information with the face image information stored in the database module.
In the embodiment of the invention, the similarity value 10 before the ranking, the corresponding face image information and the corresponding character relation graph are output, manual analysis and comparison are carried out, and finally, the target is locked to avoid omission; and the similarity value is an average value calculated for many times, so that the accuracy is improved. In other embodiments, a threshold value may be preset, and when the similarity value is greater than the threshold value, the corresponding face image information is stored in the suspected target library, and then the information stored in the suspected target library is manually analyzed and compared, so as to finally lock the target.
The retrieval module further comprises a second retrieval unit;
the second retrieval unit is configured to:
acquiring names of a plurality of persons;
performing word segmentation processing on names of a plurality of persons;
carrying out fragment retrieval in a graph database;
and outputting background information of a plurality of persons and corresponding person relation graphs.
The name of the person to be searched is obtained through the second searching unit, the background information and the character relation graph are visually displayed in front of the user, the case handling thought is conveniently cleared, and the case handling efficiency is improved.
The embodiment of the invention also comprises a display module which is used for displaying the output results of the first retrieval unit and the second retrieval unit in a chart form.
Example two
The embodiment of the invention provides a method for constructing a graph database system based on an leveling system, which comprises the following steps as shown in figure 2:
acquiring background information of a specific group; the background information comprises case information, track information and basic information; the basic information comprises name information, age information, gender information, native place information, relatives information, work unit information and face image information;
extracting the relation characteristics of the background information to construct a character relation graph;
storing the background information and the character relation graph into a graph database.
The graph database is updated when the context information of a particular population changes.
The background information can be obtained through intranet data and internet data of the safety system. The safety system intranet data comprise text data such as case writing records, personnel travel tracks, vehicle tracks, hotel accommodations, case information, civil aviation, railways, traffic management, civil administration information and the like. The internet data comprises a search platform and information of a short message, a WeChat, a QQ and other network social platform. The character relation extraction module comprises a knowledge extraction module and a knowledge fusion module. And the knowledge extraction module is used for extracting entities, attributes and relationships from the mass multi-source heterogeneous data. The character relation extraction module comprises a knowledge extraction module and a knowledge fusion module. And the knowledge extraction module is used for extracting entities, attributes and relationships from the mass multi-source heterogeneous data. The database bottom layer adopts an optimized mixed storage technology integrating Hbase, elastic search and Phoenix secondary indexes, a storage layer and a calculation layer are designed by using a distributed architecture, the lateral expansibility of the database is improved, the storage and calculation performance of the system can be easily improved by adding nodes, and the database module can be conveniently and rapidly updated.
EXAMPLE III
The embodiment of the invention provides a retrieval method of a graph database system based on an leveling system, which comprises the following steps:
acquiring a picture to be processed;
comparing the image with the face image information stored in the graph database module, calculating a similarity value, and sequencing the similarity values from large to small;
outputting the similarity value of N before ranking, corresponding face image information and a corresponding character relation graph; wherein N is a natural number.
The comparison between the image and the face image information stored in the graph database module specifically comprises the following steps:
preprocessing the picture;
carrying out gray level processing on the preprocessed picture to obtain a gray level picture;
extracting the characteristics of the gray level picture to obtain characteristic information;
and comparing the characteristic information with the face image information stored in the database module.
In the embodiment of the invention, the similarity value 10 before the ranking, the corresponding face image information and the corresponding character relation graph are output, manual analysis and comparison are carried out, and finally, the target is locked to avoid omission; and the similarity value is an average value calculated for many times, so that the accuracy is improved. In other embodiments, a threshold value may be preset, and when the similarity value is greater than the threshold value, the corresponding face image information is stored in the suspected target library, and then the information stored in the suspected target library is manually analyzed and compared, so as to finally lock the target.
Example four
The embodiment of the invention provides a retrieval method of a graph database system based on an leveling system, which comprises the following steps:
acquiring names of a plurality of persons;
performing word segmentation processing on names of a plurality of persons;
carrying out fragment retrieval in a graph database;
and outputting background information of a plurality of persons and corresponding person relation graphs.
The name of the person to be searched is obtained through the second searching unit, the background information and the character relation graph are visually displayed in front of the user, the case handling thought is conveniently cleared, and the case handling efficiency is improved.
EXAMPLE five
The embodiment of the invention provides construction equipment of a graph database system based on a leveling system, and FIG. 3 is a hardware architecture diagram of the construction equipment of the graph database system based on the leveling system, which comprises input equipment, an input interface, a central processing unit, a memory, an output interface and output equipment. The input interface, the central processing unit, the memory and the output interface are mutually connected through a bus, and the input equipment and the output equipment are respectively connected with the bus through the input interface and the output interface and further connected with other components of the equipment. Specifically, the input device receives input information from the outside and transmits the input information to the central processor through the input interface. The central processor processes the input information based on computer executable program code stored in the memory to generate output information, temporarily or permanently stores the output information in the memory, and then transmits the output information through the output interface to an output device, which outputs the output information outside of the device for use by a user.
EXAMPLE six
An embodiment of the present invention provides a storage medium storing the above executable program code. The executable program code, when executed by a processor, implements the method of constructing a graph database system based on a leveling system as described above. In this embodiment, the storage medium may be any available medium that can be read by a computer or a data storage device such as a server, a data center, or the like, that is integrated with one or more available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk SSD). Further, the computer readable storage medium may also include both an internal storage unit and an external storage device of the system. The computer-readable storage medium is used for storing a computer program and other programs and data required by the system. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The embodiment of the invention provides a graph database system based on an peace system, a construction method, equipment and a medium, which can acquire background information of a specific crowd and deduce a corresponding character relation graph through a character relation extraction module. The security system staff can obtain corresponding background information and character relation pictures by searching the staff names or pictures, the view angle of case analysis is widened, potential clues are further excavated, potential illegal relatives are found, case handling ideas are conveniently cleared, and case handling efficiency is improved.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (9)
1. A graph database system based on an leveling system, comprising:
the information acquisition module is used for acquiring background information of a specific group; the background information comprises case information, track information and basic information; the basic information comprises name information, age information, gender information, native place information, relatives information, work unit information and face image information;
the figure relation extraction module is used for extracting the relation characteristics of the background information and constructing a figure relation graph;
and the graph database module is used for storing the background information and the character relation graph.
2. The leveling system based database system of claim 1, further comprising an update module configured to complete updating of the database module when the context information of the specific group changes.
3. The leveling system based graph database system of claim 1, further comprising a retrieval module; the retrieval module comprises a first retrieval unit;
the first retrieval unit is to:
acquiring a picture to be processed;
comparing the picture with face image information stored in a graph database module, calculating a similarity value, and sequencing the similarity values from large to small;
outputting the similarity value of N before ranking, corresponding face image information and a corresponding character relation graph; wherein N is a natural number.
4. The system according to claim 3, wherein comparing the image with the face image information stored in the image database module specifically comprises:
preprocessing the picture;
carrying out gray level processing on the preprocessed picture to obtain a gray level picture;
extracting the characteristics of the gray level picture to obtain characteristic information;
and comparing the characteristic information with the face image information stored in the graph database module.
5. The leveling system based graph database system of claim 3, wherein the retrieval module further comprises a second retrieval unit;
the second retrieval unit is to:
acquiring names of a plurality of persons;
performing word segmentation processing on the names of the plurality of people;
carrying out fragment retrieval in a graph database;
and outputting the background information of the plurality of people and the corresponding character relation graph.
6. The leveling system based graph database system of claim 5, further comprising a display module for displaying the output results of the first and second search units in the form of a graph.
7. A method for constructing a graph database system based on an leveling system is characterized by comprising the following steps:
acquiring background information of a specific group; the background information comprises case information, track information and basic information; the basic information comprises name information, age information, gender information, native place information, relatives information, work unit information and face image information; the relative information is obtained through a social network;
extracting the relation characteristics of the background information to construct a character relation graph;
and storing the background information and the character relation graph into a graph database.
8. A construction device of a graph database system based on an leveling system is characterized by comprising a memory and a processor; the memory is used for storing executable program codes;
the processor is configured to read executable program code stored in the memory to perform the method of constructing a leveling system based graph database system as claimed in claim 7.
9. A storage medium characterized in that it stores the executable program code of claim 8.
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| CN106909539A (en) * | 2015-12-22 | 2017-06-30 | 成都理想境界科技有限公司 | Image indexing system, server, database and related methods |
| CN112330331A (en) * | 2020-11-19 | 2021-02-05 | 平安普惠企业管理有限公司 | Identity verification method, device and equipment based on face recognition and storage medium |
| CN112380297A (en) * | 2020-12-02 | 2021-02-19 | 福建天创信息科技有限公司 | Method and terminal for generating relation map |
| KR102228873B1 (en) * | 2019-12-27 | 2021-03-17 | (주)아이와즈 | Construction system of criminal suspect knowledge network using public security information and Method thereof |
| CN112597238A (en) * | 2020-12-17 | 2021-04-02 | 北京以萨技术股份有限公司 | Method, system, device and medium for establishing knowledge graph based on personnel information |
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- 2021-07-30 CN CN202110874885.8A patent/CN114003743A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106909539A (en) * | 2015-12-22 | 2017-06-30 | 成都理想境界科技有限公司 | Image indexing system, server, database and related methods |
| KR102228873B1 (en) * | 2019-12-27 | 2021-03-17 | (주)아이와즈 | Construction system of criminal suspect knowledge network using public security information and Method thereof |
| CN112330331A (en) * | 2020-11-19 | 2021-02-05 | 平安普惠企业管理有限公司 | Identity verification method, device and equipment based on face recognition and storage medium |
| CN112380297A (en) * | 2020-12-02 | 2021-02-19 | 福建天创信息科技有限公司 | Method and terminal for generating relation map |
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