CN112632195A - Big data based concept graph display method, device, equipment and medium - Google Patents
Big data based concept graph display method, device, equipment and medium Download PDFInfo
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Abstract
The invention relates to big data technology, and discloses a big data-based concept graph display method, which comprises the following steps: acquiring service data from a big data platform, and integrating the service data to obtain standard service data; performing structural analysis on the standard service data, and determining a data description scheme of the standard service data according to an analysis result; constructing a big data conceptual diagram corresponding to the standard business data according to the data description scheme; and establishing a data analysis model according to the user requirements based on the big data conceptual diagram. The invention also relates to a block chain technology, and the service data can be stored in the block chain. The invention can realize the purpose of describing and displaying the big data.
Description
Technical Field
The invention relates to the field of big data, in particular to a method and a device for displaying a concept graph based on big data, electronic equipment and a computer-readable storage medium.
Background
Conventional databases typically use E-R graphs to describe and present the data, and for further analysis and mining. However, in the big data era, big data is large in scale and complex in data structure, wherein an entity contains more data attributes than traditional data, and the complex content of the big data cannot be displayed by using an E-R diagram and the expansion of the big data in subsequent modeling is not facilitated, so that a new method for describing and displaying the big data is needed.
Disclosure of Invention
The invention provides a method and a device for displaying a conceptual diagram based on big data, electronic equipment and a computer-readable storage medium, and mainly aims to describe and display the big data.
In order to achieve the above object, the present invention provides a method for displaying a conceptual diagram based on big data, comprising:
acquiring service data from a big data platform, and integrating the service data to obtain standard service data;
performing structural analysis on the standard service data, and determining a data description scheme of the standard service data according to an analysis result;
constructing a big data conceptual diagram corresponding to the standard business data according to the data description scheme;
and establishing a data analysis model according to the user requirements based on the big data conceptual diagram.
Optionally, the integrating the service data to obtain standard service data includes:
extracting data characteristics of each data in the service data;
clustering data containing similar data characteristics by using a clustering algorithm;
and carrying out normalization processing on the service data after clustering processing to obtain the standard service data.
Optionally, the performing structural analysis on the standard service data includes:
extracting a service object in the standard service data as an entity;
abstracting the entity into an abstract entity according to the theme relationship, and determining the attribute of the abstract entity;
and determining the incidence relation between the abstract entities, and summarizing the abstract entities into a summary entity to obtain the analysis result of the standard service data.
Optionally, the constructing a big data conceptual diagram corresponding to the standard service data according to the data description scheme includes:
determining corresponding diagram identifiers for elements included in the data description scheme one by one;
and displaying the standard business data in a graph according to the graph identification, and performing optimization processing to obtain a big data conceptual diagram corresponding to the standard business data.
Optionally, the establishing a data analysis model according to a user requirement based on the big data conceptual diagram includes:
acquiring user requirements;
acquiring associated service data related to the user requirements in the standard service data according to the big data conceptual diagram;
and establishing a corresponding data analysis model according to the associated service data.
In order to solve the above problems, the present invention further provides a conceptual diagram display apparatus based on big data, the apparatus comprising:
the data integration processing module is used for acquiring service data from a big data platform and integrating the service data to obtain standard service data;
the data structure analysis module is used for carrying out structural analysis on the standard business data and determining a data description scheme of the standard business data according to an analysis result;
the big data conceptual diagram building module is used for building a big data conceptual diagram corresponding to the standard business data according to the data description scheme;
and the analysis model establishing module is used for establishing a data analysis model according to the user requirements based on the big data conceptual diagram.
Optionally, when the service data is integrated to obtain standard service data, the data integration processing module executes the following operations:
extracting data characteristics of each data in the service data;
clustering data containing similar data characteristics by using a clustering algorithm;
and carrying out normalization processing on the service data after clustering processing to obtain the standard service data.
Optionally, when performing the structural analysis on the standard business data, the data structure analysis module performs the following operations:
extracting a service object in the standard service data as an entity;
abstracting the entity into an abstract entity according to the theme relationship, and determining the attribute of the abstract entity;
and determining the incidence relation between the abstract entities, and summarizing the abstract entities into a summary entity to obtain the analysis result of the standard service data.
In order to solve the above problem, the present invention also provides an electronic device, including:
a memory storing at least one instruction; and
and the processor executes the instructions stored in the memory to realize the big data-based conceptual diagram showing method.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, which includes a storage data area and a storage program area, wherein the storage data area stores data created according to the use of the blockchain node, and the storage program area stores a computer program, and when the computer program is executed by a processor, the method for displaying a conceptual diagram based on big data according to any one of the above aspects is implemented.
The embodiment of the invention obtains the service data from the big data platform, integrates the service data to obtain the standard service data, can enhance the service characteristics of the service data, and is beneficial to analyzing the service data subsequently; performing structural analysis on the standard service data, and determining a data description scheme of the standard service data according to an analysis result, so that the data can be conveniently displayed subsequently, and the efficiency is improved; constructing a big data conceptual diagram corresponding to the standard business data according to the data description scheme, and displaying the data and the data association in the standard business data more clearly and intuitively in a graphic mode; and establishing a data analysis model according to user requirements based on the big data conceptual diagram, so that the business data can be further mined and analyzed. Therefore, the method, the device and the computer-readable storage medium for displaying the conceptual diagram based on the big data can achieve the purpose of describing and displaying the big data.
Drawings
Fig. 1 is a schematic flow chart of a big data-based conceptual diagram display method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a big data structure analysis method according to an embodiment of the present invention;
FIG. 3 is a block diagram of a big data based concept graph display apparatus according to an embodiment of the present invention;
fig. 4 is a schematic internal structural diagram of an electronic device implementing a big data-based conceptual diagram presentation method according to an embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a conceptual diagram display method based on big data. The big data is data with huge scale, and has four characteristics of massive data scale, rapid data circulation, various data types and low value density. The operations of obtaining, storing, managing, analyzing and the like of the big data exceed the range of the processing capacity of the traditional database, so that the big data needs to be further analyzed and the structure needs to be carded.
The execution subject of the big data-based conceptual diagram presentation method provided by the embodiment of the present application includes, but is not limited to, at least one of electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the big data-based conceptual diagram presentation method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a block chain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Fig. 1 is a schematic flow chart of a conceptual diagram showing method based on big data according to an embodiment of the present invention.
In this embodiment, the method for displaying a conceptual diagram based on big data includes:
and S1, acquiring the service data from the big data platform, and integrating the service data to obtain standard service data.
In the embodiment of the invention, the service data can be various service record data generated by the service operation of mass users in a big data platform. For example, the service data obtained from the database of an online shopping platform includes massive user data, massive commodity data, and massive user purchase records. The acquisition of business data from large data platforms is growing and updating. It is emphasized that, the size of the service data acquired in the big data platform is large, and the embodiment of the present invention may efficiently acquire the service data by using the high throughput of the block chain.
Therefore, the embodiment of the invention acquires the business data from the big data platform by using the python statement with the data grabbing function.
Specifically, in the embodiment of the present invention, the integrating the service data to obtain standard service data includes:
extracting data characteristics of each data in the service data;
clustering data containing similar data characteristics by using a clustering algorithm;
and carrying out normalization processing on the service data after clustering processing to obtain the standard service data.
The clustering algorithm can be a K-mean algorithm, the normalization processing can be realized by a z-score algorithm, and the normalization processing can enhance the service characteristics of the service data and is beneficial to analyzing the structure of the service data subsequently.
Preferably, the traditional data is structured and relational data, and the data scale is small, whereas the service data acquired from the big data platform in the embodiment of the present invention includes not only structured and relational data, but also unstructured data such as images, sounds, files, and the like, and the data scale is large, so that the service data needs to be integrated to acquire the service features of the unstructured data, which is convenient for performing a uniform analysis on the service data subsequently, and saves computer resources.
And S2, performing structural analysis on the standard business data, and determining a data description scheme of the standard business data according to an analysis result.
Further, referring to fig. 2, the performing of the structural analysis on the standard service data includes:
s21, extracting the business object in the standard business data as an entity, for example, in the user shopping analysis business, the commodity is an entity, and the user is an entity;
s22, abstracting the entity into abstract entity according to the theme relationship, and determining the attribute of the abstract entity, wherein the attribute comprises entity attribute, unstructured attribute, dimension attribute and the like;
specifically, the subject relation refers to a preset type of business process related in the standard business data, such as adding a shopping cart, immediately purchasing, submitting an order, and the like; in the user shopping analysis service, the shopping cart can be an abstract entity, and the order record can be an abstract entity.
In detail, the entity attributes are used to describe the structural features that the abstract entity has, including, but not limited to: name of the goods, name of the user, etc.; the unstructured properties are used to describe unstructured features that the abstract entity has, including, but not limited to: commodity pictures, commodity recommendation videos, and the like; the dimension attributes are used to describe the abstract entity from different dimensions, including, but not limited to: time dimension, area dimension, etc. For example, the order record generated by a certain user within 3 months may be a dimension attribute, and the order records generated by all users within a certain cell may be a dimension attribute.
And S23, determining the incidence relation between the abstract entities, and summarizing the abstract entities into a summary entity to obtain the analysis result of the standard service data.
Specifically, the association relationship refers to the business relationship existing between the abstract entities, and generally keeps consistent with the subject relationship, for example, the association relationship between the shopping cart and the order record is the order submission.
In detail, after the standard service data is analyzed, a data description scheme of the standard service data can be obtained. The description scheme comprises elements such as an entity, an abstract entity, attributes, an association relation and a summary entity, and the data description scheme is a scheme for describing the standard business data based on the result of analyzing the standard business data.
And S3, constructing a big data conceptual diagram corresponding to the standard business data according to the data description scheme.
Preferably, in the embodiment of the present invention, the big data conceptual diagram indicates that the standard business data is displayed in a graphic manner according to the data description scheme, so that data and data association in the standard business data can be displayed more clearly and intuitively.
In detail, the constructing a big data conceptual diagram corresponding to the standard business data according to the data description scheme includes:
determining corresponding diagram identifiers for elements included in the data description scheme, such as entities, abstract entities and the like; and
and displaying the standard business data in a graph according to the graph identification, and performing optimization processing to obtain a big data conceptual diagram corresponding to the standard business data. For example, entities in the data description scheme are represented using a blank rectangle diagram; representing abstract entities in the data description scheme by using pictorial identification of a blank parallelogram; representing the entity attribute in the data description scheme by using an oval diagram identification; representing the unstructured attributes in the data description scheme by using a pictorial identification of a shaded ellipse; representing the dimension attribute in the data description scheme by using a diagram identification of a double-line frame ellipse; connecting the attributes with corresponding abstract entities by using solid line segments; representing the type of the incidence relation in the data description scheme by using a diamond-shaped graphical identification, and connecting the abstract entity with the incidence relation with the type of the incidence relation by using a solid line segment; and representing the summary entity in the data description scheme by using a graphical identification of a double-line frame parallelogram.
Preferably, the optimization process comprises: and integrating the same graphic representation identification in the standard service data, and adjusting the position of the graphic representation identification corresponding to the standard service data to make the graphic representation display of the standard service data more clear.
Preferably, in the embodiment of the present invention, the big data conceptual diagram shows the standard business data in an illustration manner, so that the standard business data can be shown in a theme form, a data structure of the standard business data can be clearly shown, further data mining and value analysis can be performed on the standard business data, and subsequent big data modeling and later expansion are facilitated.
And S4, establishing a data analysis model according to the user requirements based on the big data conceptual diagram.
In detail, the establishing of the data analysis model according to the user requirement based on the big data conceptual diagram comprises:
acquiring user requirements such as commodity price adjustment, optimal combination of commodities and the like;
acquiring relevant business data related to the user requirements in the standard business data, such as sales records of commodities, browsing records of commodities and the like, according to the big data conceptual diagram;
and establishing a corresponding data analysis model according to the associated service data. The data analysis model can be a commodity price sensitivity model, a sales prediction model, a commodity associated sales model, an abnormal order detection model and the like.
In detail, the data analysis model can solve the problems proposed in the actual demands, for example, a commodity-associated sales model can find another commodity combined with a certain commodity, and the two commodities are bundled together for sale, so that the sales volume of the two commodities can be increased.
The embodiment of the invention obtains the service data from the big data platform, integrates the service data to obtain the standard service data, can enhance the service characteristics of the service data, and is beneficial to analyzing the service data subsequently; performing structural analysis on the standard service data, and determining a data description scheme of the standard service data according to an analysis result, so that the data can be conveniently displayed subsequently, and the efficiency is improved; constructing a big data conceptual diagram corresponding to the standard business data according to the data description scheme, and displaying the data and the data association in the standard business data more clearly and intuitively in a graphic mode; and establishing a data analysis model according to user requirements based on the big data conceptual diagram, so that the business data can be further mined and analyzed. Therefore, the method, the device and the computer-readable storage medium for displaying the conceptual diagram based on the big data can achieve the purpose of describing and displaying the big data.
Fig. 3 is a functional block diagram of the big data-based conceptual diagram demonstration apparatus according to the present invention.
The big data based concept graph presentation apparatus 100 according to the present invention may be installed in an electronic device. According to the realized functions, the big data-based concept graph presentation device can comprise a data integration processing module 101, a data structure analysis module 102, a big data concept graph construction module 103 and an analysis model building module 104. A module according to the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the data integration processing module 101 is configured to acquire service data from a big data platform, and integrate the service data to obtain standard service data;
the data structure analysis module 102 is configured to perform structure analysis on the standard service data, and determine a data description scheme of the standard service data according to an analysis result;
the big data conceptual diagram constructing module 103 is configured to construct a big data conceptual diagram corresponding to the standard business data according to the data description scheme;
the analysis model establishing module 104 is configured to establish a data analysis model according to a user requirement based on the big data conceptual diagram.
In detail, the specific implementation steps of each module of the big data-based conceptual diagram display device are as follows:
the data integration processing module 101 is configured to acquire service data from a big data platform, and integrate the service data to obtain standard service data.
In the embodiment of the invention, the service data can be various service record data generated by the service operation of mass users in a big data platform. For example, the service data obtained from the database of an online shopping platform includes massive user data, massive commodity data, and massive user purchase records. The acquisition of business data from large data platforms is growing and updating. It is emphasized that, the size of the service data acquired in the big data platform is large, and the embodiment of the present invention may efficiently acquire the service data by using the high throughput of the block chain.
Therefore, the embodiment of the invention acquires the business data from the big data platform by using the python statement with the data grabbing function.
Specifically, in the embodiment of the present invention, the integrating the service data to obtain standard service data includes:
extracting data characteristics of each data in the service data;
clustering data containing similar data characteristics by using a clustering algorithm;
and carrying out normalization processing on the service data after clustering processing to obtain the standard service data.
The clustering algorithm can be a K-mean algorithm, the normalization processing can be realized by a z-score algorithm, and the normalization processing can enhance the service characteristics of the service data and is beneficial to analyzing the structure of the service data subsequently.
Preferably, the traditional data is structured and relational data, and the data scale is small, whereas the service data acquired from the big data platform in the embodiment of the present invention includes not only structured and relational data, but also unstructured data such as images, sounds, files, and the like, and the data scale is large, so that the service data needs to be integrated to acquire the service features of the unstructured data, which is convenient for performing a uniform analysis on the service data subsequently, and saves computer resources.
The data structure analysis module 102 is configured to perform structure analysis on the standard service data, and determine a data description scheme of the standard service data according to an analysis result.
Further, the performing structural analysis on the standard service data includes:
extracting the service object in the standard service data as an entity, for example, in a user shopping analysis service, a commodity is an entity, and a user is an entity;
abstracting the entity into an abstract entity according to a theme relationship, and determining the attribute of the abstract entity, wherein the attribute comprises an entity attribute, an unstructured attribute, a dimension attribute and the like;
specifically, the subject relation refers to a preset type of business process related in the standard business data, such as adding a shopping cart, immediately purchasing, submitting an order, and the like; in the user shopping analysis service, the shopping cart can be an abstract entity, and the order record can be an abstract entity.
In detail, the entity attributes are used to describe the structural features that the abstract entity has, including, but not limited to: name of the goods, name of the user, etc.; the unstructured properties are used to describe unstructured features that the abstract entity has, including, but not limited to: commodity pictures, commodity recommendation videos, and the like; the dimension attributes are used to describe the abstract entity from different dimensions, including, but not limited to: time dimension, area dimension, etc. For example, the order record generated by a certain user within 3 months may be a dimension attribute, and the order records generated by all users within a certain cell may be a dimension attribute.
And determining the incidence relation between the abstract entities, and summarizing the abstract entities into a summary entity to obtain the analysis result of the standard service data.
Specifically, the association relationship refers to the business relationship existing between the abstract entities, and generally keeps consistent with the subject relationship, for example, the association relationship between the shopping cart and the order record is the order submission.
In detail, after the standard service data is analyzed, a data description scheme of the standard service data can be obtained. The description scheme comprises elements such as an entity, an abstract entity, attributes, an association relation and a summary entity, and the data description scheme is a scheme for describing the standard business data based on the result of analyzing the standard business data.
The big data conceptual diagram constructing module 103 is configured to construct a big data conceptual diagram corresponding to the standard business data according to the data description scheme.
Preferably, in the embodiment of the present invention, the big data conceptual diagram indicates that the standard business data is displayed in a graphic manner according to the data description scheme, so that data and data association in the standard business data can be displayed more clearly and intuitively.
In detail, the constructing a big data conceptual diagram corresponding to the standard business data according to the data description scheme includes:
determining corresponding diagram identifiers for elements included in the data description scheme, such as entities, abstract entities and the like; and
and displaying the standard business data in a graph according to the graph identification, and performing optimization processing to obtain a big data conceptual diagram corresponding to the standard business data.
For example, entities in the data description scheme are represented using a blank rectangle diagram; representing abstract entities in the data description scheme by using pictorial identification of a blank parallelogram; representing the entity attribute in the data description scheme by using an oval diagram identification; representing the unstructured attributes in the data description scheme by using a pictorial identification of a shaded ellipse; representing the dimension attribute in the data description scheme by using a diagram identification of a double-line frame ellipse; connecting the attributes with corresponding abstract entities by using solid line segments; representing the type of the incidence relation in the data description scheme by using a diamond-shaped graphical identification, and connecting the abstract entity with the incidence relation with the type of the incidence relation by using a solid line segment; and representing the summary entity in the data description scheme by using a graphical identification of a double-line frame parallelogram.
Preferably, the optimization process comprises: and integrating the same graphic representation identification in the standard service data, and adjusting the position of the graphic representation identification corresponding to the standard service data to make the graphic representation display of the standard service data more clear.
Preferably, in the embodiment of the present invention, the big data conceptual diagram shows the standard business data in an illustration manner, so that the standard business data can be shown in a theme form, a data structure of the standard business data can be clearly shown, further data mining and value analysis can be performed on the standard business data, and subsequent big data modeling and later expansion are facilitated.
The analysis model establishing module 104 is configured to establish a data analysis model according to a user requirement based on the big data conceptual diagram.
In detail, the establishing of the data analysis model according to the user requirement based on the big data conceptual diagram comprises:
acquiring user requirements such as commodity price adjustment, optimal combination of commodities and the like;
acquiring relevant business data related to the user requirements in the standard business data, such as sales records of commodities, browsing records of commodities and the like, according to the big data conceptual diagram;
and establishing a corresponding data analysis model according to the associated service data. The data analysis model can be a commodity price sensitivity model, a sales prediction model, a commodity associated sales model, an abnormal order detection model and the like.
In detail, the data analysis model can solve the problems proposed in the actual demands, for example, a commodity-associated sales model can find another commodity combined with a certain commodity, and the two commodities are bundled together for sale, so that the sales volume of the two commodities can be increased.
Fig. 4 is a schematic structural diagram of an electronic device implementing a concept diagram presentation method based on big data according to the present invention.
The electronic device 1 may include a processor 10, a memory 11 and a bus, and may further include a computer program stored in the memory 11 and executable on the processor 10, such as a big data-based conceptual diagram presentation program 12.
The memory 11 includes at least one type of readable storage medium, which includes flash memory, removable hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only to store application software installed in the electronic device 1 and various types of data, such as code of the conceptual diagram showing program 12 based on big data, but also to temporarily store data that has been output or will be output.
The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device 1 by running or executing programs or modules stored in the memory 11 (for example, executing a conceptual diagram presentation program based on big data, etc.) and calling data stored in the memory 11.
The bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
Fig. 4 only shows an electronic device with components, and it will be understood by those skilled in the art that the structure shown in fig. 4 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device 1 may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so as to implement functions of charge management, discharge management, power consumption management, and the like through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device 1 may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
Further, the electronic device 1 may further include a network interface, and optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a bluetooth interface, etc.), which are generally used for establishing a communication connection between the electronic device 1 and other electronic devices.
Optionally, the electronic device 1 may further comprise a user interface, which may be a Display (Display), an input unit (such as a Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the electronic device 1 and for displaying a visualized user interface, among other things.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The memory 11 in the electronic device 1 stores a big data-based conceptual diagram showing program 12 which is a combination of a plurality of instructions, and when running in the processor 10, can realize:
acquiring service data from a big data platform, and integrating the service data to obtain standard service data;
performing structural analysis on the standard service data, and determining a data description scheme of the standard service data according to an analysis result;
constructing a big data conceptual diagram corresponding to the standard business data according to the data description scheme;
and establishing a data analysis model according to the user requirements based on the big data conceptual diagram.
Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. The computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any accompanying claims should not be construed as limiting the claim concerned.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A big data-based concept graph display method is characterized by comprising the following steps:
acquiring service data from a big data platform, and integrating the service data to obtain standard service data;
performing structural analysis on the standard service data, and determining a data description scheme of the standard service data according to an analysis result;
constructing a big data conceptual diagram corresponding to the standard business data according to the data description scheme;
and establishing a data analysis model according to the user requirements based on the big data conceptual diagram.
2. The method for displaying the big data-based conceptual diagram according to claim 1, wherein the integrating the service data to obtain standard service data comprises:
extracting data characteristics of each data in the service data;
clustering data containing similar data characteristics by using a clustering algorithm;
and carrying out normalization processing on the service data after clustering processing to obtain the standard service data.
3. The big-data-based concept graph presentation method according to claim 1, wherein the performing the structural analysis on the standard business data comprises:
extracting a service object in the standard service data as an entity;
abstracting the entity into an abstract entity according to the theme relationship, and determining the attribute of the abstract entity;
and determining the incidence relation between the abstract entities, and summarizing the abstract entities into a summary entity to obtain the analysis result of the standard service data.
4. The big data-based concept graph presentation method according to claim 1, wherein the constructing the big data concept graph corresponding to the standard business data according to the data description scheme comprises:
determining corresponding diagram identifiers for elements included in the data description scheme one by one;
and displaying the standard business data in a graph according to the graph identification, and performing optimization processing to obtain a big data conceptual diagram corresponding to the standard business data.
5. The big data-based concept graph presentation method according to claim 1, wherein the establishing of the data analysis model according to the user requirement based on the big data concept graph comprises:
acquiring user requirements;
acquiring associated service data related to the user requirements in the standard service data according to the big data conceptual diagram;
and establishing a corresponding data analysis model according to the associated service data.
6. A big data-based concept graph presentation device, the device comprising:
the data integration processing module is used for acquiring service data from a big data platform and integrating the service data to obtain standard service data;
the data structure analysis module is used for carrying out structural analysis on the standard business data and determining a data description scheme of the standard business data according to an analysis result;
the big data conceptual diagram building module is used for building a big data conceptual diagram corresponding to the standard business data according to the data description scheme;
and the analysis model establishing module is used for establishing a data analysis model according to the user requirements based on the big data conceptual diagram.
7. The big-data-based concept graph presentation apparatus according to claim 6, wherein when the business data is integrated to obtain standard business data, the data integration processing module performs the following operations:
extracting data characteristics of each data in the service data;
clustering data containing similar data characteristics by using a clustering algorithm;
and carrying out normalization processing on the service data after clustering processing to obtain the standard service data.
8. The big-data-based concept graph presentation apparatus according to claim 6, wherein in performing the structural analysis on the standard business data, the data structure analysis module performs the following operations:
extracting a service object in the standard service data as an entity;
abstracting the entity into an abstract entity according to the theme relationship, and determining the attribute of the abstract entity;
and determining the incidence relation between the abstract entities, and summarizing the abstract entities into a summary entity to obtain the analysis result of the standard service data.
9. An electronic device, characterized in that the electronic device comprises:
a memory storing at least one instruction; and
a processor executing instructions stored in the memory to perform the big data based concept graph presentation method of any of claims 1 to 5.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the big data based concept graph presentation method according to any one of claims 1 to 5.
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