CN112182244A - Brand knowledge graph construction method and device and terminal - Google Patents
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Abstract
The application relates to a brand knowledge graph construction method, a brand knowledge graph construction device and a terminal, wherein the brand knowledge graph construction method comprises the steps of obtaining social platform brand data; extracting a plurality of key entities from social platform brand data; establishing incidence relations among different entities in a plurality of key entities; and generating a brand knowledge graph according to the plurality of key entities and the incidence relation. The method and the device can visually display the participation and the influence of the brand on the social platform for the brand owner, and are beneficial to improving the economic benefits of the brand owner and enterprises.
Description
Technical Field
The application belongs to the technical field of internet marketing, and particularly relates to a brand knowledge graph construction method, a brand knowledge graph construction device and a brand knowledge graph construction terminal.
Background
With the explosion of social networks, users generate a great deal of content and data on social platforms. This data is of paramount importance to brand owners who wish to find content and users on the social network that are relevant to the brand and to mine this data to guide the brand owner in the marketing campaign on the social platform.
The knowledge graph, also called scientific knowledge graph, combines the theories and methods of applying mathematics, graphics, information visualization technology, information science and other disciplines with the methods of metrology citation analysis, co-occurrence analysis and the like, and uses the visualized graph to vividly display the core structure, development history, frontier field and overall knowledge framework of the disciplines to achieve the modern theory of multidisciplinary fusion. Provides a practical and valuable reference for subject research. However, in the existing knowledge graph in the internet marketing field, the relation between the marketing brand and the social platform is output less, and a brand owner cannot visually know the participation and the influence of the brand on the social platform, so that the activity plan of the brand owner lacks a basis, and the economic benefits of the brand owner and enterprises are influenced.
Disclosure of Invention
The method, the device and the terminal for establishing the brand knowledge graph are used for solving the problems that in the existing knowledge graph in the internet marketing field, the relation output of a marketing brand and a social platform is less, a brand owner cannot visually know the participation and the influence of the brand on the social platform, the brand owner activity plan lacks basis, and the economic benefit of the brand owner and an enterprise is influenced to at least a certain extent.
In a first aspect, the present application provides a brand knowledge graph construction method, including:
obtaining social platform brand data;
extracting a plurality of key entities from the social platform brand data;
establishing incidence relations among different entities in the key entities;
and generating a brand knowledge graph according to the plurality of key entities and the incidence relation.
Further, the method also comprises the following steps:
storing the plurality of key entities and the incidence relations to a graph database;
and querying data in the database so that the data is displayed on the terminal interface in a graph form.
Further, the querying data in the database so that the data is displayed on the terminal interface in a graph form includes:
statistical calculations based on graph calculations are performed on data in a graph database,
and displaying the calculated aggregate data on a terminal interface in a graph form.
Further, the plurality of key entities includes:
entities include multiple items of brand, industry of ownership, product of ownership, content, user, and topic.
Further, the establishing an association relationship between different entities includes:
attribution relations between brands and belonged products, publishing relations between users and contents, mentioning relations between contents and brands, mentioning relations between contents and topics, and attention relations between users and users.
Further, the brand knowledge graph includes:
one or more of interactive content published by brands, fans of influential brand accounts, brand-initiated engagement topics, and influence comparison between brands on a social platform.
Further, the social platform influence comparison between the brands comprises:
the interest level of users who mention a brand in other brands, other brands that users who focus on the brand focus on, whether other brands are more popular than the brand in the same industry.
Further, the obtaining social platform brand data includes:
continuously collecting related content of a plurality of brands in a social platform in a plurality of industries;
and preprocessing the related content to obtain social platform brand data.
In a second aspect, the present application provides a brand knowledge graph building apparatus comprising:
the acquisition module is used for acquiring social platform brand data;
the extraction module is used for extracting a plurality of key entities from the social platform brand data;
the establishing module is used for establishing incidence relations among different entities in the key entities;
and the generating module is used for generating the brand knowledge graph according to the plurality of key entities and the incidence relation.
In a third aspect, the present application provides a terminal, comprising:
a processor and a memory;
the processor is configured to execute a computer program stored in the memory to implement the brand knowledge graph building method of any one of the first aspects.
The technical scheme provided by the embodiment of the application can have the following beneficial effects:
according to the brand knowledge graph construction method, the brand knowledge graph construction device and the brand knowledge graph construction terminal, the social platform brand data are obtained, the key entities are extracted from the social platform brand data, the association relations among different entities are established in the key entities, and the brand knowledge graph is generated according to the key entities and the association relations, so that the participation degree and the influence of a brand on the social platform can be visually displayed for a brand owner, and the brand owner and enterprise economic benefits are improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
FIG. 1 is a flowchart of a brand knowledge graph building method according to an embodiment of the present application.
FIG. 2 is a flowchart of a brand knowledge graph building method according to another embodiment of the present application.
FIG. 3 is a flowchart of a brand knowledge graph building method according to another embodiment of the present application.
FIG. 4 is a functional block diagram of a brand knowledge map building apparatus according to an embodiment of the present application.
FIG. 5 is a functional block diagram of a brand knowledge graph building system according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail below. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 1 is a flowchart of a brand knowledge graph building method according to an embodiment of the present application, and as shown in fig. 1, the brand knowledge graph building method includes:
s11: obtaining social platform brand data;
s12: extracting a plurality of key entities from social platform brand data;
s13: establishing incidence relations among different entities in a plurality of key entities;
s14: and generating a brand knowledge graph according to the plurality of key entities and the incidence relation.
Because the relation between the marketing brand and the social platform is less output in the existing knowledge graph in the field of internet marketing, a brand owner cannot visually know the participation and the influence of the brand on the social platform, so that the activity plan of the brand owner lacks basis, and the economic benefits of the brand owner and enterprises are influenced.
In the embodiment, by acquiring the brand data of the social platform, extracting a plurality of key entities from the brand data of the social platform, establishing association relations among different entities in the key entities, and generating the brand knowledge graph according to the key entities and the association relations, the participation and the influence of the brand on the social platform can be visually displayed for a brand owner, and the social platform is beneficial to improving the economic benefits of the brand owner and enterprises.
Fig. 2 is a flowchart of a brand knowledge graph building method according to another embodiment of the present application, and as shown in fig. 2, the brand knowledge graph building method includes:
s21: obtaining social platform brand data;
s22: extracting a plurality of key entities from social platform brand data, including but not limited to brands, affiliated industries, affiliated products, content, users, topics and the like;
the entity also comprises attributes, such as the attributes of the product comprise the brand class, and the attributes of the content comprise the type: text/picture/video, number of interactions, attributes of the user including gender, age, region, interest tag, authentication type, attributes of the topic including number of participants, etc.
S23: the incidence relation between different entities is established in a plurality of key entities, including but not limited to the attribution relation between brands and belonged products, the publishing relation between users and contents, the mentioning relation between contents and brands, the mentioning relation between contents and topics, the attention relation between users and users, and the like.
S24: storing a plurality of key entities and incidence relations to a graph database;
s25: and querying data in the database so that the data is displayed on the terminal interface in a graph form.
In some embodiments, querying data in a database to make the data presented in a terminal interface in a graph form includes:
s251: statistical calculations based on graph calculations are performed on data in a graph database,
s252: and displaying the calculated aggregate data on a terminal interface in a graph form.
Displaying on a terminal interface in a graph form, namely presenting related information of a brand on a social platform in a knowledge graph form, wherein the brand knowledge graph comprises: interactive content for brand publication, fans of influential brand accounts, brand-initiated engagement topics, and social platform influence pairs between brands such as interestingness of other brands by users who mention the brand, other brands of interest by users who are interested in the brand, whether other brands are more popular than the brand in the same industry, and the like.
On one hand, a brand owner can more visually see key contents related to the brand on the social platform, such as most interactive contents published by the brand, most influential fans of brand accounts, and topics with highest brand-initiated participation, and on the other hand, the brand owner can also see the comparison between the brand and other brands on the social platform, such as a user who mentions a certain brand is more interested in which brand, a user who pays attention to a certain brand pays attention to which brand, whether other brands are more popular than a certain brand in the same industry, and the like. The information has great reference value for brand owners to market and promote on the social platform.
Existing social marketing analysis tools generally analyze from both the content and the user direction, the analysis of the content level generally includes volume trend, hot content display, and the like, and the user level generally analyzes attributes of associated users, such as age, geographical distribution, and the like.
In the embodiment, compared with the traditional content and user-level analysis, a higher-dimensional analysis visual angle is established by referring to the idea of the knowledge map, the core content can be more effectively extracted and displayed in a visual form, the cross-brand association analysis capability is realized, the marketing activity plan of a brand owner is facilitated, and the influence of the brand owner and enterprises is improved.
Fig. 3 is a flowchart of a brand knowledge graph building method according to another embodiment of the present application, and as shown in fig. 3, the brand knowledge graph building method includes:
s31: continuously collecting related content of a plurality of brands in a social platform in a plurality of industries;
the related content comprises: all contents containing brand keywords, user information for publishing the contents, topic information of participating brands, topic content of participating brands, contents and interaction information published by official accounts of the brands on a social platform, fan information of the official accounts of the brands on the social platform and the like;
s32: and preprocessing the related content to obtain social platform brand data.
In some embodiments, the preprocessing operations include filtering and word segmentation operations on related content, analyzing association between content and brand, filtering noise data that is not related to brand, and performing word segmentation operations on content.
In the embodiment, relevant content of a plurality of brands in a social platform in a plurality of industries is collected continuously, the relevant content is preprocessed to obtain the brand data of the social platform, data support can be provided for brand knowledge graph construction, and the speed and accuracy of knowledge graph construction are improved.
An embodiment of the present invention provides a brand knowledge graph constructing apparatus, which is a functional structure diagram shown in fig. 4, and includes:
an obtaining module 41, configured to obtain social platform brand data;
an extraction module 42, configured to extract a plurality of key entities from social platform brand data;
an establishing module 43, configured to establish an association relationship between different entities in a plurality of key entities;
and the generating module 44 is configured to generate a brand knowledge graph according to the plurality of key entities and the association relationship.
A storage module 45, configured to store the plurality of key entities and the association relationship in a graph database;
and the query module 46 is used for querying the data in the graph database so as to display the data on the terminal interface in a graph form.
The acquisition module 47 is used for continuously acquiring related contents of a plurality of brands in a social platform in a plurality of industries;
and the preprocessing module 48 is used for preprocessing the related content to obtain the social platform brand data.
In the embodiment, the social platform brand data is acquired through the acquisition module, the extraction module extracts a plurality of key entities from the social platform brand data, the establishment module establishes association relations among different entities in the key entities, and the generation module generates the brand knowledge graph according to the key entities and the association relations, so that the participation and influence of the brand on the social platform can be visually displayed for a brand owner, and the economic benefits of the brand owner and enterprises can be improved.
An embodiment of the present invention provides a terminal, and as shown in a functional structure diagram in fig. 5, the terminal includes:
a processor 51 and a memory 52;
In some embodiments, a display 53 is further included, and the display 53 is used to present the query data in the form of a graph.
In the embodiment, original content related to the brand is obtained through the processor, the memory and the display, the key entity is extracted, the association relation is built, the association graph of the brand is generated by means of the graph database, the participation degree and the influence of the brand on the social platform are visually displayed for a brand owner, influence activity designation is facilitated, and user requirements are met.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present application, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional component mode. The integrated module, if implemented in the form of a software functional component and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
It should be noted that the present invention is not limited to the above-mentioned preferred embodiments, and those skilled in the art can obtain other products in various forms without departing from the spirit of the present invention, but any changes in shape or structure can be made within the scope of the present invention with the same or similar technical solutions as those of the present invention.
Claims (10)
1. A brand knowledge graph construction method is characterized by comprising the following steps:
obtaining social platform brand data;
extracting a plurality of key entities from the social platform brand data;
establishing incidence relations among different entities in the key entities;
and generating a brand knowledge graph according to the plurality of key entities and the incidence relation.
2. The brand knowledge graph building method of claim 1, further comprising:
storing the plurality of key entities and the incidence relations to a graph database;
and querying data in the database so that the data is displayed on the terminal interface in a graph form.
3. The method for building a brand knowledge graph according to claim 2, wherein the querying data in the graph database so that the data is displayed on a terminal interface in a graph form comprises:
statistical calculations based on graph calculations are performed on data in a graph database,
and displaying the calculated aggregate data on a terminal interface in a graph form.
4. The brand knowledge graph building method of claim 1, wherein the plurality of key entities comprises:
entities include multiple items of brand, industry of ownership, product of ownership, content, user, and topic.
5. The brand knowledge graph building method according to claim 4, wherein the establishing of the association relationship between different entities comprises:
attribution relations between brands and belonged products, publishing relations between users and contents, mentioning relations between contents and brands, mentioning relations between contents and topics, and attention relations between users and users.
6. The method of brand knowledge graph construction according to any one of claims 1 to 5, wherein the brand knowledge graph comprises:
one or more of interactive content published by brands, fans of influential brand accounts, brand-initiated engagement topics, and influence comparison between brands on a social platform.
7. The brand knowledge graph building method of claim 6, wherein the inter-brand impact comparisons at a social platform comprise:
the interest level of users who mention a brand in other brands, other brands that users who focus on the brand focus on, whether other brands are more popular than the brand in the same industry.
8. The brand knowledge graph building method of claim 1, wherein the obtaining social platform brand data comprises:
continuously collecting related content of a plurality of brands in a social platform in a plurality of industries;
and preprocessing the related content to obtain social platform brand data.
9. A brand knowledge graph building apparatus, comprising:
the acquisition module is used for acquiring social platform brand data;
the extraction module is used for extracting a plurality of key entities from the social platform brand data;
the establishing module is used for establishing incidence relations among different entities in the key entities;
and the generating module is used for generating the brand knowledge graph according to the plurality of key entities and the incidence relation.
10. A terminal, comprising:
a processor and a memory;
the processor is configured to execute a computer program stored in the memory to implement the brand knowledge graph building method of any one of claims 1 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113570417A (en) * | 2021-08-09 | 2021-10-29 | 上海明略人工智能(集团)有限公司 | Social digital marketing method and system, storage medium and electronic equipment |
| CN114298774A (en) * | 2022-03-09 | 2022-04-08 | 广州鹰云信息科技有限公司 | Business complex analysis method and system based on brand knowledge graph |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110218960A1 (en) * | 2010-03-07 | 2011-09-08 | Hamid Hatami-Haza | Interactive and Social Knowledge Discovery Sessions |
| CN109726295A (en) * | 2018-12-06 | 2019-05-07 | 深圳云天励飞技术有限公司 | Brand knowledge map display methods, device, figure server and storage medium |
| CN110334220A (en) * | 2019-07-15 | 2019-10-15 | 中国人民解放军战略支援部队航天工程大学 | A kind of knowledge mapping construction method based on multi-data source |
| CN110737845A (en) * | 2019-10-15 | 2020-01-31 | 精硕科技（北京）股份有限公司 | method, computer storage medium and system for realizing information analysis |
-
2020
- 2020-09-28 CN CN202011038350.9A patent/CN112182244A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110218960A1 (en) * | 2010-03-07 | 2011-09-08 | Hamid Hatami-Haza | Interactive and Social Knowledge Discovery Sessions |
| CN109726295A (en) * | 2018-12-06 | 2019-05-07 | 深圳云天励飞技术有限公司 | Brand knowledge map display methods, device, figure server and storage medium |
| CN110334220A (en) * | 2019-07-15 | 2019-10-15 | 中国人民解放军战略支援部队航天工程大学 | A kind of knowledge mapping construction method based on multi-data source |
| CN110737845A (en) * | 2019-10-15 | 2020-01-31 | 精硕科技（北京）股份有限公司 | method, computer storage medium and system for realizing information analysis |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113570417A (en) * | 2021-08-09 | 2021-10-29 | 上海明略人工智能(集团)有限公司 | Social digital marketing method and system, storage medium and electronic equipment |
| CN114298774A (en) * | 2022-03-09 | 2022-04-08 | 广州鹰云信息科技有限公司 | Business complex analysis method and system based on brand knowledge graph |
| CN114298774B (en) * | 2022-03-09 | 2022-06-07 | 广州鹰云信息科技有限公司 | Business complex analysis method and system based on brand knowledge graph |
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