CN110674316B - Data conversion method and related device - Google Patents
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- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
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- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/60—Information retrieval; Database structures therefor; File system structures therefor of audio data
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- G06F16/686—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using information manually generated, e.g. tags, keywords, comments, title or artist information, time, location or usage information, user ratings
Abstract
The embodiment of the application provides a data conversion method and a related device, which can effectively save time cost and improve the efficiency of data format conversion. Wherein, the method comprises the following steps: the server firstly obtains service content data, wherein the service content data comprises a first keyword and first subdata corresponding to the first keyword. And then acquiring a knowledge graph corresponding to the business content data, wherein the knowledge graph comprises a first keyword and a second keyword associated with the first keyword. And finally, converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword according to the knowledge map, wherein the first subdata and the second subdata are data in different formats.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a data conversion method and a related apparatus.
Background
With the continuous development of intelligent voice technology, the intelligent speaker has become one of the main tools for human-computer interaction. Specifically, the smart sound box can recognize a voice command of the user, and then provide corresponding business services for the user. For example, if a user inputs a music request instruction to the smart speaker, after the smart speaker recognizes the instruction, the smart speaker may obtain music corresponding to the instruction from the server and play the music.
In order to meet the diversified music requirements of users, the server of the smart speaker generally needs to store music content data in advance, where the data includes various types of keyword data, such as an artist and an album of a certain song, and a song title, and therefore, the server may determine corresponding music based on the keyword data included in the music content data and send the music to the smart speaker. However, the music content data is usually provided by a music provider, and the formats of the music content data made by different music providers are different, so that it is necessary to uniformly convert the music content data in different formats into a data format that can be recognized by the server.
However, in the above process, it is necessary to manually make a conversion rule for music content data of each format, which takes time and costs high, and the conversion efficiency is low.
Disclosure of Invention
The embodiment of the application provides a data conversion method and a related device, which can effectively save time cost and improve the efficiency of data format conversion.
A first aspect of an embodiment of the present application provides a method for data conversion, where the method includes:
acquiring service content data, wherein the service content data comprises a first keyword and first subdata corresponding to the first keyword;
acquiring a knowledge graph corresponding to the business content data, wherein the knowledge graph comprises the first keyword and a second keyword associated with the first keyword;
and converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword according to the knowledge graph, wherein the first subdata and the second subdata are data in different formats.
A second aspect of the embodiments of the present application provides an apparatus for data conversion, where the apparatus includes:
the system comprises a first obtaining module, a second obtaining module and a processing module, wherein the first obtaining module is used for obtaining service content data, and the service content data comprises a first keyword and first subdata corresponding to the first keyword;
a second obtaining module, configured to obtain a knowledge graph corresponding to the service content data, where the knowledge graph includes the first keyword and a second keyword associated with the first keyword;
the conversion module is configured to convert the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword according to the knowledge graph, where the first subdata and the second subdata are data in different formats.
Based on the second aspect, in a first implementation manner of the second aspect of the embodiment of the present application, the conversion module is further configured to:
determining the second keyword corresponding to the first keyword from the knowledge graph;
and converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword.
Based on the first implementation manner of the second aspect, in a second implementation manner of the second aspect of the embodiment of the present application, the second obtaining module is further configured to:
acquiring the service type of the service content data;
and acquiring a knowledge graph corresponding to the service type of the service content data.
Based on the second aspect, or the first implementation manner of the second aspect, or the second implementation manner of the second aspect, in a third implementation manner of the second aspect of the embodiment of the present application, the apparatus further includes:
a third obtaining module, configured to obtain a target service corresponding to the service content data;
and the building module is used for building the corresponding relation between the second subdata corresponding to the second keyword and the target service.
Based on the second aspect, or the first implementation manner of the second aspect, or the second implementation manner of the second aspect, in a third implementation manner of the second aspect of the embodiment of the present application, the second keyword is a synonym of the first keyword.
A third aspect of the embodiments of the present application provides a network device, including: a memory, a transceiver, a processor, and a bus system;
wherein the memory is used for storing programs;
the processor is used for executing the program in the memory and comprises the following steps:
acquiring service content data, wherein the service content data comprises a first keyword and first subdata corresponding to the first keyword;
acquiring a knowledge graph corresponding to the business content data, wherein the knowledge graph comprises the first keyword and a second keyword associated with the first keyword;
converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword according to the knowledge graph, wherein the first subdata and the second subdata are data in different formats;
the bus system is used for connecting the memory and the processor so as to enable the memory and the processor to communicate.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a computer, cause the computer to perform the method according to the first aspect.
According to the technical scheme, the embodiment of the application has the following advantages:
the embodiment of the application provides a data conversion method, in the method, a server firstly obtains service content data, wherein the service content data comprises a first keyword and first subdata corresponding to the first keyword. And then acquiring a knowledge graph corresponding to the business content data, wherein the knowledge graph comprises a first keyword and a second keyword associated with the first keyword. And finally, converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword according to the knowledge map, wherein the first subdata and the second subdata are data in different formats. In the above process, after the server acquires the first keyword included in the service content data and the knowledge graph corresponding to the service content data, because the knowledge graph includes the first keyword and the second keyword associated with the first keyword, the server can convert the first subdata corresponding to the first keyword into the second subdata corresponding to the second keyword based on the knowledge graph, and formats of the two data are different (a format of the second subdata is a uniform data format required by the server). Because the server can automatically complete the conversion of the data format based on the knowledge graph, the time cost can be effectively saved, and the efficiency of the data format conversion is improved.
Drawings
FIG. 1 is a schematic diagram of a data conversion system according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a method for data conversion according to an embodiment of the present application;
FIG. 3 is a schematic illustration of a knowledge graph in an embodiment of the present application;
fig. 4 is a schematic structural diagram of a data conversion framework disposed inside a server in the embodiment of the present application;
FIG. 5 is a schematic diagram of an embodiment of the present application;
fig. 6 is a schematic structural diagram of a network device in this embodiment.
Detailed Description
The embodiment of the application provides a data conversion method and a related device, which can effectively save time cost and improve the efficiency of data format conversion.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "corresponding" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be appreciated that as artificial intelligence technology is researched and developed, artificial intelligence technology has been developed and applied in a variety of fields. The data conversion method adopts a Natural Language Processing (NLP) technology to perform data conversion, wherein the natural Language processing is an important direction in the fields of computer science and artificial intelligence. It studies various theories and methods that enable efficient communication between humans and computers using natural language. Natural language processing is a science integrating linguistics, computer science and mathematics. Therefore, the research in this field will involve natural language, i.e. the language that people use everyday, so it is closely related to the research of linguistics. Natural language processing techniques typically include text processing, semantic understanding, machine translation, robotic question and answer, knowledge mapping, and the like.
Specifically, the intelligent sound box can recognize the voice instruction of the user, and further provide corresponding business service for the user. Fig. 1 is a schematic structural diagram of a data conversion system in an embodiment of the present application, as shown in fig. 1, if a user inputs a music request instruction to a smart speaker, the smart speaker recognizes the instruction, and forwards keyword data (such as a song name) included in the instruction to a server, and the server obtains music corresponding to the keyword data and returns the music to the smart speaker for playing.
The server usually needs to store music content data in a uniform format in advance, where the data includes various types of keyword data, such as an artist, an album, a song title, and the like of a certain song, so that the server can determine corresponding music based on the keyword data included in the music content data and send the music to the smart speaker. For example, when the server receives that the keyword data sent by the smart speaker is a XX song, the server may determine which music content data includes the keyword data (XX song), find a corresponding song based on the keyword data in the music content data, and return to the smart speaker.
However, the music content data is usually provided by a music provider, and the formats of the music content data made by different music providers are different, so that it is necessary to uniformly convert the music content data in different formats into a data format that can be recognized by the server.
In order to improve the efficiency of data conversion, the present application provides a method for data conversion, fig. 2 is a schematic flowchart of the method for data conversion in the embodiment of the present application, and as shown in fig. 2, an embodiment of the method for data conversion in the embodiment of the present application includes:
201. acquiring service content data, wherein the service content data comprises a first keyword and first subdata corresponding to the first keyword;
in this embodiment, to perform data format conversion, the server may first obtain service content data provided by a service provider, where the service content data generally includes a first keyword and first sub data corresponding to the first keyword. Specifically, the service in this embodiment may be entertainment services such as music and video, and for convenience of description, music will be schematically described below as an example. For example, if the server needs to acquire music data in advance, such as song a, song a may be acquired from a plurality of music providers, and at the same time, each music provider will provide the music content data of song a together, such as the singer who performed song a, the song name of song a, the album to which song a belongs, and so on. Specifically, the first keyword included in the music content data may be "name of singer", "name of song", "name of album", and the first sub-data corresponding to the first keyword may be specific information corresponding to "name of singer", such as "name of singer B", "specific information corresponding to name of song", such as "name of song a", "specific information corresponding to name of album", such as "name of album C", and the like.
202. Acquiring a knowledge graph corresponding to business content data, wherein the knowledge graph comprises a first keyword and a second keyword associated with the first keyword;
in this embodiment, a knowledge graph corresponding to the service content data is provided, where the knowledge graph includes a first keyword and a second keyword associated with the first keyword. It should be noted that the second keyword in the knowledge graph represents a uniform data format defined by the server, and the first keyword represents a data format defined by the service provider, that is, the first subdata corresponding to the first keyword is data in the format defined by the service provider.
Specifically, the first keyword and the second keyword are related phrases, for example, the first keyword is "song name", the second keyword may be "song name", or the first keyword is "singer name", the second keyword may be "singer name", and the like.
203. And converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword according to the knowledge map, wherein the first subdata and the second subdata are data in different formats.
After the server acquires the knowledge graph, the knowledge graph comprises the association relationship between the first keyword and the second keyword, so that after the server analyzes the first keyword from the service content data, the server can convert the first subdata corresponding to the first keyword into the second subdata corresponding to the second keyword based on the association relationship between the first keyword and the second keyword in the knowledge graph, and the second subdata corresponding to the second keyword is data in a unified format specified by the server because the second keyword represents the unified data format specified by the server. At this point, the service content data provided by the service provider is converted into the service content data in the uniform format of the server.
In this embodiment, after the server obtains the first keyword included in the service content data and the knowledge graph corresponding to the service content data, because the knowledge graph includes the first keyword and the second keyword associated with the first keyword, the server may convert the first sub-data corresponding to the first keyword into the second sub-data corresponding to the second keyword based on the knowledge graph, and formats of the two data are different (a format of the second sub-data is a uniform data format required by the server). Because the server can automatically complete the conversion of the data format based on the knowledge graph, the time cost can be effectively saved, and the efficiency of the data format conversion is improved.
Based on the embodiment corresponding to fig. 2, in an optional embodiment of the method for data conversion in the embodiment of the present application, acquiring a knowledge graph corresponding to service content data includes:
acquiring the service type of the service content data;
and acquiring a knowledge graph corresponding to the service type of the service content data.
In this embodiment, since the service may be of multiple types, for example, the service may be music or video, and each type has a dedicated knowledge graph, after the server acquires the service content data, the server may determine the service type of the service content data first, and then acquire the knowledge graph corresponding to the service type.
Based on each embodiment corresponding to fig. 2, in an optional embodiment of the data conversion method in the embodiment of the present application, converting the first sub-data corresponding to the first keyword into the second sub-data corresponding to the second keyword according to the knowledge graph includes:
determining a second keyword corresponding to the first keyword from the knowledge graph;
and converting the first subdata corresponding to the first key words into second subdata corresponding to the second key words.
In this embodiment, after the server obtains the service content data, the server may first analyze the service content data to obtain a first keyword, determine a second keyword corresponding to the first keyword from a knowledge graph (the knowledge graph includes a corresponding relationship between the first keyword and the second keyword), and then convert first subdata corresponding to the first keyword into second subdata corresponding to the second keyword. For convenience of understanding, the following description is made with reference to fig. 3, fig. 3 is a schematic diagram of a knowledge graph in an embodiment of the present application, please refer to fig. 3, the knowledge graph is a knowledge graph of a music service, a center node of the knowledge graph is "music", nodes connected to the nodes are entity categories, for example, "singer", "song name", "album", respectively, three entity categories, and a node connected under each entity category is a keyword, for example, a name, under the category. Therefore, the node "singer" and the node "name" may constitute the first keyword, i.e., "singer name", and likewise, the node "album" and the node "name" connected thereto may also constitute the first keyword, i.e., "album name", and the rest of the categories are the same, and will not be described herein again. Further, the node "name" may also connect to associated nodes, such as "name", "title", etc., and the keywords of such nodes are associated with the "name" node, and may be treated as synonyms (or equivalents) between the keywords. Likewise, the node "singer" and the node "name" may constitute the second keyword, or the "singer" and the node "title" may also constitute the second keyword.
Further, when the server determines that the first keyword in the custom format in the music provider is "name of singer", and finds that the second keyword in the format specified by the server is "name of singer" in the knowledge map, the data in the format of "name of singer" (i.e., the first sub-data) in the music content data provided by the music provider may be converted into the data in the format of "name of singer" (i.e., the second sub-data), i.e., the data in the format specified by the server. For example, the first sub-data corresponding to the first keyword "name of singer" is "name B of singer", and the second sub-data corresponding to the conversion into the second keyword "name of singer" may also be "name B of singer", although the data presentation results are the same, but the data structure is different.
Based on the above description, it can be understood that the knowledge graph in this embodiment includes the association relationship between the first keyword and the second keyword, so that the service content data in the format defined by the service provider can be converted into the service content data in the uniform format defined by the server based on the association relationship.
It should be understood that the above-mentioned "name of album", "name of singer" as the first keyword is only illustrative, and "name of singer" or "title of singer" as the first keyword may also be set according to the actual requirements of music providers and servers, and is not limited herein.
Based on each embodiment corresponding to fig. 2, in an optional embodiment of the data conversion method in the embodiment of the present application, after converting the first sub-data corresponding to the first keyword into the second sub-data corresponding to the second keyword according to the knowledge graph, the method further includes:
acquiring a target service corresponding to the service content data;
and constructing a corresponding relation between second subdata corresponding to the second keyword and the target service.
In this embodiment, after the server obtains the second sub-data corresponding to the second keyword, the second sub-data may be associated with the target service corresponding to the service content data, for example, when a music provider provides song a to the server, the music data of song a (i.e., the data of the song a itself) and the music content data of song a (including a singer singing song a, a song name of song a, an album to which song a belongs, and the like) may be simultaneously associated. When the server obtains the music content data (second sub-data containing the second keyword) in the specified format through data conversion, the artist B of the song a and the album C of the song a are associated with the song a. After the server receives the keyword data sent by the intelligent sound box, if the user needs to play the song A of the singer B, the keyword data is matched with the second subdata of the second keyword in the music content data related to the song A and stored in the server, and then the music data of the song A can be returned to the intelligent sound box for the user to use.
For further understanding, in this embodiment, a data conversion frame is described with reference to fig. 4, fig. 4 is a schematic structural diagram of the data conversion frame disposed inside the server in the embodiment of the present application, please refer to fig. 4, a data conversion frame is pre-disposed inside the server, and the data conversion frame includes: the system comprises a knowledge graph calculation engine, a data conversion module and a data persistence module, wherein the knowledge graph calculation engine is provided with knowledge graphs of various services, the data conversion module is used for carrying out data conversion, and a data persistence module is used for storing data after format conversion.
The embodiment converts the service data conversion from a manual conversion matching mode to a data attribute searching matching processing mode based on the knowledge graph, can well support the conversion of large-data-volume complex-format service data, and has stronger flexibility and excellent expansibility. Furthermore, once the format of the service content data defined by the service provider is modified, the embodiment can flexibly and conveniently modify the keyword association relationship in the knowledge graph, and can timely cope with the change of the upstream data format, thereby preventing the data conversion from being wrong or impossible.
The above is a detailed description of a data conversion method in an embodiment of the present application, and a structure and a connection relationship of a data conversion device in the embodiment of the present application are described below, fig. 5 is a schematic structural diagram of the data conversion device in the embodiment of the present application, and please refer to fig. 5, an embodiment of the data conversion device in the embodiment of the present application includes:
a first obtaining module 501, configured to obtain service content data, where the service content data includes a first keyword and first subdata corresponding to the first keyword;
a second obtaining module 502, configured to obtain a knowledge graph corresponding to the service content data, where the knowledge graph includes a first keyword and a second keyword associated with the first keyword;
the conversion module 503 is configured to convert, according to the knowledge graph, first subdata corresponding to the first keyword into second subdata corresponding to the second keyword, where the first subdata and the second subdata are data in different formats.
Based on the embodiment corresponding to fig. 5, in an optional embodiment of the apparatus for data conversion in the embodiment of the present application, the conversion module 503 is further configured to:
determining a second keyword corresponding to the first keyword from the knowledge graph;
and converting the first subdata corresponding to the first key words into second subdata corresponding to the second key words.
Based on the various embodiments corresponding to fig. 5, in an optional embodiment of the apparatus for data conversion in the embodiment of the present application, the second obtaining module is further configured to:
acquiring the service type of the service content data;
and acquiring a knowledge graph corresponding to the service type of the service content data.
Based on the various embodiments corresponding to fig. 5, in an optional embodiment of the apparatus for data conversion in the embodiment of the present application, the apparatus further includes:
the third acquisition module is used for acquiring the target service corresponding to the service content data;
and the building module is used for building the corresponding relation between the second subdata corresponding to the second keyword and the target service.
Based on the embodiments corresponding to fig. 5, in an optional embodiment of the apparatus for data conversion in the embodiment of the present application, the second keyword is a synonym of the first keyword.
It should be noted that, because the contents of information interaction, execution process, and the like between the modules/units of the apparatus are based on the same concept as the method embodiment of the present application, the technical effect brought by the contents is the same as the method embodiment of the present application, and specific contents may refer to the description in the foregoing method embodiment of the present application, and are not described herein again.
Fig. 6 is a schematic structural diagram of a network device according to an embodiment of the present application, where the network device 600 may have a relatively large difference due to different configurations or performances, and may include one or more Central Processing Units (CPUs) 622 (e.g., one or more processors) and a memory 632, and one or more storage media 630 (e.g., one or more mass storage devices) for storing applications 642 or data 644. Memory 632 and storage medium 630 may be, among other things, transient or persistent storage. The program stored on the storage medium 630 may include one or more modules (not shown), each of which may include a sequence of instructions operating on the network device. Still further, central processor 622 may be configured to communicate with storage medium 630 to perform a series of instruction operations in storage medium 630 on network device 600.
The network device 600 may also include one or more power supplies 626, one or more wired or wireless network interfaces 650, one or more input-output interfaces 658, and/or one or more operating systems 641, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and so forth.
Based on the network device structure shown in fig. 6, the central processor 622 is used to execute the program in the memory 632, and includes the following steps:
acquiring service content data, wherein the service content data comprises a first keyword and first subdata corresponding to the first keyword;
acquiring a knowledge graph corresponding to the service content data, wherein the knowledge graph comprises a first keyword and a second keyword associated with the first keyword;
and converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword according to the knowledge map, wherein the first subdata and the second subdata are data in different formats.
Based on the embodiment corresponding to fig. 6, in an optional embodiment of the network device in the embodiment of the present application, the central processor 622 is further configured to:
determining a second keyword corresponding to the first keyword from the knowledge graph;
and converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword.
Based on each embodiment corresponding to fig. 6, in an optional embodiment of the network device in the embodiment of the present application, the central processor 622 is further configured to:
acquiring the service type of the service content data;
and acquiring a knowledge graph corresponding to the service type of the service content data.
Based on each embodiment corresponding to fig. 6, in an optional embodiment of the network device in the embodiment of the present application, the central processor 622 is further configured to:
acquiring a target service corresponding to the service content data;
and constructing a corresponding relation between second subdata corresponding to the second keyword and the target service.
Based on the embodiments corresponding to fig. 6, in an optional embodiment of the network device in the embodiment of the present application, the second keyword is a synonym of the first keyword.
In this embodiment, a server first obtains service content data, where the service content data includes a first keyword and first subdata corresponding to the first keyword. And then acquiring a knowledge graph corresponding to the business content data, wherein the knowledge graph comprises a first keyword and a second keyword associated with the first keyword. And finally, converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword according to the knowledge map, wherein the first subdata and the second subdata are data in different formats. In the above process, after the server acquires the first keyword included in the service content data and the knowledge graph corresponding to the service content data, because the knowledge graph includes the first keyword and the second keyword associated with the first keyword, the server can convert the first subdata corresponding to the first keyword into the second subdata corresponding to the second keyword based on the knowledge graph, and formats of the two data are different (a format of the second subdata is a uniform data format required by the server). Because the server can automatically complete the conversion of the data format based on the knowledge graph, the time cost can be effectively saved, and the efficiency of the data format conversion is improved.
Embodiments of the present application also provide a computer-readable storage medium, which includes instructions that, when executed on a computer, cause the computer to perform the method for data transformation as described above.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units 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 units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application 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, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (8)
1. A method of data conversion, the method comprising:
acquiring service content data, wherein the service content data comprises a first keyword and first subdata corresponding to the first keyword;
acquiring a knowledge graph corresponding to the business content data, wherein the knowledge graph comprises the first keyword and a second keyword associated with the first keyword;
converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword according to the knowledge graph, wherein the first subdata and the second subdata are data in different formats, the first subdata corresponding to the first keyword is data in a format defined by a service provider, and the second subdata corresponding to the second keyword is data in a uniform data format specified by a server;
the acquiring the knowledge graph corresponding to the service content data comprises: acquiring the service type of the service content data, wherein the service type is music or video; and acquiring a knowledge graph corresponding to the service type of the service content data.
2. The method of claim 1, wherein the converting the first sub-data corresponding to the first keyword into the second sub-data corresponding to the second keyword according to the knowledge graph comprises:
determining the second keyword corresponding to the first keyword from the knowledge graph;
and converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword.
3. The method of any one of claims 1 to 2, wherein after the converting the first sub-data corresponding to the first keyword into the second sub-data corresponding to the second keyword according to the knowledge graph, the method further comprises:
acquiring a target service corresponding to the service content data;
and constructing a corresponding relation between second subdata corresponding to the second keyword and the target service.
4. The method according to any one of claims 1 to 2, wherein the second keyword is a synonym of the first keyword.
5. An apparatus for data conversion, the apparatus comprising:
the system comprises a first obtaining module, a second obtaining module and a processing module, wherein the first obtaining module is used for obtaining service content data, and the service content data comprises a first keyword and first subdata corresponding to the first keyword;
a second obtaining module, configured to obtain a knowledge graph corresponding to the service content data, where the knowledge graph includes the first keyword and a second keyword associated with the first keyword;
a conversion module, configured to convert, according to the knowledge graph, the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword, where the first subdata and the second subdata are data in different formats, the first subdata corresponding to the first keyword is data in a format customized by a service provider, and the second subdata corresponding to the second keyword is data in a uniform data format specified by a server;
the second obtaining module is further configured to:
acquiring the service type of the service content data, wherein the service type is music or video;
and acquiring a knowledge graph corresponding to the service type of the service content data.
6. The apparatus for data conversion according to claim 5, wherein the conversion module is further configured to:
determining the second keyword corresponding to the first keyword from the knowledge graph;
and converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword.
7. A network device, comprising: a memory, a transceiver, a processor, and a bus system;
wherein the memory is used for storing programs;
the processor is used for executing the program in the memory and comprises the following steps:
acquiring service content data, wherein the service content data comprises a first keyword and first subdata corresponding to the first keyword;
acquiring a knowledge graph corresponding to the business content data, wherein the knowledge graph comprises the first keyword and a second keyword associated with the first keyword;
converting the first subdata corresponding to the first keyword into second subdata corresponding to the second keyword according to the knowledge graph, wherein the first subdata and the second subdata are data in different formats, the first subdata corresponding to the first keyword is data in a format defined by a service provider, and the second subdata corresponding to the second keyword is data in a uniform data format specified by a server;
the acquiring the knowledge graph corresponding to the service content data comprises: acquiring the service type of the service content data, wherein the service type is music or video; acquiring a knowledge graph corresponding to the service type of the service content data;
the bus system is used for connecting the memory and the processor so as to enable the memory and the processor to communicate.
8. A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to perform the method of any of claims 1 to 4.
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