KR-20260063473-A - METHOD AND APPARATUS FOR GENERATING RESPONSE BASED ON DATA PROCESSING

Abstract

A method and apparatus for generating a response based on data processing are disclosed. A method for generating a response based on data processing according to one embodiment may include the steps of determining a question type of input data corresponding to an advertisement object, determining a data type to be extracted based on the question type, obtaining advertisement data corresponding to the data type, generating a prompt based on the question type and the advertisement data, and applying the prompt to a response generation model to obtain answer data.

Inventors

• 전석원
• 김대용
• 위희주

Assignees

• 주식회사 카카오

Dates

Publication Date

20260507

Application Date

20241030

Claims (20)

1. In a data processing-based response generation method, A step of determining the question type of input data corresponding to the ad object; A step of determining the type of data to be extracted based on the above question type; A step of obtaining advertising data corresponding to the above data type; A step of generating a prompt based on the above question type and the above advertisement data; and A step of obtaining response data by authorizing the above prompt to a response generation model including, method.
2. In paragraph 1, The step of determining the data type to be extracted above Step of obtaining a query indicating a data type mapped to the above question type including, method.
3. In paragraph 1, The above question type is determined based on the response generation model pool, method.
4. In paragraph 3, The above response generation model pool includes one or more response generation models in which at least one of a prompt template and a neural network is distinct from each other. method.
5. In paragraph 1, The step of determining the data type to be extracted above If the above question type is a first question type, a step of determining the advertising data of the above advertising object as the data type to be extracted; and If the above question type is a second question type, the step of determining the advertising data of another advertising object related to the above advertising object as the data type to be extracted including, method.
6. In paragraph 1, The step of determining the data type to be extracted above A step of determining a target advertising object based on the above question type and classification information of the above advertising object; and Step of determining the advertising data of the above-mentioned target advertising object as the data type to be extracted including, method.
7. In paragraph 6, The step of determining the above-mentioned target advertising object is A step of determining at least one of the advertising objects as the target advertising object based on the advertising performance metrics of the advertising objects corresponding to the classification information of the advertising objects. including, method.
8. In paragraph 6, The classification information of the above advertising object including at least one of classification information of an item corresponding to the above-mentioned advertising object and classification information of a target consumer of the advertisement corresponding to the above-mentioned advertising object, method.
9. In paragraph 1, The step of generating the above prompt is A step of generating a prompt including a prompt template mapped to the above question type and the above advertising data including, method.
10. In paragraph 1, The step of generating the above prompt is A step of obtaining a prompt template mapped to the above question type; and Step of determining the value of a variable included in the above prompt template as the value of an item of the above advertising data mapped to the above variable including, method.
11. In paragraph 1, The step of generating the above prompt is Based on the above question type, a step of determining at least one of a plurality of candidate response generation models included in a response generation model pool as the response generation model; and A step of generating a prompt corresponding to the determined response generation model based on the above advertisement data. including, method.
12. In paragraph 1, The step of obtaining the above answer data is Based on the above question type, a step of determining at least one of a plurality of candidate response generation models included in a response generation model pool as the response generation model; and A step of obtaining answer data by applying the above prompt to the above-determined response generation model. including, method.
13. In paragraph 1, The above input data is received from the advertiser's terminal, and the above response data is provided to the advertiser's terminal. method.
14. In paragraph 1, The above question types include at least one of a type regarding advertising performance summary and a type regarding advertising performance improvement, method.
15. A computer program stored on a computer-readable medium in combination with hardware to execute the method of any one of claims 1 to 14.
16. In terms of the server, One or more processors; and Memory that stores commands Includes, When the above commands are executed by the one or more processors, the server, A step of determining the question type of input data corresponding to the ad object; A step of determining the type of data to be extracted based on the above question type; A step of obtaining advertising data corresponding to the above data type; A step of generating a prompt based on the above question type and the above advertisement data; and A step of obtaining response data by authorizing the above prompt to a response generation model causing to perform, Server.
17. In Paragraph 16, The step of determining the data type to be extracted above Step of obtaining a query indicating a data type mapped to the above question type including, Server.
18. In Paragraph 16, The above question type is determined based on the response generation model pool, Server.
19. In Paragraph 16, The step of determining the data type to be extracted above If the above question type is a first question type, a step of determining the advertising data of the above advertising object as the data type to be extracted; and If the above question type is a second question type, the step of determining the advertising data of another advertising object related to the above advertising object as the data type to be extracted including, Server.
20. In Paragraph 16, The step of determining the data type to be extracted above A step of determining a target advertising object based on the above question type and classification information of the above advertising object; and Step of determining the advertising data of the above-mentioned target advertising object as the data type to be extracted including, Server.

Description

Method and apparatus for generating response based on data processing The following embodiments relate to a data processing-based response generation method and apparatus. Generative models are models that generate new text, images, speech, etc., from given input data; examples include GANs (Generative Adversarial Networks), Transformers, and GPTs (Generative Pre-trained Transformers). Unlike simple rule-based approaches, generative models learn patterns in unstructured data from large-scale datasets and can generate responses corresponding to input data by understanding and applying context. Data processing and response generation technologies based on generative models can be applied to various fields such as information retrieval and customer support. Accordingly, the development of technologies is underway to efficiently analyze and process data using generative models to generate natural and appropriate responses in specific situations. FIG. 1 is an operation flowchart of a data processing-based response generation method according to one embodiment. FIG. 2 is a diagram illustrating a data processing-based response generation system according to one embodiment. FIG. 3 is a diagram illustrating the operation of a data processing-based response generation method according to a specific example of one embodiment. FIG. 4 is a diagram illustrating the operation of a data processing-based response generation method according to a specific example of one embodiment. FIG. 5 is an example diagram of a server configuration according to one embodiment. Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only and may be modified and implemented in various forms. Accordingly, actual implementations are not limited to the specific embodiments disclosed, and the scope of this specification includes modifications, equivalents, or substitutions included in the technical concept described by the embodiments. In relation to the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of the noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, each of the phrases such as "A or B", "at least one of A and B", "at least one of A or B", "A, B or C", "at least one of A, B and C", and "at least one of A, B, or C" may include any one of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as “first,” “second,” or “first” or “second” may be used simply to distinguish a component from another component and do not limit the components in other aspects (e.g., importance or order). For example, a first component may be named a second component, and similarly, a second component may be named a first component. Where any (e.g., 1st) component is referred to as “coupled” or “connected” to another (e.g., 2nd) component, with or without the terms “functionally” or “communicationly,” it means that said any component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this specification, terms such as "comprising" or "having" are intended to specify the existence of the described features, numbers, steps, actions, components, parts, or combinations thereof, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof. Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this specification. Hereinafter, embodiments will be described in detail with reference to the attached drawings. In the description with reference to the attached drawings, identical components are given the same reference numeral regardless of the drawing number, and redundant descriptions thereof will be omitted. FIG. 1 is an operation flowchart of a data processing-based response generation method according to one embodiment. Hereinafter, the data processing-based response generation method may be briefly referred to as the response generation method. The response generation method according to one embodiment may be performed on a server. For example, the operation of the response generation method may be performed by at least one processor of the server. The specific hardware configuration of the server is described in detail below. A response generated by a response generatio