EP-4738225-A1 - DATA PROCESSING METHOD AND RELATED APPARATUS

EP4738225A1EP 4738225 A1EP4738225 A1EP 4738225A1EP-4738225-A1

Abstract

A data processing method may be applied to the field of artificial intelligence. The method includes: obtaining a first prompt, where the first prompt includes description information of an advertisement and attribute information of a media, the media is a delivery platform of the advertisement, and the first prompt indicates to generate a delivery demand of the advertisement on the media based on the description information and the attribute information of the media; obtaining the delivery demand on the media based on the first prompt by using a language model; and determining, based on a received advertisement access request of a user on the media and a relationship between the delivery demand and intent information of the user, whether to deliver the advertisement to the user. In this application, the language model is guided by using the first prompt, to help an advertiser efficiently and accurately establish an advertisement delivery task (that is, a delivery demand) at a scenario granularity without media expertise.

Inventors

GUO, HUIFENG
TANG, Ruiming
WANG, YICHAO
MENG, Xiaojun
QIAN, LI

Assignees

Huawei Technologies Co., Ltd.

Dates

Publication Date: 20260506
Application Date: 20240718

Claims (14)

A data processing method, wherein the method comprises: obtaining a first prompt, wherein the first prompt comprises description information of an advertisement and attribute information of a media, the media is a delivery platform of the advertisement, and the first prompt indicates to generate a delivery demand of the advertisement on the media based on the description information and the attribute information of the media; obtaining the delivery demand on the media based on the first prompt by using a language model; and determining, based on a received advertisement access request of a user on the media and a relationship between the delivery demand and intent information of the user, whether to deliver the advertisement to the user.
The method according to claim 1, wherein the delivery demand comprises a plurality of slots and a description corresponding to each slot, and each slot corresponds to one demand; and the first prompt specifically indicates to generate, based on the description information and the attribute information of the media, the plurality of slots and the description corresponding to each slot, and each slot corresponds to one delivery demand.
The method according to claim 1 or 2, wherein obtaining the delivery demand on the media based on the first prompt by using the language model comprises: obtaining a candidate delivery demand on the media based on the first prompt by using the language model; and receiving modification information for the candidate delivery demand, and obtaining the delivery demand on the media based on a second prompt by using the language model, wherein the second prompt indicates to modify the candidate delivery demand based on the modification information.
The method according to any one of claims 1 to 3, wherein the method further comprises: obtaining a third prompt, wherein the third prompt comprises a historical behavior of the user, and the third prompt indicates to enrich profile information of the user based on the historical behavior; and obtaining the attribute information of the user based on the third prompt by using the language model, wherein the attribute information of the media comprises the profile information of the user.
The method according to any one of claims 1 to 4, wherein the method further comprises: obtaining a fourth prompt, wherein the fourth prompt comprises corresponding context information when the user triggers an advertisement access request on the media, and the fourth prompt indicates to determine the intent information of the user based on the context information; and obtaining the intent information of the user based on the fourth prompt by using the language model.
A data processing apparatus, wherein the apparatus comprises: an obtaining module, configured to obtain a first prompt, wherein the first prompt comprises description information of an advertisement and attribute information of a media, the media is a delivery platform of the advertisement, and the first prompt indicates to generate a delivery demand of the advertisement on the media based on the description information and the attribute information of the media; and a processing module, configured to: obtain the delivery demand on the media based on the first prompt by using a language model; and determine, based on a received advertisement access request of a user on the media and a relationship between the delivery demand and intent information of the user, whether to deliver the advertisement to the user.
The apparatus according to claim 6, wherein the delivery demand comprises a plurality of slots and a description corresponding to each slot, and each slot corresponds to one demand; and the first prompt specifically indicates to generate, based on the description information and the attribute information of the media, the plurality of slots and the description corresponding to each slot, and each slot corresponds to one delivery demand.
The apparatus according to claim 6 or 7, wherein the processing module is specifically configured to: obtain a candidate delivery demand on the media based on the first prompt by using the language model; and receive modification information for the candidate delivery demand, and obtain the delivery demand on the media based on a second prompt by using the language model, wherein the second prompt indicates to modify the candidate delivery demand based on the modification information.
The apparatus according to any one of claims 6 to 8, wherein the obtaining module is further configured to: obtain a third prompt, wherein the third prompt comprises a historical behavior of the user, and the third prompt indicates to enrich profile information of the user based on the historical behavior; and the processing module is further configured to obtain the attribute information of the user based on the third prompt by using the language model, wherein the attribute information of the media comprises the profile information of the user.
The apparatus according to any one of claims 6 to 9, wherein the obtaining module is further configured to: obtain a fourth prompt, wherein the fourth prompt comprises corresponding context information when the user triggers an advertisement access request on the media, and the fourth prompt indicates to determine the intent information of the user based on the context information; and the processing module is further configured to obtain the intent information of the user based on the fourth prompt by using the language model.
A computing device, wherein the computing device comprises a memory and a processor, the memory stores code, and the processor is configured to: obtain the code, and perform the method according to any one of claims 1 to 5.
A computer storage medium, wherein the computer storage medium stores one or more instructions, and when the instructions are executed by one or more computers, the one or more computers are enabled to implement the method according to any one of claims 1 to 5.
A computer program product, comprising code, wherein when the code is executed, the method according to any one of claims 1 to 5 is implemented.
A chip, comprising a processor, wherein the processor is configured to support a data processing apparatus in implementing the method according to any one of claims 1 to 5.

Description

This application claims priority to Chinese Patent Application No. 202310896986.4, filed with the China National Intellectual Property Administration on July 20, 2023 and entitled "DATA PROCESSING METHOD AND RELATED APPARATUS", which is incorporated herein by reference in its entirety. TECHNICAL FIELD This application relates to the field of artificial intelligence, and in particular, to a data processing method and a related apparatus. BACKGROUND Artificial intelligence (artificial intelligence, AI) is a theory, a method, a technology, and an application system in which human intelligence is simulated, extended, and expanded by using a digital computer or a machine controlled by a digital computer, to perceive an environment, obtain knowledge, and obtain an optimal result by using the knowledge. In other words, the artificial intelligence is a branch of computer science, and is intended to understand essence of intelligence and produce a new intelligent machine that can react in a manner similar to the human intelligence. Artificial intelligence is to research design principles and implementation methods of various intelligent machines, so that the machines have perception, inference, and decision-making functions. A machine learning system includes a personalized recommendation system, and trains parameters of a machine learning model based on input data and labels by using an optimization method such as gradient descent. After the model parameters converge, the model may be used to complete prediction of unknown data. The following uses prediction of a click-through rate in the personalized recommendation system as an example. Input data of the personalized recommendation system includes user attributes and commodity attributes. How to predict a personalized recommendation list based on a user preference has important impact on improvement of recommendation accuracy of the recommendation system. With the release of a series of large language models (large language models, LLMs), such as ChatGPT, many manufacturers study application of the large language models on a recommendation task. ChatGPT is a large language model that uses a human feedback reinforcement learning technology to align a generative capability of the large language model with a human intent. In this way, ChatGPT has a human conversation capability with fairly high performance. In an advertisement delivery system, an advertiser may set an advertisement delivery task at a demand-side platform (demand-side platform, DSP) according to a demand of the advertiser. A user group label, a keyword, and the like are used as anchors for formulating the task, and the advertiser selects a keyword suitable for the advertiser to formulate the task. However, the advertiser selects the keyword from the perspective of the advertiser to establish the task. Due to knowledge limitation, the advertiser may be unable to select a keyword that is most favorable to the advertiser and that can best reflect the demand of the advertiser. This may result in relatively low advertisement delivery accuracy. SUMMARY This application provides a data processing method, to help an advertiser efficiently and accurately construct an advertisement delivery task at a scenario granularity without media background knowledge. According to a first aspect, this application provides a data processing method. The method includes: obtaining a first prompt, where the first prompt includes description information of an advertisement and attribute information of a media, the media is a delivery platform of the advertisement, and the first prompt indicates to generate a delivery demand of the advertisement on the media based on the description information and the attribute information of the media; obtaining the delivery demand on the media based on the first prompt by using a language model; and determining, based on a received advertisement access request of a user on the media and a relationship between the delivery demand and intent information of the user, whether to deliver the advertisement to the user. The language model is guided by using the first prompt, to help an advertiser efficiently and accurately construct an advertisement delivery task at a scenario granularity without media background knowledge. In addition, the advertisement delivery task may be adjusted in an interactive manner. In a possible implementation, the delivery demand generated by using the language model includes a plurality of slots and a description corresponding to each slot. Each slot corresponds to one demand. Specifically, the plurality of slots may be specified in the prompt, and the language model may be guided by using the first prompt to generate the description of the delivery demand corresponding to each slot. In other words, the first prompt may specifically indicate to generate, based on the description information and the attribute information of the media, the plurality of slots and the descr