计算机与现代化Issue(8)：16-23,8.DOI:10.3969/j.issn.1006-2475.2025.08.003
目标驱动的面向推荐的对话生成方法
Goal Driven Recommendation-oriented Dialog Generation Method
摘要
Abstract
The task of recommendation-oriented dialog generation aims to achieve accurate recommendations by obtaining user preferences through human-computer dialog interactions.In response to the problem of limited dialog recommendation types and low quality of generated replies in existing research,this paper proposes a Goal Driven Recommendation-oriented Dialog Genera-tion model(GDRDG)based on the Unified Language Model pre-training(UniLM).The model comprises a text representation module,a multi-head encoding module,a decoding module,and a specialized attention masking mechanism.The text represen-tation module uses UniLM to vectorize the input text,ensuring that the model captures deep semantic features of the text.The multi-head encoding module employs a multi-head self-attention mechanism to capture global contextual information,enhanc-ing the coherence and relevance of the generated responses.The decoding module generates the target of the current dialogue round and the response based on this target,ensuring that the reply is consistent with the context and guides the conversation to-wards the intended goal.The special attention masking mechanism is used to control the information flow during the decoding pro-cess,ensuring that the model focuses only on information relevant to the current round,thereby improving the quality of the re-sponse.Experimental results demonstrate that the proposed GDRDG model outperforms existing methods in metrics such as BLEU,Distinct,F1,and Hit@1,thereby validating the model's effectiveness and advancement.关键词
目标驱动/推荐对话/对话生成/统一预训练语言模型/注意力机制Key words
goal driven/recommendation dialog/dialog generation/unified language model pre-training/attention mechanism分类
信息技术与安全科学引用本文复制引用
景清武,陈洪军,高翟,周美美..目标驱动的面向推荐的对话生成方法[J].计算机与现代化,2025,(8):16-23,8.基金项目
国家自然科学基金资助项目(61672144) （61672144）
