Prometheus Chatbot：用于计算机组件推荐的知识图谱协同大语言模型
Prometheus Chatbot: Knowledge Graph Collaborative Large Language Model for Computer Components Recommendation
AI总结：
针对自然语言驱动的知识图谱推荐系统在意图理解和实体链接上的挑战，开发了集成KG与LLM的Prometheus聊天机器人，实现计算机组件的精准个性化推荐。
摘要：
知识图谱（KGs）在网络对齐、问答和推荐系统（RSs）等应用中至关重要，因为它们提供了结构化的关系数据，有助于推断间接关系。然而，开发能够处理自然语言用户输入的基于KG的RS面临重大挑战。首先，自然语言处理单元必须有效处理人类语言的歧义性和多变性，以准确解读用户意图。其次，系统必须精确识别并将实体（如产品名称）链接到KG中对应的节点。为克服这些挑战，在Lenovo的支持下，我们开发了一款名为“Prometheus”的新型聊天机器人，它将KG与大语言模型（LLM）集成，专为推荐计算机组件而设计。该聊天机器人能准确解码用户请求，并基于KG提供个性化推荐，确保精准理解和响应其计算机配置需求。
英文摘要：
Knowledge graphs (KGs) are essential in applications such as network alignment, question-answering, and recommender systems (RSs) since they offer structured relational data that facilitate the inference of indirect relationships. However, the development of KG-based RSs capable of processing user inputs in natural language faces significant challenges. Firstly, natural language processing units must effectively handle the ambiguity and variability in human language to interpret user intents accurately. Secondly, the system must precisely identify and link entities, like product names, to their corresponding nodes in KGs. To overcome these challenges, supported by Lenovo, we developed a novel chatbot called "Prometheus," which integrates a KG with a large language model (LLM), specifically designed for recommending computer components. This chatbot can accurately decode user requests and deliver personalized recommendations derived from KGs, ensuring precise comprehension and response to their computer setup needs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
