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Is ChatGPT a Good Recommender? A Preliminary Study by Liu, Junling; Liu, Chao; Zhou, Peilin; Lv, Renjie; Zhou, Kang; Zhang, Yan is a scholarly article available to read on EtoBox.

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Recommendation systems have witnessed significant advancements and have been widely used over the past decades. However, most traditional recommendation methods are task-specific and therefore lack efficient generalization ability. Recently, the emergence of ChatGPT has significantly advanced NLP tasks by enhancing the capabilities of conversational models. Nonetheless, the application of ChatGPT in the recommendation domain has not been thoroughly investigated. In this paper, we employ ChatGPT as a general-purpose recommendation model to explore its potential for transferring extensive linguistic and world knowledge acquired from large-scale corpora to recommendation scenarios. Specifically, we design a set of prompts and evaluate ChatGPT's performance on five recommendation scenarios. Unlike traditional recommendation methods, we do not fine-tune ChatGPT during the entire evaluation process, relying only on the prompts themselves to convert recommendation tasks into natural language tasks. Further, we explore the use of few-shot prompting to inject interaction information that contains user potential interest to help ChatGPT better understand user needs and interests. Comprehensi

Author

Liu, Junling; Liu, Chao; Zhou, Peilin; Lv, Renjie; Zhou, Kang; Zhang, Yan

Published

2023

Language

EN