Concept -- An Evaluation Protocol on Conversational Recommender Systems with System-centric and User-centric Factors
| Autor: | Huang, Chen, Qin, Peixin, Deng, Yang, Lei, Wenqiang, Lv, Jiancheng, Chua, Tat-Seng |
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| Rok vydání: | 2024 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | The conversational recommendation system (CRS) has been criticized regarding its user experience in real-world scenarios, despite recent significant progress achieved in academia. Existing evaluation protocols for CRS may prioritize system-centric factors such as effectiveness and fluency in conversation while neglecting user-centric aspects. Thus, we propose a new and inclusive evaluation protocol, Concept, which integrates both system- and user-centric factors. We conceptualise three key characteristics in representing such factors and further divide them into six primary abilities. To implement Concept, we adopt a LLM-based user simulator and evaluator with scoring rubrics that are tailored for each primary ability. Our protocol, Concept, serves a dual purpose. First, it provides an overview of the pros and cons in current CRS models. Second, it pinpoints the problem of low usability in the "omnipotent" ChatGPT and offers a comprehensive reference guide for evaluating CRS, thereby setting the foundation for CRS improvement. Comment: 33 pages, 18 tables, and 10 figures. Our code is available at https://github.com/huangzichun/Concept4CRS |
| Databáze: | arXiv |
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