PSCon: Toward Conversational Product Search

• URL: http://arxiv.org/abs/2502.13881v1
• Date: Wed, 19 Feb 2025 17:05:42 GMT
• Title: PSCon: Toward Conversational Product Search
• Authors: Jie Zou, Mohammad Aliannejadi, Evangelos Kanoulas, Shuxi Han, Heli Ma, Zheng Wang, Yang Yang, Heng Tao Shen,
• Abstract summary: We introduce a new CPS data collection protocol and present PSCon, a novel CPS dataset designed to assist product search via human-like conversations.<n>The dataset is constructed using a coached human-to-human data collection protocol and supports two languages and dual markets.
• Score: 55.94925947614474
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Conversational Product Search (CPS) is confined to simulated conversations due to the lack of real-world CPS datasets that reflect human-like language. Additionally, current conversational datasets are limited to support cross-market and multi-lingual usage. In this paper, we introduce a new CPS data collection protocol and present PSCon, a novel CPS dataset designed to assist product search via human-like conversations. The dataset is constructed using a coached human-to-human data collection protocol and supports two languages and dual markets. Also, the dataset enables thorough exploration of six subtasks of CPS: user intent detection, keyword extraction, system action prediction, question selection, item ranking, and response generation. Furthermore, we also offer an analysis of the dataset and propose a benchmark model on the proposed CPS dataset.

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