A Usage-centric Take on Intent Understanding in E-Commerce
CoRR(2024)
摘要
Identifying and understanding user intents is a pivotal task for E-Commerce.
Despite its popularity, intent understanding has not been consistently defined
or accurately benchmarked. In this paper, we focus on predicative user intents
as "how a customer uses a product", and pose intent understanding as a natural
language reasoning task, independent of product ontologies. We identify two
weaknesses of FolkScope, the SOTA E-Commerce Intent Knowledge Graph, that limit
its capacity to reason about user intents and to recommend diverse useful
products. Following these observations, we introduce a Product Recovery
Benchmark including a novel evaluation framework and an example dataset. We
further validate the above FolkScope weaknesses on this benchmark.
更多查看译文
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要