Wei-Te Chen — accepted AI-conference papers

2023

A Unified Generative Approach to Product Attribute-Value Identification

Keiji Shinzato, Naoki Yoshinaga, Yandi Xia, Wei-Te Chen

ACL 2023findings

Product attribute-value identification (PAVI) has been studied to link products on e-commerce sites with their attribute values (e.g., ⟨Material, Cotton⟩) using product text as clues. Technical demands from real-world e-commerce platforms require PAVI methods to handle unseen values, multi-attribute…

Cited by 12 Source ↗PDF ↗Scholar ↗

2022

Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product Attribute Extraction

Keiji Shinzato, Naoki Yoshinaga, Yandi Xia, Wei-Te Chen

ACL 2022short

A key challenge in attribute value extraction (AVE) from e-commerce sites is how to handle a large number of attributes for diverse products. Although this challenge is partially addressed by a question answering (QA) approach which finds a value in product data for a given query (attribute), it doe…

Cited by 30 Source ↗PDF ↗code ↗Scholar ↗