The knowledge graph (KG) that represents structural relations among entities has become
an increasingly important research field for knowledge-driven artificial intelligence. In this …

Attribute value extraction refers to the task of identifying values of an attribute of interest from
product information. Product attribute values are essential in many e-commerce scenarios …

With the support of advanced information and communication technologies and open
innovative design platforms, the emerging and blooming paradigm of mass personalization …

Product attribute values are essential in many e-commerce scenarios, such as customer
service robots, product recommendations, and product retrieval. While in the real world, the …

We present a new multimodal question answering challenge, ManyModalQA, in which an
agent must answer a question by considering three distinct modalities: text, images, and …

Automatic product attribute value extraction refers to the task of identifying values of an
attribute from the product information. Product attributes are essential in improving online …

Attribute extraction aims to identify attribute names and the corresponding values from
descriptive texts, which is the foundation for extensive downstream applications such as …

Existing pre-trained language models (PLMs) have demonstrated the effectiveness of self-
supervised learning for a broad range of natural language processing (NLP) tasks …

Product attributes can display the selling points of products, helping users find their desired
products in search results. However, product attributes are typically incomplete. In e …

Automatically extracting visual attributes for e-commerce data has widespread applications
in cataloging, catalogue qualification and enrichment, visual search, etc. Here, we address …