10 papers with code • 0 benchmarks • 0 datasets
Expand a seed taxonomy with new unseen node
These leaderboards are used to track progress in Taxonomy Expansion
Taxonomies consist of machine-interpretable semantics and provide valuable knowledge for many web applications.
Automatic construction of a taxonomy supports many applications in e-commerce, web search, and question answering.
We propose a self-supervised taxonomy expansion model named STEAM, which leverages natural supervision in the existing taxonomy for expansion.
Enquire One's Parent and Child Before Decision: Fully Exploit Hierarchical Structure for Self-Supervised Taxonomy Expansion
Taxonomy is a hierarchically structured knowledge graph that plays a crucial role in machine intelligence.
Learning What You Need from What You Did: Product Taxonomy Expansion with User Behaviors Supervision
Specifically, i) to fully exploit user behavioral information, we extract candidate hyponymy relations that match user interests from query-click concepts; ii) to enhance the semantic information of new concepts and better detect hyponymy relations, we model concepts and relations through both user-generated content and structural information in existing taxonomies and user click logs, by leveraging Pre-trained Language Models and Graph Neural Network combined with Contrastive Learning; iii) to reduce the cost of dataset construction and overcome data skews, we construct a high-quality and balanced training dataset from existing taxonomy with no supervision.
Specifically, the inherited feature originates from "parent" nodes and is weighted by an inheritance factor.
A Unified Taxonomy-Guided Instruction Tuning Framework for Entity Set Expansion and Taxonomy Expansion
Entity Set Expansion, Taxonomy Expansion, and Seed-Guided Taxonomy Construction are three representative tasks that can be used to automatically populate an existing taxonomy with new entities.