Enhancing Taxonomy Completion with Concept Generation via Fusing Relational Representations

by   Qingkai Zeng, et al.

Automatic construction of a taxonomy supports many applications in e-commerce, web search, and question answering. Existing taxonomy expansion or completion methods assume that new concepts have been accurately extracted and their embedding vectors learned from the text corpus. However, one critical and fundamental challenge in fixing the incompleteness of taxonomies is the incompleteness of the extracted concepts, especially for those whose names have multiple words and consequently low frequency in the corpus. To resolve the limitations of extraction-based methods, we propose GenTaxo to enhance taxonomy completion by identifying positions in existing taxonomies that need new concepts and then generating appropriate concept names. Instead of relying on the corpus for concept embeddings, GenTaxo learns the contextual embeddings from their surrounding graph-based and language-based relational information, and leverages the corpus for pre-training a concept name generator. Experimental results demonstrate that GenTaxo improves the completeness of taxonomies over existing methods.


page 1

page 2

page 3

page 4


CoRel: Seed-Guided Topical Taxonomy Construction by Concept Learning and Relation Transferring

Taxonomy is not only a fundamental form of knowledge representation, but...

TaxoEnrich: Self-Supervised Taxonomy Completion via Structure-Semantic Representations

Taxonomies are fundamental to many real-world applications in various do...

HyperExpan: Taxonomy Expansion with Hyperbolic Representation Learning

Taxonomies are valuable resources for many applications, but the limited...

Learning What You Need from What You Did: Product Taxonomy Expansion with User Behaviors Supervision

Taxonomies have been widely used in various domains to underpin numerous...

TaxoGen: Unsupervised Topic Taxonomy Construction by Adaptive Term Embedding and Clustering

Taxonomy construction is not only a fundamental task for semantic analys...

A User-Centered Concept Mining System for Query and Document Understanding at Tencent

Concepts embody the knowledge of the world and facilitate the cognitive ...

Taxonomy Enrichment with Text and Graph Vector Representations

Knowledge graphs such as DBpedia, Freebase or Wikidata always contain a ...