86 citations · 210 across the 12 of their papers we have counts for
12 papers
Generative Knowledge Graph Construction: A Review
Hongbin Ye, Ningyu Zhang, Hui Chen +1
Generative Knowledge Graph Construction (KGC) refers to those methods that leverage the sequence-to-sequence framework for building knowledge graphs, which is flexible and can be a…
Neural-Symbolic Entangled Framework for Complex Query Answering
Zezhong Xu, Wen Zhang, Peng Ye +2
Answering complex queries over knowledge graphs (KG) is an important yet challenging task because of the KG incompleteness issue and cascading errors during reasoning. Recent query…
Ruleformer: Context-aware Differentiable Rule Mining over Knowledge Graph
Zezhong Xu, Peng Ye, Hui Chen +3
Rule mining is an effective approach for reasoning over knowledge graph (KG). Existing works mainly concentrate on mining rules. However, there might be several rules that could be…
Bridging the Gap between Reality and Ideality of Entity Matching: A Revisiting and Benchmark Re-Construction
Tianshu Wang, Hongyu Lin, Cheng Fu +6
Entity matching (EM) is the most critical step for entity resolution (ER). While current deep learningbased methods achieve very impressive performance on standard EM benchmarks, t…
Commonsense Knowledge Salience Evaluation with a Benchmark Dataset in E-commerce
Yincen Qu, Ningyu Zhang, Hui Chen +6
In e-commerce, the salience of commonsense knowledge (CSK) is beneficial for widespread applications such as product search and recommendation. For example, when users search for `…
From Discrimination to Generation: Knowledge Graph Completion with Generative Transformer
Xin Xie, Ningyu Zhang, Zhoubo Li +5
Knowledge graph completion aims to address the problem of extending a KG with missing triples. In this paper, we provide an approach GenKGC, which converts knowledge graph completi…
Ontology-enhanced Prompt-tuning for Few-shot Learning
Hongbin Ye, Ningyu Zhang, Shumin Deng +5
Few-shot Learning (FSL) is aimed to make predictions based on a limited number of samples. Structured data such as knowledge graphs and ontology libraries has been leveraged to ben…
Learning to Ask for Data-Efficient Event Argument Extraction
Hongbin Ye, Ningyu Zhang, Zhen Bi +5
Event argument extraction (EAE) is an important task for information extraction to discover specific argument roles. In this study, we cast EAE as a question-based cloze task and e…
Knowledge Perceived Multi-modal Pretraining in E-commerce
Yushan Zhu, Huaixiao Tou, Wen Zhang +4
In this paper, we address multi-modal pretraining of product data in the field of E-commerce. Current multi-modal pretraining methods proposed for image and text modalities lack ro…
AliCG: Fine-grained and Evolvable Conceptual Graph Construction for Semantic Search at Alibaba
Ningyu Zhang, Qianghuai Jia, Shumin Deng +8
Conceptual graphs, which is a particular type of Knowledge Graphs, play an essential role in semantic search. Prior conceptual graph construction approaches typically extract high-…
Improving Conversational Recommendation System by Pretraining on Billions Scale of Knowledge Graph
Chi-Man Wong, Fan Feng, Wen Zhang +7
Conversational Recommender Systems (CRSs) in E-commerce platforms aim to recommend items to users via multiple conversational interactions. Click-through rate (CTR) prediction mode…
Text-guided Legal Knowledge Graph Reasoning
Luoqiu Li, Zhen Bi, Hongbin Ye +3
Recent years have witnessed the prosperity of legal artificial intelligence with the development of technologies. In this paper, we propose a novel legal application of legal provi…