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08/11/2023
Large Language Models and Knowledge Graphs: Opportunities and Challenges
Large Language Models (LLMs) have taken Knowledge Representation – and t...
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03/18/2023
An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question Answering
Large-scale pre-trained language models (PLMs) such as BERT have recentl...
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03/09/2023
Knowledge-augmented Few-shot Visual Relation Detection
Visual Relation Detection (VRD) aims to detect relationships between obj...
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02/17/2023
Vision, Deduction and Alignment: An Empirical Study on Multi-modal Knowledge Graph Alignment
Entity alignment (EA) for knowledge graphs (KGs) plays a critical role i...
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01/26/2023
Box^2EL: Concept and Role Box Embeddings for the Description Logic EL++
Representation learning in the form of semantic embeddings has been succ...
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12/29/2022
MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid
As an important variant of entity alignment (EA), multi-modal entity ali...
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11/28/2022
Low-resource Personal Attribute Prediction from Conversation
Personal knowledge bases (PKBs) are crucial for a broad range of applica...
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11/20/2022
Embracing Ambiguity: Improving Similarity-oriented Tasks with Contextual Synonym Knowledge
Contextual synonym knowledge is crucial for those similarity-oriented ta...
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10/28/2022
Understanding Adverse Biological Effect Predictions Using Knowledge Graphs
Extrapolation of adverse biological (toxic) effects of chemicals is an i...
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10/08/2022
Relational Message Passing for Fully Inductive Knowledge Graph Completion
In knowledge graph completion (KGC), predicting triples involving emergi...
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09/30/2022
Construction and Applications of Open Business Knowledge Graph
Business Knowledge Graph is important to many enterprises today, providi...
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08/19/2022
Aspect-based Sentiment Classification with Sequential Cross-modal Semantic Graph
Multi-modal aspect-based sentiment classification (MABSC) is an emerging...
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07/26/2022
LaKo: Knowledge-driven Visual Question Answering via Late Knowledge-to-Text Injection
Visual question answering (VQA) often requires an understanding of visua...
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07/04/2022
DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning
Zero-shot learning (ZSL) aims to predict unseen classes whose samples ha...
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06/08/2022
Disentangled Ontology Embedding for Zero-shot Learning
Knowledge Graph (KG) and its variant of ontology have been widely used f...
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05/11/2022
Ontology-Based and Weakly Supervised Rare Disease Phenotyping from Clinical Notes
Computational text phenotyping is the practice of identifying patients w...
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03/21/2022
Automated Clinical Coding: What, Why, and Where We Are?
Clinical coding is the task of transforming medical information in a pat...
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02/15/2022
Knowledge Graph Reasoning with Logics and Embeddings: Survey and Perspective
Knowledge graph (KG) reasoning is becoming increasingly popular in both ...
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12/08/2021
Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings
We have created a knowledge graph based on major data sources used in ec...
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12/05/2021
BERTMap: A BERT-based Ontology Alignment System
Ontology alignment (a.k.a ontology matching (OM)) plays a critical role ...
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07/12/2021
Zero-shot Visual Question Answering using Knowledge Graph
Incorporating external knowledge to Visual Question Answering (VQA) has ...
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06/29/2021
K-ZSL: Resources for Knowledge-driven Zero-shot Learning
External knowledge (a.k.a side information) plays a critical role in zer...
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06/16/2021
PRASEMap: A Probabilistic Reasoning and Semantic Embedding based Knowledge Graph Alignment System
Knowledge Graph (KG) alignment aims at finding equivalent entities and r...
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05/17/2021
OntoEA: Ontology-guided Entity Alignment via Joint Knowledge Graph Embedding
Semantic embedding has been widely investigated for aligning knowledge g...
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05/12/2021
Unsupervised Knowledge Graph Alignment by Probabilistic Reasoning and Semantic Embedding
Knowledge Graph (KG) alignment is to discover the mappings (i.e., equiva...
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02/26/2021
Knowledge-aware Zero-Shot Learning: Survey and Perspective
Zero-shot learning (ZSL) which aims at predicting classes that have neve...
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02/15/2021
OntoZSL: Ontology-enhanced Zero-shot Learning
Zero-shot Learning (ZSL), which aims to predict for those classes that h...
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10/22/2020
An Industry Evaluation of Embedding-based Entity Alignment
Embedding-based entity alignment has been widely investigated in recent ...
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09/30/2020
OWL2Vec*: Embedding of OWL Ontologies
Semantic embedding of knowledge graphs has been widely studied and used ...
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06/30/2020
Ontology-guided Semantic Composition for Zero-Shot Learning
Zero-shot learning (ZSL) is a popular research problem that aims at pred...
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04/07/2020
Generative Adversarial Zero-shot Learning via Knowledge Graphs
Zero-shot learning (ZSL) is to handle the prediction of those unseen cla...
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02/25/2020
Dividing the Ontology Alignment Task with Semantic Embeddings and Logic-based Modules
Large ontologies still pose serious challenges to state-of-the-art ontol...
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01/28/2020
An Internal Clock Based Space-time Neural Network for Motion Speed Recognition
In this work we present a novel internal clock based space-time neural n...
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01/19/2020
Correcting Knowledge Base Assertions
The usefulness and usability of knowledge bases (KBs) is often limited b...
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08/27/2019
Enabling Semantic Data Access for Toxicological Risk Assessment
Experimental effort and animal welfare are concerns when exploring the e...
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08/22/2019
Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning
Relation extraction aims to extract relational facts from sentences. Pre...
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08/22/2019
Improving Few-shot Text Classification via Pretrained Language Representations
Text classification tends to be difficult when the data is deficient or ...
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07/02/2019
Knowledge Graph Embedding for Ecotoxicological Effect Prediction
Exploring the effects a chemical compound has on a species takes a consi...
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06/26/2019
Canonicalizing Knowledge Base Literals
Ontology-based knowledge bases (KBs) like DBpedia are very valuable reso...
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05/31/2019
Augmenting Transfer Learning with Semantic Reasoning
Transfer learning aims at building robust prediction models by transferr...
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05/30/2019
Learning Semantic Annotations for Tabular Data
The usefulness of tabular data such as web tables critically depends on ...
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03/21/2019
Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning
Reasoning is essential for the development of large knowledge graphs, es...
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01/20/2019
Human-centric Transfer Learning Explanation via Knowledge Graph [Extended Abstract]
Transfer learning which aims at utilizing knowledge learned from one pro...
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11/04/2018
ColNet: Embedding the Semantics of Web Tables for Column Type Prediction
Automatically annotating column types with knowledge base (KB) concepts ...
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07/22/2018
Knowledge-based Transfer Learning Explanation
Machine learning explanation can significantly boost machine learning's ...
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04/24/2017
