2023年5月15日 · Current Multimodal Knowledge Graph Construction (MKGC) models struggle with the real-world dynamism of continuously emerging entities and relations, often …

2024年10月7日 · 多模态知识图构建（mkgc）涉及使用多种模态（例如文本和图像）创建实体和关系的结构化表示。 然而，现有的 MKGC 模型在处理动态现实场景中添加新实体和关系时面临 …

2022年10月17日 · In this paper, we propose MoSE, a Modality Split representation learning and Ensemble inference framework for MKGC. Specifically, in the training phase, we learn …

如下图所示，本文提出的MKGformer模型具有统一的多模态KGC框架。 主要包括混合 Transformer 架构和特定任务范式。 具体来说，MKGformer分别采用 ViT 和 BERT 作为视觉Transformer和 …

2024年10月19日 · mkgc的目标是预测候选三元组对mkg正确的概率。该方法可应用于基于信号的轴承故障mkg进行故障诊断。现有的技术目前忽略了不同阶域的不同重要性。提出了一种基 …

Code and dataset for IJCAI 2024 paper Continual Multimodal Knowledge Graph Construction. 1. Overview. Please note "we provide". This is the data set of lifelong benchmark provided by us.

2024年6月26日 · Multilingual Knowledge Graph Completion (mKGC) aim at solving queries like (h, r, ?) in different languages by reasoning a tail entity t thus improving multilingual knowledge …

In this work, we introduce a Unified Multi-Modal Knowledge Graph (MMKG) Representation Framework that incorporates tailored training objectives for Multi-modal Knowledge Graph …

To address the aforementioned challenges, we proposed a novel model named SCI-MKGC, which is a MKGC method based on spatial context enhancement and cross-modal interaction …

2020年6月25日 · To tackle this challenging problem, this article proposes a new MKGC method to learn a consensus affinity graph directly. By using the self-expressiveness graph learning and …