A Pattern to Align Them All: Integrating Different Modalities to Define Multi-Modal Entities
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Abstract (arXiv)
The ability to reason with and integrate different sensory inputs is the foundation underpinning human intelligence and it is the reason for the growing interest in modelling multi-modal information within Knowledge Graphs. Multi-Modal Knowledge Graphs extend traditional Knowledge Graphs by associating an entity with its possible modal representations, including text, images, audio, and videos, all of which are used to convey the semantics of the entity. Despite the increasing attention that Multi-Modal Knowledge Graphs have received, there is a lack of consensus about the definitions and modelling of modalities, whose definition is often determined by application domains. In this paper, we propose a novel ontology design pattern that captures the separation of concerns between an entity (and the information it conveys), whose semantics can have different manifestations across different media, and its realisation in terms of a physical information entity. By introducing this abstract model, we aim to facilitate the harmonisation and integration of different existing multi-modal ontologies which is crucial for many intelligent applications across different domains spanning from medicine to digital humanities.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 55 references that are in the map. First posted on arXiv 17 Oct 2024.
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References · 14
- 201912-in-1: Multi-Task Vision and Language Representation Learningcited by 278
- 2020Counterfactual VQA: A Cause-Effect Look at Language Biascited by 266
- 2020When Radiology Report Generation Meets Knowledge Graphcited by 145
- 2019Multimodal Intelligence: Representation Learning, Information Fusion, and Applicationscited by 89
- 2022Multi-Modal Knowledge Graph Construction and Application: A Surveycited by 74
- 2024Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Surveycited by 53
- 2018Embedding Multimodal Relational Data for Knowledge Base Completioncited by 34
- 2021Boosting Entity-aware Image Captioning with Multi-modal Knowledge Graphcited by 31
- 2018Entity-aware Image Caption Generationcited by 26
- 2019Multi-modality Latent Interaction Network for Visual Question Answeringcited by 23
- 2021Plot and Rework: Modeling Storylines for Visual Storytellingcited by 14
- 2021Automatic Modeling of Social Concepts Evoked by Art Images as Multimodal Framescited by 4
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