Knowledge graphs meet multi-modal learning: A comprehensive survey
Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …
semantic web community's exploration into multi-modal dimensions unlocking new avenues …
A survey of knowledge graph reasoning on graph types: Static, dynamic, and multi-modal
Knowledge graph reasoning (KGR), aiming to deduce new facts from existing facts based on
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …
Recent developments in recommender systems: A survey
In this technical survey, the latest advancements in the field of recommender systems are
comprehensively summarized. The objective of this study is to provide an overview of the …
comprehensively summarized. The objective of this study is to provide an overview of the …
Meaformer: Multi-modal entity alignment transformer for meta modality hybrid
Multi-modal entity alignment (MMEA) aims to discover identical entities across different
knowledge graphs (KGs) whose entities are associated with relevant images. However …
knowledge graphs (KGs) whose entities are associated with relevant images. However …
Attribute-consistent knowledge graph representation learning for multi-modal entity alignment
The multi-modal entity alignment (MMEA) aims to find all equivalent entity pairs between
multi-modal knowledge graphs (MMKGs). Rich attributes and neighboring entities are …
multi-modal knowledge graphs (MMKGs). Rich attributes and neighboring entities are …
Rethinking uncertainly missing and ambiguous visual modality in multi-modal entity alignment
As a crucial extension of entity alignment (EA), multi-modal entity alignment (MMEA) aims to
identify identical entities across disparate knowledge graphs (KGs) by exploiting associated …
identify identical entities across disparate knowledge graphs (KGs) by exploiting associated …
Relation-enhanced negative sampling for multimodal knowledge graph completion
Knowledge Graph Completion (KGC), aiming to infer the missing part of Knowledge Graphs
(KGs), has long been treated as a crucial task to support downstream applications of KGs …
(KGs), has long been treated as a crucial task to support downstream applications of KGs …
Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation
In the realm of deep learning-based recommendation systems, the increasing computational
demands, driven by the growing number of users and items, pose a significant challenge to …
demands, driven by the growing number of users and items, pose a significant challenge to …
Sgaligner: 3d scene alignment with scene graphs
Building 3D scene graphs has recently emerged as a topic in scene representation for
several embodied AI applications to represent the world in a structured and rich manner …
several embodied AI applications to represent the world in a structured and rich manner …
Mmiea: Multi-modal interaction entity alignment model for knowledge graphs
Fusing data from different sources to improve decision making in smart cities has received
increasing attention. Collected data through sensors usually exist in a multi-modal form …
increasing attention. Collected data through sensors usually exist in a multi-modal form …