Knowledge graphs: Opportunities and challenges
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally
important to organize and represent the enormous volume of knowledge appropriately. As …
important to organize and represent the enormous volume of knowledge appropriately. As …
Graph neural networks in recommender systems: a survey
With the explosive growth of online information, recommender systems play a key role to
alleviate such information overload. Due to the important application value of recommender …
alleviate such information overload. Due to the important application value of recommender …
Unifying large language models and knowledge graphs: A roadmap
Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …
field of natural language processing and artificial intelligence, due to their emergent ability …
A survey on accuracy-oriented neural recommendation: From collaborative filtering to information-rich recommendation
Influenced by the great success of deep learning in computer vision and language
understanding, research in recommendation has shifted to inventing new recommender …
understanding, research in recommendation has shifted to inventing new recommender …
Multi-modal knowledge graph construction and application: A survey
Recent years have witnessed the resurgence of knowledge engineering which is featured
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …
Hybrid transformer with multi-level fusion for multimodal knowledge graph completion
Multimodal Knowledge Graphs (MKGs), which organize visual-text factual knowledge, have
recently been successfully applied to tasks such as information retrieval, question …
recently been successfully applied to tasks such as information retrieval, question …
Multi-modal self-supervised learning for recommendation
The online emergence of multi-modal sharing platforms (eg, TikTok, Youtube) is powering
personalized recommender systems to incorporate various modalities (eg, visual, textual …
personalized recommender systems to incorporate various modalities (eg, visual, textual …
Mukea: Multimodal knowledge extraction and accumulation for knowledge-based visual question answering
Abstract Knowledge-based visual question answering requires the ability of associating
external knowledge for open-ended cross-modal scene understanding. One limitation of …
external knowledge for open-ended cross-modal scene understanding. One limitation of …
Multi-modal graph contrastive learning for micro-video recommendation
Recently micro-videos have become more popular in social media platforms such as TikTok
and Instagram. Engagements in these platforms are facilitated by multi-modal …
and Instagram. Engagements in these platforms are facilitated by multi-modal …
Multi-modal siamese network for entity alignment
The booming of multi-modal knowledge graphs (MMKGs) has raised the imperative demand
for multi-modal entity alignment techniques, which facilitate the integration of multiple …
for multi-modal entity alignment techniques, which facilitate the integration of multiple …