Machine knowledge: Creation and curation of comprehensive knowledge bases
Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
relationships has been a longstanding goal of AI. Over the last decade, large-scale …
Knowledge graph quality management: a comprehensive survey
B Xue, L Zou - IEEE Transactions on Knowledge and Data …, 2022 - ieeexplore.ieee.org
As a powerful expression of human knowledge in a structural form, knowledge graph (KG)
has drawn great attention from both the academia and the industry and a large number of …
has drawn great attention from both the academia and the industry and a large number of …
Personal knowledge graphs: A research agenda
Knowledge graphs, organizing structured information about entities, and their attributes and
relationships, are ubiquitous today. Entities, in this context, are usually taken to be anyone or …
relationships, are ubiquitous today. Entities, in this context, are usually taken to be anyone or …
Knowledge graph completeness: A systematic literature review
The quality of a Knowledge Graph (also known as Linked Data) is an important aspect to
indicate its fitness for use in an application. Several quality dimensions are identified, such …
indicate its fitness for use in an application. Several quality dimensions are identified, such …
Degree-aware alignment for entities in tail
Entity alignment (EA) is to discover equivalent entities in knowledge graphs (KGs), which
bridges heterogeneous sources of information and facilitates the integration of knowledge …
bridges heterogeneous sources of information and facilitates the integration of knowledge …
What we talk about when we talk about Wikidata quality: a literature survey
Launched in 2012, Wikidata has already become a success story. It is a collaborative
knowledge graph, whose large community has produced so far data about more than 55 …
knowledge graph, whose large community has produced so far data about more than 55 …
Uncommonsense: Informative negative knowledge about everyday concepts
Commonsense knowledge about everyday concepts is an important asset for AI
applications, such as question answering and chatbots. Recently, we have seen an …
applications, such as question answering and chatbots. Recently, we have seen an …
Finetuning generative large language models with discrimination instructions for knowledge graph completion
Traditional knowledge graph (KG) completion models learn embeddings to predict missing
facts. Recent works attempt to complete KGs in a text-generation manner with large …
facts. Recent works attempt to complete KGs in a text-generation manner with large …
Completeness-aware rule learning from knowledge graphs
Abstract Knowledge graphs (KGs) are huge collections of primarily encyclopedic facts. They
are widely used in entity recognition, structured search, question answering, and other …
are widely used in entity recognition, structured search, question answering, and other …
Mirai: Evaluating llm agents for event forecasting
Recent advancements in Large Language Models (LLMs) have empowered LLM agents to
autonomously collect world information, over which to conduct reasoning to solve complex …
autonomously collect world information, over which to conduct reasoning to solve complex …