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Rethinking complex queries on knowledge graphs with neural link predictors
Reasoning on knowledge graphs is a challenging task because it utilizes observed
information to predict the missing one. Particularly, answering complex queries based on …
information to predict the missing one. Particularly, answering complex queries based on …
Advancing abductive reasoning in knowledge graphs through complex logical hypothesis generation
Abductive reasoning is the process of making educated guesses to provide explanations for
observations. Although many applications require the use of knowledge for explanations …
observations. Although many applications require the use of knowledge for explanations …
Top Ten Challenges Towards Agentic Neural Graph Databases
Graph databases (GDBs) like Neo4j and TigerGraph excel at handling interconnected data
but lack advanced inference capabilities. Neural Graph Databases (NGDBs) address this by …
but lack advanced inference capabilities. Neural Graph Databases (NGDBs) address this by …
Understanding inter-session intentions via complex logical reasoning
Understanding user intentions is essential for improving product recommendations,
navigation suggestions, and query reformulations. However, user intentions can be intricate …
navigation suggestions, and query reformulations. However, user intentions can be intricate …