Reasoning over Multi-view Knowledge Graphs

by   Zhaohan Xi, et al.

Recently, knowledge representation learning (KRL) is emerging as the state-of-the-art approach to process queries over knowledge graphs (KGs), wherein KG entities and the query are embedded into a latent space such that entities that answer the query are embedded close to the query. Yet, despite the intensive research on KRL, most existing studies either focus on homogenous KGs or assume KG completion tasks (i.e., inference of missing facts), while answering complex logical queries over KGs with multiple aspects (multi-view KGs) remains an open challenge. To bridge this gap, in this paper, we present ROMA, a novel KRL framework for answering logical queries over multi-view KGs. Compared with the prior work, ROMA departs in major aspects. (i) It models a multi-view KG as a set of overlaying sub-KGs, each corresponding to one view, which subsumes many types of KGs studied in the literature (e.g., temporal KGs). (ii) It supports complex logical queries with varying relation and view constraints (e.g., with complex topology and/or from multiple views); (iii) It scales up to KGs of large sizes (e.g., millions of facts) and fine-granular views (e.g., dozens of views); (iv) It generalizes to query structures and KG views that are unobserved during training. Extensive empirical evaluation on real-world KGs shows that significantly outperforms alternative methods.


NQE: N-ary Query Embedding for Complex Query Answering over Hyper-relational Knowledge Graphs

Complex query answering (CQA) is an essential task for multi-hop and log...

EFO_k-CQA: Towards Knowledge Graph Complex Query Answering beyond Set Operation

To answer complex queries on knowledge graphs, logical reasoning over in...

Towards Robust Reasoning over Knowledge Graphs

Answering complex logical queries over large-scale knowledge graphs (KGs...

Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings

Answering complex logical queries on large-scale incomplete knowledge gr...

Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts

Many large-scale knowledge bases simultaneously represent two views of k...

Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs

Knowledge Graphs (KGs) are ubiquitous structures for information storage...

SOFOS: Demonstrating the Challenges of Materialized View Selection on Knowledge Graphs

Analytical queries over RDF data are becoming prominent as a result of t...

Please sign up or login with your details

Forgot password? Click here to reset