LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals

04/28/2023
by   Caglar Demir, et al.
0

Most real-world knowledge graphs, including Wikidata, DBpedia, and Yago are incomplete. Answering queries on such incomplete graphs is an important, but challenging problem. Recently, a number of approaches, including complex query decomposition (CQD), have been proposed to answer complex, multi-hop queries with conjunctions and disjunctions on such graphs. However, all state-of-the-art approaches only consider graphs consisting of entities and relations, neglecting literal values. In this paper, we propose LitCQD – an approach to answer complex, multi-hop queries where both the query and the knowledge graph can contain numeric literal values: LitCQD can answer queries having numerical answers or having entity answers satisfying numerical constraints. For example, it allows to query (1) persons living in New York having a certain age, and (2) the average age of persons living in New York. We evaluate LitCQD on query types with and without literal values. To evaluate LitCQD, we generate complex, multi-hop queries and their expected answers on a version of the FB15k-237 dataset that was extended by literal values.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/27/2022

Query2Particles: Knowledge Graph Reasoning with Particle Embeddings

Answering complex logical queries on incomplete knowledge graphs (KGs) w...
research
08/12/2023

Approximate Answering of Graph Queries

Knowledge graphs (KGs) are inherently incomplete because of incomplete w...
research
06/17/2023

Query2GMM: Learning Representation with Gaussian Mixture Model for Reasoning over Knowledge Graphs

Logical query answering over Knowledge Graphs (KGs) is a fundamental yet...
research
07/04/2018

Feature-based reformulation of entities in triple pattern queries

Knowledge graphs encode uniquely identifiable entities to other entities...
research
05/02/2022

Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs

Multi-hop reasoning over real-life knowledge graphs (KGs) is a highly ch...
research
07/29/2020

How and Why is An Answer (Still) Correct? Maintaining Provenance in Dynamic Knowledge Graphs

Knowledge graphs (KGs) have increasingly become the backbone of many cri...
research
02/22/2021

Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification

Large, heterogeneous datasets are characterized by missing or even erron...

Please sign up or login with your details

Forgot password? Click here to reset