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

Understand

Answering complex logical queries on large-scale incomplete knowledge graphs (KGs) is a fundamental yet challenging task.

• Recently, a promising approach to this problem has been to embed KG entities as well as the query into a vector space such that entities that answer the query are embedded close to the query.
• However, prior work models queries as single points in the vector space, which is problematic because a complex query represents a potentially large set of its answer entities, but it is unclear how such a set can be represented as a single point.
• Furthermore, prior work can only handle queries that use conjunctions ($\wedge$) and existential quantifiers ($\exists$).