Ontotext | Semantic Technology Developer(About) > Ontotext transforms how organizations **identify meaning across** diverse databases and massive amounts of unstructured data by **combining a semantic graph database with text mining, and machine learning**.
Traversing Knowledge Graphs in Vector Space (2015)(About) Knowledge graphs often have missing facts (edges) which disrupts path queries. Recent models for knowledge base completion impute missing facts by embedding knowledge graphs in vector spaces. We show that these models can be recursively applied to answer path queries, but that they suffer from cascading errors. This motivates a new "compositional" training objective, which dramatically improves all models' ability to answer path queries, in some cases more than doubling accuracy.