Knowledge graph-based document embedding enrichmentKoloski, Boshko (Avtor) Robnik Šikonja, Marko (Mentor) Škrlj, Blaž (Komentor) knowledge graphsword embeddingknowledge graph embeddingnatural language processingStructured and unstructured textual data requires efficient representation for computation and manipulation. Many different methods have been developed to represent text in numerical form. Some of these methods are based only on statistical metrics, and some introduce the concept of word context. Structured textual data about concepts and entities is stored in knowledge graphs for which different numerical representations have been developed. By using the facts about concepts, semantics can be introduced into the representation of documents. We propose an approach that merges the knowledge base induced numerical representation of texts and entities that appear in the texts, induced from knowledge bases. We analyze the proposed method using two use cases. The results show that the use of external knowledge significantly improves the performance of machine learning models. We show that the proposed method outperforms non-enriched representations.20202020-09-10 17:45:00Diplomsko delo/naloga119701sl