Koen Dercksen

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it
• Natural Language Processing — 10 citations into it

Whom Koen Dercksen trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. Thomas Hofmann (in Artificial Intelligence)
2. Octavian-Eugen Ganea (in Artificial Intelligence)

Papers from Koen Dercksen's perspective

Ordered by how strongly the researchers Koen Dercksen trusts endorse each paper. Same corpus, a different order for every researcher.

1. GloVe: Global Vectors for Word Representation
2. Learning to link with wikipedia
3. Robust Disambiguation of Named Entities in Text
4. Large-Scale Named Entity Disambiguation Based on Wikipedia Data (Conference on Empirical Methods in Natural Language Processing)
5. Deep Joint Entity Disambiguation with Local Neural Attention
6. Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation
7. Using Encyclopedic Knowledge for Named entity Disambiguation (Conference of the European Chapter of the Association for Computational Linguistics)
8. Improving Entity Linking by Modeling Latent Relations between Mentions
9. Contextual String Embeddings for Sequence Labeling
10. GERBIL - Benchmarking Named Entity Recognition and Linking consistently

Their papers

• REL: An Entity Linker Standing on the Shoulders of Giants (2020) — 152 citations