Analyzing Parallelism and Domain Similarities in the MAREC Patent Corpus

By Katharina Wäschle, Stefan Riezler. 2012

29 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology, Natural Language Processing, Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Ondrej Bojar
2. Philipp Koehn
3. Lucia Specia
4. Graham Neubig
5. Barry Haddow
6. Rico Sennrich
7. Felix Stahlberg
8. Ondrej Dusek

In Molecular Biology

1. Lucia Specia
2. Ondrej Bojar
3. Philipp Koehn
4. Ondrej Dusek
5. Barry Haddow
6. Christof Monz
7. Matt Post
8. Yvette Graham

In Natural Language Processing

1. Ondrej Bojar
2. Philipp Koehn
3. Lucia Specia
4. Barry Haddow
5. Ondrej Dusek
6. Matt Post
7. Christof Monz
8. Graham Neubig

In Evaluation & Benchmarks

1. Ondrej Bojar
2. Philipp Koehn
3. Lucia Specia
4. Barry Haddow
5. Matt Post
6. Christian Federmann
7. Yvette Graham
8. Ondrej Dusek

Citations in the corpus

• Findings of the 2014 Workshop on Statistical Machine Translation (2014, methodology): “COPPA (Corpus of Parallel Patent Applications (Pouliquen and Mazenc, 2011) is a French–English parallel corpus extracted from the MAREC patent collection (W¨aschle and Riezler, 2012).”
• Adaptation of machine translation for multilingual information retrieval in the medical domain (2014, methodology): “5 million sentence pairs is extracted from PatTR, a parallel corpus extracted from the MAREC patent collection [57].”