no code implementations • 25 Sep 2019 • Yeabsira Asefa Ashengo, Rosa Tsegaye Aga, Surafel Lemma Abebe
The current approaches for machine translation usually require large set of parallel corpus in order to achieve fluency like in the case of neural machine translation (NMT), statistical machine translation (SMT) and example-based machine translation (EBMT).
no code implementations • WS 2016 • Christian Wartena, Rosa Tsegaye Aga
The CogALex-V Shared Task provides two datasets that consists of pairs of words along with a classification of their semantic relation.
no code implementations • COLING 2016 • Rosa Tsegaye Aga, Lucas Drumond, Christian Wartena, Lars Schmidt-Thieme
Thus we show, that MRMF provides an interesting approach for building semantic classifiers that (1) gives better results than unsupervised approaches based on vector similarity, (2) gives similar results as other supervised methods and (3) can naturally be extended with other sources of information in order to improve the results.
no code implementations • LREC 2016 • Rosa Tsegaye Aga, Christian Wartena, Lucas Drumond, Lars Schmidt-Thieme
The similarity of words can be computed by comparing their feature vectors.