Márton Makrai conducts computational semantic research, and he is as a junior research fellow at the MTA Research Institute for Cognitive Neuroscience and Psychology. His main field of interest is machine learning of word ambiguity.
The Hungarian version of this page may be more clear for people who are unfamiliar with natural language processing, but speak Hungarian.
Currently, he writes the last chapter of his dissertation at the MTA-ELTE theoretical linguistics program. The chapter links together his two major topics so far, verbal roles and linear algebraic models. Further topics:
- the 4lang semantic network: gold meaning representations of the defining vocabulary, deep cases, spreading activation, and identifying the defining vocabulary with IR and lexicography.
- semantic granularity of multi-sense word embeddings
- hypernyms with sparse word representations, winning some categories at the SemEval 2018 task.
- word translation: combining the method of triangulation with the linear mapping of vectors -- German--Hungarian word pairs with confidence scores
- Hungarian equivalents of the analogy question set for evaluating embeddings
- multilingual sentence clustering for the CoALa project
- young researcher (2015--2018, MTA NYI)
- master's thesis on a mathematical model of language acquisition (identification in the limit)