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sorry for a few minutes delay so as you probably can already figure out this talk will be about word embeddings for specific domains so yeah letamp;#39;s dive right in why do we need word embeddings for specific domains well there are really great word embeddings or models to generate word embeddings but they are generated on corp that are as large as possible so they cover every domain possible youamp;#39;ve got two problems and two main problems and the first is words are ambiguous meaning that they have multiple meanings and for a domain in a specific domain you might only be interested in one of those senses one of those meanings of those words so how can you push those word factors toward towards that meaning or extract up meaning and the second major problem is that you usually have a terminology in your specific domain meaning that you have terms that if you use a general word corpus and look at the most frequently used words and base your vocabulary on that you miss t