I'm looking for NLP expert who can create an efficient Chinese and English language Question and Answer system based on short text similarity algorithm, using tensorflow or keras K-means to create clusters to enhance accuracy. Each question submitted by users should be given a score from 0 to 1 based on its similarity rate to the original set of questions.
The script should be in python that can run on server side.
More details will be share via private message.
You must have experience with natural language processing and familiar with popular off-the-shelf word embedding models such as Word2Vec (by Google), GloVe (by Stanford) or fastText (by Facebook) and open source language resources in GitHub pre-trained multilingual language models and other related NLP online resources downloadable to our server.