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.
Attached file is an example of the program created by former programmer and it needs your expertise and improvement to enhance its accuracy.
NLP, Data Science, short text classification, Python, Java
33 фрилансеров(-а) в среднем готовы выполнить эту работу за $574
Good day Me and my team can deliver your tasks with great quality We are working on hourly rate 35usd / hour. Contact me for an enjoyable and reliable development experience. Thank you.
Hello John, I am familiar with word embedding models and also algorithms like KNN, cosine, jaccard similarities... Message me to discuss your project futher. thanks