In the last few blogs I have shown how the NLP techniques or Topic Modelling and Word2Vec can be used in literature review by grouping relevant articles together and narrow down the number of articles that are relevant and needs to be analysed. In this final blog of the series, I will show how toContinue reading “COVID-19 Literature Review using NLP – Part #4 Summarising Articles”
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COVID-19 Literature Review using NLP – Part #2 TF-IDF and Word Vectors
In the last blog I have showed how to use topic modelling to seperate a large number of articles into different topics. In this blog, I am going to talk about how to take one step further, and use word vectors and clustering to track down the articles that you really need. Recall from theContinue reading “COVID-19 Literature Review using NLP – Part #2 TF-IDF and Word Vectors”
COVID-19 Literature Review using Natural Language Process – Part #1 Topic Modelling
Ask any PhD students and they will tell you that literature review is a daunting task. Sifting through mountains of papers to find the specific information that you need is no easy feat, especially there are often conflicting information, and worse, abstracts that looks promising but nothing of interest actually offer in the full-text. ThereContinue reading “COVID-19 Literature Review using Natural Language Process – Part #1 Topic Modelling”
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