angelosalatino/cso-classifier: CSO Classifier v2.1

The CSO Classifier is an application that takes as input the text from abstract, title, and keywords of a research paper and outputs a list of relevant concepts from CSO. This new release (version v2.1) aims at improving its scalability. Compared to its previous version (v2.0), the classifier relies on a cached word2vec model which connects the words within the model vocabulary directly with the CSO topics. Thanks to this cache, the classifier is able to quickly retrieve all CSO topics that could be inferred by given tokens, speeding up the processing time. In addition, this cache is lighter (~64M) compared to the actual word2vec model (~366MB), which allows to save additional time at loading time. Thanks to this improvement the CSO Classifier is around 24x faster and can be easily run on large corpus of scholarly data