.../approach In this paper, global vectors (GloVe) and Bidirectional Encoder Representations Transformers (BERT) pre-trained word embedding are used to identify relationships between words, which helps to classify emails into their relevant categories using machine learning and deep learning models. Two...

... embedding techniques. Combining these would aid the best performing collection selection method to speed up retrieval performance of DIR solutions. Design/methodology/approach The authors propose a collection selection model based on word embedding using Word2Vec approach that learns the similarity...

... and phrases. Design/methodology/approach To account for this language use, the authors present domain-specific pre-trained word embeddings for the patent domain. The authors train the model on a very large data set of more than 5m patents and evaluate it at the task of patent classification. To this end...