We propose a novel generative model to explore both local and global context for joint
learning topics and topic-specific word embeddings. In particular, we assume that global …

Throughout history, texts have been essential in communication between humans and
machines, as well as among humans themselves. Texts are used for multiple purposes …

Combining topic discovery with topic-specific word embeddings is a popular, powerful
method for text mining in a small collection of documents. However, the existing researches …

Definition modeling is a recently-introduced task in natural language processing (NLP)
which aims to predict and generate dictionary-style definitions for any given word. Most prior …

In this work 1 we investigate Natural Language Representations by two different points of
view cognitive neuroscience and topic modelling. For the evaluation of each approach, we …