Clustering Text Using Attention
This addresses text clustering for NLP researchers, but it appears incremental as it adapts existing attention mechanisms to a new task without demonstrated broad impact.
The paper tackles the problem of text clustering in NLP by proposing a novel technique using attention mechanisms, which extends attention to clustering and opens a new research area, though no concrete performance numbers are provided.
Clustering Text has been an important problem in the domain of Natural Language Processing. While there are techniques to cluster text based on using conventional clustering techniques on top of contextual or non-contextual vector space representations, it still remains a prevalent area of research possible to various improvements in performance and implementation of these techniques. This paper discusses a novel technique to cluster text using attention mechanisms. Attention Mechanisms have proven to be highly effective in various NLP tasks in recent times. This paper extends the idea of attention mechanism in clustering space and sheds some light on a whole new area of research