Summarization Based on Embedding Distributions

  title={Summarization Based on Embedding Distributions},
  author={Hayato Kobayashi and Masaki Noguchi and Taichi Yatsuka},
In this study, we consider a summarization method using the document level similarity based on embeddings, or distributed representations of words, where we assume that an embedding of each word can represent its “meaning.” We formalize our task as the problem of maximizing a submodular function defined by the negative summation of the nearest neighbors’ distances on embedding distributions, each of which represents a set of word embeddings in a document. We proved the submodularity of our… CONTINUE READING