Viet Phung
ABSTRACT
Automatic text summarization is the process of automatically reducing the length of documents without losing the primary ideas. Due to the flood of digital text-based information, there is a great demand for summarization systems. In this paper, we investigate a number of word-embedding based approaches for sentence representation which are combined with the PageRank algorithm to select sentences for summary construction. We compare these new methods with a range of other current approaches to summarization. While the same summarization approaches can generally be applied across different languages, we target Vietnamese because of the relative lack of previous work in this space and also because it provides a good example of a language which generally requires word segmentation. Our experiments find that a word-embedding and graph based approach is an effective strategy for Vietnamese summarization and that word segmentation is not necessary for achieving good summarization results.
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Index Terms
- A Study on the Use of Word Embeddings and PageRank for Vietnamese Text Summarization
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