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CLT seminar: Mikael Kågebäck - Automatic Summarization using Continuous Vector Space Models

SEMINAR

Automatic summarization can help users extract the most important pieces of information from the vast amount of text digitized into electronic form everyday. Central to automatic summarization is the notion of similarity between sentences. We propose the use of continuous vector representations for semantically aware representations of sentences as a basis for measuring similarity. The approach is evaluated on a standard dataset using the ROUGE evaluation measures. Our experiments show that this method improves performance of a state-of-the-art summarization framework and strongly indicate the benefits of continuous word vector representations for automatic summarization.

Date: 2014-03-06 10:30 - 11:30

Location: L308, Lennart Torstenssonsgatan 8

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Page updated: 2014-03-03 09:38

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