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COLING
2002

A New Probabilistic Model for Title Generation

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A New Probabilistic Model for Title Generation
Title generation is a complex task involving both natural language understanding and natural language synthesis. In this paper, we propose a new probabilistic model for title generation. Different from the previous statistical models for title generation, which treat title generation as a generation process that converts the `document representation' of information directly into a `title representation' of the same information, this model introduces a hidden state called `information source' and divides title generation into two steps, namely the step of distilling the `information source' from the observation of a document and the step of generating a title from the estimated `information source'. In our experiment, the new probabilistic model outperforms the previous model for title generation in terms of both automatic evaluations and human judgments.
Rong Jin, Alexander G. Hauptmann
Added 17 Dec 2010
Updated 17 Dec 2010
Type Journal
Year 2002
Where COLING
Authors Rong Jin, Alexander G. Hauptmann
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