How can catchy titles be generated without loss of informativeness? - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier Access content directly
Journal Articles Expert Systems with Applications Year : 2014

How can catchy titles be generated without loss of informativeness?

Abstract

Automatic titling of text documents is an essential task for several applications (automatic heading of e-mails, summarization, and so forth). This paper describes a system facilitating information retrieval in a set of textual documents by tackling the automatic titling and subtitling issue. Automatic titling here involves providing both informative and catchy titles. We thus propose two different approaches based on NLP, text mining, and Web Mining techniques. The first one (POSTIT) consists of extracting relevant noun phrases from texts as candidate titles. An original approach combining statistical criteria and noun phrase positions in the text helps in collecting informative titles and subtitles. The second approach (NOMIT) is based on various assumptions made on POSTIT and aims to generate both informative and catchy titles. Both approaches are applied to a corpus of news articles, then evaluated according to two criteria, i.e. informativeness and catchiness.
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Dates and versions

lirmm-00856372 , version 1 (09-09-2013)

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Cédric Lopez, Violaine Prince, Mathieu Roche. How can catchy titles be generated without loss of informativeness?. Expert Systems with Applications, 2014, 41 (4), pp.1051-1062. ⟨10.1016/j.eswa.2013.07.102⟩. ⟨lirmm-00856372⟩
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