How can catchy titles be generated without loss of informativeness?

Lopez Cédric, Prince Violaine, Roche Mathieu. 2014. How can catchy titles be generated without loss of informativeness?. Expert Systems with Applications, 41 (4) : 1051-1062.

Quartile : Q1, Sujet : OPERATIONS RESEARCH & MANAGEMENT SCIENCE / Quartile : Q1, Sujet : ENGINEERING, ELECTRICAL & ELECTRONIC / Quartile : Q1, Sujet : COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Economie-gestion

Résumé : 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.

Classification Agris : C30 - Documentation et information
000 - Autres thèmes

Champ stratégique Cirad : Hors axes (2014-2018)

Auteurs et affiliations

• Lopez Cédric, VISEO (FRA)
• Prince Violaine, LIRMM (FRA)
• Roche Mathieu, CIRAD-ES-UMR TETIS (FRA) ORCID: 0000-0003-3272-8568

Source : Cirad - Agritrop (https://agritrop.cirad.fr/571379/)

Métriques

[ Page générée et mise en cache le 2024-01-06 ]