Keyphrase Generation: A Text Summarization Struggle

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10405617" target="_blank" >RIV/00216208:11320/19:10405617 - isvavai.cz</a>

Result on the web

<a href="https://www.aclweb.org/anthology/N19-1070" target="_blank" >https://www.aclweb.org/anthology/N19-1070</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.18653/v1/N19-1070" target="_blank" >10.18653/v1/N19-1070</a>

Result language

angličtina

Original language name

Keyphrase Generation: A Text Summarization Struggle

Original language description

Authors&apos; keyphrases assigned to scientific articles are essential for recognizing content and topic aspects. Most of the proposed supervised and unsupervised methods for keyphrase generation are unable to produce terms that are valuable but do not appear in the text. In this paper, we explore the possibility of considering the keyphrase string as an abstractive summary of the title and the abstract. First, we collect, process and release a large dataset of scientific paper metadata that contains 2.2 million records. Then we experiment with popular text summarization neural architectures. Despite using advanced deep learning models, large quantities of training data and many days of computation, our systematic evaluation on four test datasets reveals that the explored text summarization methods could not produce better keyphrases than the much simpler unsupervised methods or the existing supervised ones.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

The 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

ISBN

978-1-950737-13-0

ISSN

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e-ISSN

—

Number of pages

7

Pages from-to

666-672

Publisher name

NAACL-HLT 2019

Place of publication

Minneapolis, USA

Event location

Minneapolis, USA

Event date

Jun 2, 2019

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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