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Unsupervised automatic keyphrases extraction on Italian datasets

Capitolo di libro
Data di Pubblicazione:
2021
Abstract:
Keyword/keyphrase extraction is an important research activity in text mining, natural language processing, and information retrieval. A large number of algorithms, divided into supervised or unsupervised methods, have been designed and developed to solve the problem of automatic keyphrases extraction. The aim of the chapter is to critically discuss the unsupervised automatic keyphrases extraction algorithms, analyzing in depth their characteristics. The methods presented will be tested on different datasets, presenting in detail the data, the algorithms, and the different options tested in the runs. Moreover, most of the studies and experiments have been conducted on texts in English, while there are few experiments concerning other languages, such as Italian. Particular attention will be paid to the evaluation of the results of the methods in two different languages, English, and Italian.
Tipologia CRIS:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
Unsupervised Automatic keyword Extraction; Natural language processing; Italian dataset
Elenco autori:
Gagliardi, Isabella; Artese, MARIA TERESA
Autori di Ateneo:
ARTESE MARIA TERESA
GAGLIARDI ISABELLA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/401506
Titolo del libro:
Encyclopedia of Information Science and Technology. Fifth edition.
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https://www.igi-global.com/gateway/chapter/260179
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