CINECA IRIS Institutional Research Information System
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishSince most content in Digital Libraries and Archives is text, there is an interest in the application of Natural Language Processing (NLP) to extract valuable information from it in order to support various kinds of user activities. Most NLP techniques exploit linguistic resources that are language-specific, costly and error-prone to produce manually, which motivates research for automatic ways to build them. This paper extends the BLA-BLA tool for learning linguistic resources, adding a Grammar Induction feature based on the advanced process mining and management system WoMan. Experimental results are encouraging, envisaging interesting applications to Digital Libraries and motivating further research aimed at extracting an explicit grammar from the learned models.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
| Titolo: | Towards a Process Mining Approach to Grammar Induction for Digital Libraries |
| Autori: | ANGELASTRO, SERGIO (Corresponding) |
| Data di pubblicazione: | 2019 |
| Abstract: | Since most content in Digital Libraries and Archives is text, there is an interest in the application of Natural Language Processing (NLP) to extract valuable information from it in order to support various kinds of user activities. Most NLP techniques exploit linguistic resources that are language-specific, costly and error-prone to produce manually, which motivates research for automatic ways to build them. This paper extends the BLA-BLA tool for learning linguistic resources, adding a Grammar Induction feature based on the advanced process mining and management system WoMan. Experimental results are encouraging, envisaging interesting applications to Digital Libraries and motivating further research aimed at extracting an explicit grammar from the learned models. |
| Handle: | http://hdl.handle.net/11586/225926 |
| ISBN: | 978-3-030-11225-7 978-3-030-11226-4 |
| Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
File in questo prodotto:
Copyright © 2020