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.
Towards a Process Mining Approach to Grammar Induction for Digital Libraries
Ferilli, Stefano
;Angelastro, Sergio
2019-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
