As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
This work presents a parsing approach able to extract relevant knowledge from judgements. It is based on finite state automata and Hidden Markov Models, as a compromise solution between NLP and machine learning approaches for case texts parsing. The approach is tested on a dataset of Italian court decisions to provide a support to their automatic structuring and semantic indexing.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.