Professor Enrico Francesconi of Università degli Studi di Firenze Dipartimento di Sistemi e Informatica and ITTIG/CNR will present a paper entitled Legal Rules Learning Based on a Semantic Model for Legislation (for the full text of the paper, click here for the conference proceedings in PDF and scroll down to the page numbered 46) at SPLeT 2010: The 3rd Workshop on Semantic Processing of Legal Texts, to be held 23 May 2010 in Malta.
Here is the abstract of the paper:
Legal rules extraction from legislative texts can be an effective method to make it easier the implementation of rules-based systems for legal assessment and reasoning, as well as for implementing advanced search and retrieval systems for legislative documents. In this paper machine learning and NLP techniques are used for extracting legal rules on the basis of a semantic model for legislative texts, which is oriented to knowledge reusability and sharing. Moreover the identified entities of the regulated domain can be a starting point to a bottom-up implementation of domain ontologies. This approach is aimed at giving a contribution to bridge the gap between consensus and authoritativeness in legal knowledge representation.
Tags: Enrico Francesconi, Extracting legal rules from legal texts, Extracting legal rules from legislation, Knowledge extraction from legal texts, Knowledge extraction from legislation, Legal knowledge extraction, Legal knowledge representation, Legal machine learning, Legal natural language processing, Legal ontologies, Natural language processing and law, SPLeT, SPLeT 2010, Workshop on Semantic Processing of Legal Texts