{"type":"ScholarlyArticle","title":"Sentence Extraction for Legal Text Summarisation","authors":[{"name":"Ben Hachey","slug":"ben-hachey","given":"Ben","family":"Hachey","affiliation":""},{"name":"Claire Grover","slug":"claire-grover","given":"Claire","family":"Grover","affiliation":""}],"abstract":"We describe a system for generating extractive summaries of texts in the legal domain, focusing on the relevance classifier, which determines which sentences are abstract-worthy. We experiment with na ̈ıve Bayes and maximum entropy estimation toolkits and explore methods for selecting abstract-worthy sentences in rank order. Evaluation using standard accuracy measures and using correlation confirm the utility of our approach, but suggest different optimal configurations.","doi":null,"url":"https://ijcai.org/proceedings/2005/328","pdf":"https://ijcai.org/proceedings/2005/0328.pdf","markdown":"https://ijcai.org/proceedings/2005/328.md","bibtex":"https://ijcai.org/proceedings/2005/bibtex/328","volume":{"slug":"2005","title":"Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2005","url":"https://ijcai.org/proceedings/2005/","year":2005,"location":"Edinburgh, Scotland, UK","dates":"","editors":"","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":328,"pages":{"first":1686,"last":1686},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}