Sentence Extraction for Legal Text Summarisation
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 1686-1686.
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.
Ben Hachey, and Claire Grover. 2005. Sentence Extraction for Legal Text Summarisation. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05. IJCAI, 1686–1686. https://ijcai.org/proceedings/2005/328
Hachey, B., & Grover, C. (2005). Sentence Extraction for Legal Text Summarisation. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 (pp. 1686–1686). IJCAI. https://ijcai.org/proceedings/2005/328
@inproceedings{ijcai2005p328,
title = {Sentence Extraction for Legal Text Summarisation},
author = {Hachey, Ben and Grover, Claire},
booktitle = {Proceedings of the Nineteenth International Joint Conference on
Artificial Intelligence, {IJCAI-05}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {1686--1686},
year = {2005},
url = {https://ijcai.org/proceedings/2005/328},
}
TY - CPAPER TI - Sentence Extraction for Legal Text Summarisation AU - Hachey, Ben AU - Grover, Claire T2 - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 PB - International Joint Conferences on Artificial Intelligence PY - 2005 SP - 1686 EP - 1686 UR - https://ijcai.org/proceedings/2005/328 ER -Copied
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