Abstract
This paper presents an approach towards using both incoming and outgoing citation information for document summarisation. Our work aims at generating automatically catchphrases for legal case reports, using, beside the full text, also the text of cited cases and cases that cite the current case. We propose methods to use catchphrases and sentences of cited/citing cases to extract catchphrases from the text of the target case. We created a corpus of cases, catchphrases and citations, and performed a ROUGE based evaluation, which shows the superiority of our citation-based methods over full-text-only methods.
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Galgani, F., Compton, P., Hoffmann, A. (2012). Citation Based Summarisation of Legal Texts. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_6
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DOI: https://doi.org/10.1007/978-3-642-32695-0_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32694-3
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