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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/8223
Title: Catchphrase Extraction from Legal Documents Using LSTM Networks
Authors: Sharma, Yashvardhan
Keywords: Computer Science
Keyword Extraction
Legal Documents
Deep Learning
LSTM
Natural Language Processing
Issue Date: Dec-2017
Publisher: CEUR
Abstract: Legal texts usually have a complex structure and reading through them is a time-consuming and strenuous task. Hence it is essential to provide the legal practitioners a concise representation of the text. Catchphrases are those phrases which state the important issues present in the text, thus effectively characterizing it. This paper proposes an approach for the subtask 1 of the task IRLed (Information Retrieval from Legal Documents), FIRE 2017. The proposed algorithm uses a three step approach for extracting catchphrases from legal documents.
URI: https://ceur-ws.org/Vol-2036/T3-3.pdf
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8223
Appears in Collections:Department of Computer Science and Information Systems

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