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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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