Catchphrase Extraction from Legal Documents Using LSTM Networks
| dc.contributor.author | Sharma, Yashvardhan | |
| dc.date.accessioned | 2023-01-02T10:45:18Z | |
| dc.date.available | 2023-01-02T10:45:18Z | |
| dc.date.issued | 2017-12 | |
| dc.description.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. | en_US |
| dc.identifier.uri | https://ceur-ws.org/Vol-2036/T3-3.pdf | |
| dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8223 | |
| dc.language.iso | en | en_US |
| dc.publisher | CEUR | en_US |
| dc.subject | Computer Science | en_US |
| dc.subject | Keyword Extraction | en_US |
| dc.subject | Legal Documents | en_US |
| dc.subject | Deep Learning | en_US |
| dc.subject | LSTM | en_US |
| dc.subject | Natural Language Processing | en_US |
| dc.title | Catchphrase Extraction from Legal Documents Using LSTM Networks | en_US |
| dc.type | Article | en_US |
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