Catchphrase Extraction from Legal Documents Using LSTM Networks
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Date
2017-12
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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.
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Keywords
Computer Science, Keyword Extraction, Legal Documents, Deep Learning, LSTM, Natural Language Processing