Unsupervised Keyword Extraction from Polish Legal Texts

TL;DR

This paper applies an unsupervised keyword extraction method, RAKE, to Polish legal texts, enhancing it with an automatic stoplist selection to improve domain-specific performance.

Contribution

It introduces an automatic stoplist selection approach for RAKE, tailored to Polish legal texts, improving keyword extraction accuracy in a specialized domain.

Findings

RAKE effectively extracts keywords from Polish legal texts.

Automatic stoplist selection improves keyword relevance.

Method is language and domain independent with proper stoplist adaptation.

Abstract

In this work, we present an application of the recently proposed unsupervised keyword extraction algorithm RAKE to a corpus of Polish legal texts from the field of public procurement. RAKE is essentially a language and domain independent method. Its only language-specific input is a stoplist containing a set of non-content words. The performance of the method heavily depends on the choice of such a stoplist, which should be domain adopted. Therefore, we complement RAKE algorithm with an automatic approach to selecting non-content words, which is based on the statistical properties of term distribution.