# A Review of Keyphrase Extraction

## TL;DR

This paper provides a comprehensive review of keyphrase extraction methods, evaluation approaches, open issues, and compares popular unsupervised techniques across multiple datasets.

## Contribution

It offers a structured overview of existing keyphrase extraction research, insights on evaluation methods, and a comparative experimental analysis of unsupervised techniques.

## Key findings

- Unsupervised techniques vary significantly in performance.
- Evaluation methods influence the perceived effectiveness.
- Open issues include dataset diversity and evaluation standards.

## Abstract

Keyphrase extraction is a textual information processing task concerned with the automatic extraction of representative and characteristic phrases from a document that express all the key aspects of its content. Keyphrases constitute a succinct conceptual summary of a document, which is very useful in digital information management systems for semantic indexing, faceted search, document clustering and classification. This article introduces keyphrase extraction, provides a well-structured review of the existing work, offers interesting insights on the different evaluation approaches, highlights open issues and presents a comparative experimental study of popular unsupervised techniques on five datasets.