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.

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.