ELSKE: Efficient Large-Scale Keyphrase Extraction

TL;DR

ELSKE introduces a computationally efficient keyphrase extraction method suitable for large-scale and streaming data, enabling real-time insights without strict structural constraints.

Contribution

The paper presents a novel, scalable approach for keyphrase extraction that balances efficiency and performance on both large collections and individual documents.

Findings

Method is computationally efficient for large datasets

Performs competitively on individual documents

Suitable for real-time streaming data analysis

Abstract

Keyphrase extraction methods can provide insights into large collections of documents such as social media posts. Existing methods, however, are less suited for the real-time analysis of streaming data, because they are computationally too expensive or require restrictive constraints regarding the structure of keyphrases. We propose an efficient approach to extract keyphrases from large document collections and show that the method also performs competitively on individual documents.