LongKey: Keyphrase Extraction for Long Documents
Authors: name: Jeovane Honorio Alves, name: Radu State, name: Cinthia Obladen de Almendra Freitas, name: Jean Paul Barddal

In an era of information overload, manually annotating the vast and growing
corpus of documents and scholarly papers is increasingly impractical. Automated
keyphrase extraction addresses this challenge by identifying representative
terms within texts. However, most existing methods focus on short documents (up
to 512 tokens), leaving a gap in processing long-context documents. In this
paper, we introduce LongKey, a novel framework for extracting keyphrases from
lengthy documents, which uses an encoder-based language model to capture
extended text intricacies. LongKey uses a max-pooling embedder to enhance
keyphrase candidate representation. Validated on the comprehensive LDKP
datasets and six diverse, unseen datasets, LongKey consistently outperforms
existing unsupervised and language model-based keyphrase extraction methods.
Our findings demonstrate LongKey's versatility and superior performance,
marking an advancement in keyphrase extraction for varied text lengths and
domains.