# BibRank: Automatic Keyphrase Extraction Platform Using~Metadata

arXiv: https://arxiv.org/abs/2310.09151 · HTML: https://mlsanity.com/paper/2310.09151/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 29 references that are in the map.
- First posted on arXiv 13 Oct 2023.

## Builds on (most cited first, 2 of 2)

- [A Review of Keyphrase Extraction](https://mlsanity.com/paper/1905.05044/) (2019)
- [sCAKE: Semantic Connectivity Aware Keyword Extraction](https://mlsanity.com/paper/1811.10831/) (2018)

## Abstract (arXiv)

Automatic Keyphrase Extraction involves identifying essential phrases in a document. These keyphrases are crucial in various tasks such as document classification, clustering, recommendation, indexing, searching, summarization, and text simplification. This paper introduces a platform that integrates keyphrase datasets and facilitates the evaluation of keyphrase extraction algorithms. The platform includes BibRank, an automatic keyphrase extraction algorithm that leverages a rich dataset obtained by parsing bibliographic data in BibTeX format. BibRank combines innovative weighting techniques with positional, statistical, and word co-occurrence information to extract keyphrases from documents. The platform proves valuable for researchers and developers seeking to enhance their keyphrase extraction algorithms and advance the field of natural language processing.