# DivGraphPointer: A Graph Pointer Network for Extracting Diverse Keyphrases

arXiv: https://arxiv.org/abs/1905.07689 · HTML: https://mlsanity.com/paper/1905.07689/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 May 2019.

## Built on by (most cited first, 16 of 16)

- [Importance Estimation from Multiple Perspectives for Keyphrase Extraction](https://mlsanity.com/paper/2110.09749/) (2021)
- [From Statistical Methods to Deep Learning, Automatic Keyphrase Prediction: A Survey](https://mlsanity.com/paper/2305.02579/) (2023)
- [Redefining Absent Keyphrases and their Effect on Retrieval Effectiveness](https://mlsanity.com/paper/2103.12440/) (2021)
- [Unsupervised Deep Keyphrase Generation](https://mlsanity.com/paper/2104.08729/) (2021)
- [Hyperbolic Relevance Matching for Neural Keyphrase Extraction](https://mlsanity.com/paper/2205.02047/) (2022)
- [Set-to-Sequence Methods in Machine Learning: a Review](https://mlsanity.com/paper/2103.09656/) (2021)
- [KPDrop: Improving Absent Keyphrase Generation](https://mlsanity.com/paper/2112.01476/) (2021)
- [EUROPA: A Legal Multilingual Keyphrase Generation Dataset](https://mlsanity.com/paper/2403.00252/) (2024)
- [Enhancing Keyphrase Extraction from Long Scientific Documents using Graph Embeddings](https://mlsanity.com/paper/2305.09316/) (2023)
- [Pre-Trained Language Models for Keyphrase Prediction: A Review](https://mlsanity.com/paper/2409.01087/) (2024)
- [Deep Keyphrase Completion](https://mlsanity.com/paper/2111.01910/) (2021)
- [Abstractive Opinion Tagging](https://mlsanity.com/paper/2101.06880/) (2021)
- [Sentence Structure and Word Relationship Modeling for Emphasis Selection](https://mlsanity.com/paper/2108.12750/) (2021)
- [Unsupervised Open-domain Keyphrase Generation](https://mlsanity.com/paper/2306.10755/) (2023)
- [Set2Seq Transformer: Temporal and Position-Aware Set Representations for Sequential Multiple-Instance Learning](https://mlsanity.com/paper/2408.03404/) (2024)
- [Attention-Seeker: Dynamic Self-Attention Scoring for Unsupervised Keyphrase Extraction](https://mlsanity.com/paper/2409.10907/) (2024)

## Abstract (arXiv)

Keyphrase extraction from documents is useful to a variety of applications such as information retrieval and document summarization. This paper presents an end-to-end method called DivGraphPointer for extracting a set of diversified keyphrases from a document. DivGraphPointer combines the advantages of traditional graph-based ranking methods and recent neural network-based approaches. Specifically, given a document, a word graph is constructed from the document based on word proximity and is encoded with graph convolutional networks, which effectively capture document-level word salience by modeling long-range dependency between words in the document and aggregating multiple appearances of identical words into one node. Furthermore, we propose a diversified point network to generate a set of diverse keyphrases out of the word graph in the decoding process. Experimental results on five benchmark data sets show that our proposed method significantly outperforms the existing state-of-the-art approaches.