# Unsupervised Keyphrase Extraction with Multipartite Graphs

arXiv: https://arxiv.org/abs/1803.08721 · HTML: https://mlsanity.com/paper/1803.08721/

## Key facts

- Cited by 50 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Mar 2018.

## Built on by (most cited first, 30 of 50)

- [Modality-Fair Preference Optimization for Trustworthy MLLM Alignment](https://mlsanity.com/paper/2410.15334/) (2024)
- [Bringing Generative AI to Adaptive Learning in Education](https://mlsanity.com/paper/2402.14601/) (2024)
- [Keyphrase Generation for Scientific Document Retrieval](https://mlsanity.com/paper/2106.14726/) (2021)
- [MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction](https://mlsanity.com/paper/2110.06651/) (2021)
- [Unsupervised Keyphrase Extraction by Jointly Modeling Local and Global Context](https://mlsanity.com/paper/2109.07293/) (2021)
- [Retrieval-Augmented Multilingual Keyphrase Generation with Retriever-Generator Iterative Training](https://mlsanity.com/paper/2205.10471/) (2022)
- [From Statistical Methods to Deep Learning, Automatic Keyphrase Prediction: A Survey](https://mlsanity.com/paper/2305.02579/) (2023)
- [Pre-trained Language Models for Keyphrase Generation: A Thorough Empirical Study](https://mlsanity.com/paper/2212.10233/) (2022)
- [Redefining Absent Keyphrases and their Effect on Retrieval Effectiveness](https://mlsanity.com/paper/2103.12440/) (2021)
- [Word-level Human Interpretable Scoring Mechanism for Novel Text Detection Using Tsetlin Machines](https://mlsanity.com/paper/2105.04708/) (2021)
- [Ask to Know More: Generating Counterfactual Explanations for Fake Claims](https://mlsanity.com/paper/2206.04869/) (2022)
- [Rethinking Model Selection and Decoding for Keyphrase Generation with Pre-trained Sequence-to-Sequence Models](https://mlsanity.com/paper/2310.06374/) (2023)
- [Out of Thin Air: Is Zero-Shot Cross-Lingual Keyword Detection Better Than Unsupervised?](https://mlsanity.com/paper/2202.06650/) (2022)
- [KPDrop: Improving Absent Keyphrase Generation](https://mlsanity.com/paper/2112.01476/) (2021)
- [A Large-Scale Dataset for Biomedical Keyphrase Generation](https://mlsanity.com/paper/2211.12124/) (2022)
- [Phraseformer: Multimodal Key-phrase Extraction using Transformer and Graph Embedding](https://mlsanity.com/paper/2106.04939/) (2021)
- [Keyword Extraction from Short Texts with a Text-To-Text Transfer Transformer](https://mlsanity.com/paper/2209.14008/) (2022)
- [KPEval: Towards Fine-Grained Semantic-Based Keyphrase Evaluation](https://mlsanity.com/paper/2303.15422/) (2023)
- [Large Language Models as Zero-Shot Keyphrase Extractors: A Preliminary Empirical Study](https://mlsanity.com/paper/2312.15156/) (2023)
- [Unsupervised Domain Adaptation for Keyphrase Generation using Citation Contexts](https://mlsanity.com/paper/2409.13266/) (2024)
- [Keyword Extraction in Scientific Documents](https://mlsanity.com/paper/2207.01888/) (2022)
- [Theme-driven Keyphrase Extraction to Analyze Social Media Discourse](https://mlsanity.com/paper/2301.11508/) (2023)
- [On Leveraging Encoder-only Pre-trained Language Models for Effective Keyphrase Generation](https://mlsanity.com/paper/2402.14052/) (2024)
- [A Preliminary Empirical Study on Prompt-based Unsupervised Keyphrase Extraction](https://mlsanity.com/paper/2405.16571/) (2024)
- [Back to the Basics: A Quantitative Analysis of Statistical and Graph-Based Term Weighting Schemes for Keyword Extraction](https://mlsanity.com/paper/2104.08028/) (2021)
- [Enhancing Phrase Representation by Information Bottleneck Guided Text Diffusion Process for Keyphrase Extraction](https://mlsanity.com/paper/2308.08739/) (2023)
- [Utilizing Cognitive Signals Generated during Human Reading to Enhance Keyphrase Extraction from Microblogs](https://mlsanity.com/paper/2606.26485/) (2026)
- [FRAKE: Fusional Real-time Automatic Keyword Extraction](https://mlsanity.com/paper/2104.04830/) (2021)
- [Self-Compositional Data Augmentation for Scientific Keyphrase Generation](https://mlsanity.com/paper/2411.03039/) (2024)
- [ConExion: Concept Extraction with Large Language Models](https://mlsanity.com/paper/2504.12915/) (2025)

## Abstract (arXiv)

We propose an unsupervised keyphrase extraction model that encodes topical information within a multipartite graph structure. Our model represents keyphrase candidates and topics in a single graph and exploits their mutually reinforcing relationship to improve candidate ranking. We further introduce a novel mechanism to incorporate keyphrase selection preferences into the model. Experiments conducted on three widely used datasets show significant improvements over state-of-the-art graph-based models.