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2020 EMNLP EMNLP 2020

NMF Ensembles? Not for Text Summarization!

Abstract

AbstractNon-negative Matrix Factorization (NMF) has been used for text analytics with promising results. Instability of results arising due to stochastic variations during initialization makes a case for use of ensemble technology. However, our extensive empirical investigation indicates otherwise. In this paper, we establish that ensemble summary for single document using NMF is no better than the best base model summary.

❓ The Questioner

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing

Authors

Alka Khurana, Vasudha Bhatnagar

Topics

Machine Learning > Core Methods > Representation Learning Machine Learning > Learning Types > Unsupervised Learning Natural Language Processing > Generation > Summarization Machine Learning > Core Methods > Matrix Factorization

Keywords

ensemble learning topic modeling text summarization document representation document clustering ensemble method non-negative matrix factorization

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