Multi-Label Ranking: Mining Multi-Label and Label Ranking Data

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


We survey multi-label ranking tasks, specifically multi-label classification and label ranking classification. We highlight the unique challenges, and re-categorize the methods, as they no longer fit into the traditional categories of transformation and adaptation. We survey developments in the last demi-decade, with a special focus on state-of-the-art methods in deep learning multi-label mining, extreme multi-label classification and label ranking. We conclude by offering a few future research directions.

Original languageEnglish
Title of host publicationMachine Learning for Data Science Handbook
Subtitle of host publicationData Mining and Knowledge Discovery Handbook, Third Edition
Number of pages25
ISBN (Electronic)9783031246289
StatePublished - 1 Jan 2023


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