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

• URL: http://arxiv.org/abs/2101.00583v1
• Date: Sun, 3 Jan 2021 08:36:45 GMT
• Title: Multi-label Ranking: Mining Multi-label and Label Ranking Data
• Authors: Lihi Dery
• Abstract summary: 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.
• Score: 1.8275108630751844
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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