The research aims to manipulate publicly accessible metadata adequately to stage multi-label classification and to estimate; “to what extent metadata-based ...
Oct 22, 2024 · ... This approach encompasses attaching multiple associated labels to instances with multiple labels, rendering it a crucial task in diverse ...
The proposed technique has been assessed for two diverse datasets, namely, from the Journal of universal computer science (J.UCS) and the benchmark dataset ...
The proposed technique yields encouraging results in contrast to the state-of-the-art techniques in the literature. AB - From the beginning, the process of ...
Therefore, in this paper, we propose a novel neural network based approach for multi-label document classification, in which two heterogeneous graphs are ...
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Hierarchical text classification refers to assigning a document to a suitable concept from a hierarchical concept space. This paper explores the use of ...
Jul 8, 2024 · We study open-world multi-label text classification under extremely weak supervision (XWS), where the user only provides a brief description for ...
Mar 19, 2021 · In this paper, we explore and compare the recent deep learning-based methods for multi-label text classification. We investigate two scenarios.
Nov 16, 2024 · In this paper, we present a novel method for multi- property multi-label document classification that leverages an encoder embedding-driven ...
Aug 22, 2023 · We introduce in this paper a new approach to improve deep learning-based architectures for multi-label document classification.