Leveraging label hierarchy using transfer and multi-task learning: A case study on patent classification-Reference-Cited by-同舟云学术

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Leveraging label hierarchy using transfer and multi-task learning: A case study on patent classification

Published:2021-11 Issue: Volume:464 Page:421-431
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Aroyehun Segun Taofeek,Angel Jason,Majumder Navonil,Gelbukh Alexander,Hussain Amir

Funder

Consejo Nacional de Ciencia y Tecnología

Instituto Politécnico Nacional Secretaría de Investigación y Posgrado

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference60 articles.

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2. Comment toxicity detection via a multichannel convolutional bidirectional gated recurrent unit;Kumar;Neurocomputing,2021

3. Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis;Poria;Neurocomputing,2017

4. ABCDM: An attention-based bidirectional CNN-RNN deep model for sentiment analysis;Basiri;Fut. Gen. Comput. Syst.,2021

5. A. Iturbe Herrera, N.A. Castro Sánchez, D. Mújica Vargas, Rule-based spanish multiple question reformulation and their classification using a convolutional neuronal network, Computación y Sistemas 25 (1).

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3. An ensemble framework for patent classification;World Patent Information;2023-12

4. Where do pigeons’ choices come from? Transfer Learning in Spiking Neural Networks for Animal Choices in Behavioral Research;2023-02-14

5. Unveiling Black-Boxes: Explainable Deep Learning Models for Patent Classification;Communications in Computer and Information Science;2023

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