Fine-Grained Multi-label Sexism Classification Using a Semi-Supervised Multi-level Neural Approach

to related objects

Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 2364-1541

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Fine-Grained Multi-label Sexism Classification Using a Semi-Supervised Multi-level Neural Approach ; volume:6 ; number:4 ; day:17 ; month:8 ; year:2021 ; pages:359-379 ; date:12.2021
Data science and engineering ; 6, Heft 4 (17.8.2021), 359-379, 12.2021

Creator: Abburi, Harika
Parikh, Pulkit
Chhaya, Niyati
Varma, Vasudeva

Contributor: SpringerLink (Online service)

DOI: 10.1007/s41019-021-00168-y

URN: urn:nbn:de:101:1-2022010721124889669019

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:23 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Show original at data provider

Associated

Abburi, Harika
Parikh, Pulkit
Chhaya, Niyati
Varma, Vasudeva
SpringerLink (Online service)

Other Objects (12)

Sparse semi-supervised multi-label feature selection based on latent representation

Semi-Supervised learning with Collaborative Bagged Multi-label K-Nearest-Neighbors

Semi-supervised multi-label classification using an extended graph-based manifold regularization

Multi-label Rule Learning

Multi-view Multi-label Learning with Shared Features Inconsistency

Multi-label classification via multi-target regression on data streams

Multi-label Classification with ART Neural Networks

Multi-label Classification with Multiple Class Ontologies

Concise and interpretable multi-label rule sets

Automated machine learning for multi-label classification

Protein function prediction through multi-view multi-label latent tensor reconstruction

Online Multi-label Text Classification using Topic Models

Sparse semi-supervised multi-label feature selection based on latent representation

Semi-Supervised learning with Collaborative Bagged Multi-label K-Nearest-Neighbors

Semi-supervised multi-label classification using an extended graph-based manifold regularization

Multi-label Rule Learning

Multi-view Multi-label Learning with Shared Features Inconsistency

Multi-label classification via multi-target regression on data streams

Multi-label Classification with ART Neural Networks

Multi-label Classification with Multiple Class Ontologies

Concise and interpretable multi-label rule sets

Automated machine learning for multi-label classification

Protein function prediction through multi-view multi-label latent tensor reconstruction

Online Multi-label Text Classification using Topic Models

Sparse semi-supervised multi-label feature selection based on latent representation

Semi-Supervised learning with Collaborative Bagged Multi-label K-Nearest-Neighbors

Semi-supervised multi-label classification using an extended graph-based manifold regularization

Multi-label Rule Learning

Multi-view Multi-label Learning with Shared Features Inconsistency

Multi-label classification via multi-target regression on data streams

Multi-label Classification with ART Neural Networks

Multi-label Classification with Multiple Class Ontologies

Concise and interpretable multi-label rule sets

Automated machine learning for multi-label classification

Protein function prediction through multi-view multi-label latent tensor reconstruction

Online Multi-label Text Classification using Topic Models

Cultural heritage institutions wishing to register will find more information here.

Fields marked * need to be filled in.

Username*

Please enter your username

Email*

Please enter your email address

Please do not fill this field

First name

Last name

Password*

Please enter your password

Confirm password*

Please enter the same password

I have read the terms of use and the privacy policy for the collection of personal data and accept them. *

This field is required.

I would like to subscribe to the newsletter of the Deutsche Digitale Bibliothek. See newsletter subscription info.

Account created

Your "My DDB" account has been successfully created. Before you can log in to your account, you must click the confirmation link in the message we just sent to the email address you provided.

Fine-Grained Multi-label Sexism Classification Using a Semi-Supervised Multi-level Neural Approach

Object Details

References and Relationships

Contributors, Places and Time

Further information

Data provider

Associated

Other Objects (12)

Sparse semi-supervised multi-label feature selection based on latent representation

Semi-Supervised learning with Collaborative Bagged Multi-label K-Nearest-Neighbors

Semi-supervised multi-label classification using an extended graph-based manifold regularization

Multi-label Rule Learning

Multi-view Multi-label Learning with Shared Features Inconsistency

Multi-label classification via multi-target regression on data streams

Multi-label Classification with ART Neural Networks

Multi-label Classification with Multiple Class Ontologies

Concise and interpretable multi-label rule sets

Automated machine learning for multi-label classification

Protein function prediction through multi-view multi-label latent tensor reconstruction

Online Multi-label Text Classification using Topic Models

Sparse semi-supervised multi-label feature selection based on latent representation

Semi-Supervised learning with Collaborative Bagged Multi-label K-Nearest-Neighbors

Semi-supervised multi-label classification using an extended graph-based manifold regularization

Multi-label Rule Learning

Multi-view Multi-label Learning with Shared Features Inconsistency

Multi-label classification via multi-target regression on data streams

Multi-label Classification with ART Neural Networks

Multi-label Classification with Multiple Class Ontologies

Concise and interpretable multi-label rule sets

Automated machine learning for multi-label classification

Protein function prediction through multi-view multi-label latent tensor reconstruction

Online Multi-label Text Classification using Topic Models

Sparse semi-supervised multi-label feature selection based on latent representation

Semi-Supervised learning with Collaborative Bagged Multi-label K-Nearest-Neighbors

Semi-supervised multi-label classification using an extended graph-based manifold regularization

Multi-label Rule Learning

Multi-view Multi-label Learning with Shared Features Inconsistency

Multi-label classification via multi-target regression on data streams

Multi-label Classification with ART Neural Networks

Multi-label Classification with Multiple Class Ontologies

Concise and interpretable multi-label rule sets

Automated machine learning for multi-label classification

Protein function prediction through multi-view multi-label latent tensor reconstruction

Online Multi-label Text Classification using Topic Models

Related objects

Reset password