On this page:OverviewPublicationsResearchersKey papersJournalsOpen accessInstitutions
ScholarIQanswers from OpenAlex

Text and Document Classification Technologies

TopicLeading institutions, researchers & key papers

Text and Document Classification Technologies is a topic indexed in ScholarIQ from OpenAlex.

What is known about Text and Document Classification Technologies?

ScholarIQrecord summary

This cluster of papers focuses on the application of machine learning algorithms for multi-label text classification, with an emphasis on techniques such as feature selection, Naive Bayes classifier, K-nearest Neighbor (KNN), hierarchical classification, and support vector machines (SVM). The research covers various aspects of document categorization and information retrieval in the context of text mining and natural language processing.

How many works does Text and Document Classification Technologies have?

ScholarIQindexed works

Text and Document Classification Technologies has 85 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.

What is the OpenAlex record for Text and Document Classification Technologies?

ScholarIQopenalex

The OpenAlex for Text and Document Classification Technologies is on the source record.

What are the most-cited papers on Text and Document Classification Technologies?

ScholarIQmost cited works
HDLTex: Hierarchical Deep Learning for Text Classification
Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa, Kiana Jafari Meimandi, Matthew S. Gerber, Laura E. Barnes
2017450 CitationsOPEN ACCESS
Efficient English text classification using selected Machine Learning Techniques
Xiaoyu Luo
Alexandria Engineering Journal. 2021236 CitationsOPEN ACCESS
Semi-supervised Multi-label Learning by Solving a Sylvester Equation
Gang Chen, Yangqiu Song, Fei Wang, Changshui Zhang
2008194 Citations
Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning
Sheng Wan, Shirui Pan, Jian Yang, Chen Gong
Proceedings of the AAAI Conference on Artificial Intelligence. 2021151 CitationsOPEN ACCESS
Multi-label learning with label-specific features by resolving label correlations
Jia Zhang, Candong Li, Donglin Cao, Yaojin Lin, Songzhi Su, Liang Dai, Shaozi Li
Knowledge-Based Systems. 2018102 Citations

Where is Text and Document Classification Technologies research published, and who funds it?

ScholarIQvenues & funding sources

TOP FUNDERS

National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock

How much of the research on Text and Document Classification Technologies is open access?

ScholarIQopen access share
53%OPEN ACCESS
Gold
33%
Green
20%
Hybrid
0%
Bronze
0%
Closed
47%

Related on ScholarIQ

470M+ articles · free account