Text and Document Classification Technologies
Text and Document Classification Technologies is a topic indexed in ScholarIQ from OpenAlex.
What is known about Text and Document Classification Technologies?
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?
Text and Document Classification Technologies has 36,597 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.
How many citations does Text and Document Classification Technologies have?
Text and Document Classification Technologies has 458,492 citations in the OpenAlex counts ScholarIQ stores.
What is the OpenAlex record for Text and Document Classification Technologies?
The OpenAlex for Text and Document Classification Technologies is on the source record.