A common task in a world of natural language processing is text classification useful for eg
spam filters, documents sorting, science articles classification or plagiarism detection. This …

Text classification is one of the most common goals of machine learning (ML) projects, and
also one of the most frequent human intelligence tasks in crowdsourcing platforms. ML has …

Crowdsourcing has been widely used recently as an alternative to traditional annotations
that is costly and usually done by experts. However, crowdsourcing tasks are not interesting …

Text classification is a fundamental task in content analysis. Nowadays, deep learning has
demonstrated promising performance in text classification compared with shallow models …

In modern practice, labeling a dataset often involves aggregating annotator judgments
obtained from crowdsourcing. State-of-theart aggregation is performed via inference on …

This article presents the results of work on a service that allows classifying citizens' appeals.
Citizens' appeals are unstructured text written in natural language. The objective is to …

Content based Document Classification is one of the biggest challenges in the context of
free text mining. Current algorithms on document classifications mostly rely on cluster …

Feature Selection (FS) methods alleviate key problems in the development of text
classification models as they are used to reduce the data dimensionality, improve the model …

Social media has led to the democratisation of opinion sharing. A wealth of information
about public opinions, current events, and authors' insights into specific topics can be …

Analysts, researchers, and other users from different fields may spend a lot of time
recognizing their work-related documents and organizing them in a way that allows them to …