Challenges in multilingual and cross-lingual text classification Difficulties in classifying short and sparse texts

In text classification, we are given a description $\onedoc \in \mathbb{X}$ of a document, where $\mathbb{X}$ is the document space ; and a fixed set of ... ... classification operation. Currently, the only available key is: task_description : A string containing a short explanation of the text classification task. Oct 28, 2013 ... Text categorization ... Text categorization (a.k.a. text classification) is the task of assigning predefined categories to free-text documents. It ... In natural language processing (NLP), text classification tasks are increasingly fine-grained, as datasets are fragmented into a larger number of classes ... May 25, 2016 ... Title:Adversarial Training Methods for Semi-Supervised Text Classification ... Abstract:Adversarial training provides a means of regularizing ... Apr 3, 2025 ... Text classification is a key natural language processing task widely used in areas such as news classification, sentiment analysis, topic ... ... Text Line Database · Cover of Improving Text Classification with Boolean Retrieval for Rare Categories: A Case Study Identifying. Improving Text Classification ... In this module, we will learn about the different types of machine learning that exist and the operational steps of building a supervised machine learning ... Dec 24, 2022 ... In this post we'll see a demonstration of an NLP-Classification problem with 2 different approaches in python. Evaluate with Argilla¶. Now, we can start the annotation process. Just open the dataset in the Argilla UI and start annotating the records. If the suggestions ...