62 citations · 105 across the 12 of their papers we have counts for
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cs.CL2022★ 62 cited
Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches
Tim Schopf, Daniel Braun, Florian Matthes
Text classification of unseen classes is a challenging Natural Language Processing task and is mainly attempted using two different types of approaches. Similarity-based approaches…
cs.CL2022★ 25 cited
Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval on Predefined Topics
Tim Schopf, Daniel Braun, Florian Matthes
In this paper, we consider the task of retrieving documents with predefined topics from an unlabeled document dataset using an unsupervised approach. The proposed unsupervised appr…