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arXiv · 2110.00462

Explainable Point-Based Document Visualizations

Primož Godec·Nikola Ðukić·Ajda Pretnar·Vesna Tanko·Lan Žagar·Blaž Zupan
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Abstract

Two-dimensional data maps can visually reveal information about the relations between data instances. Popular techniques to construct data maps are t-SNE and UMAP. The resulting point-based visualizations, though, provide information only through their interpretation. We here consider a set of abstracts from the articles on longevity to argue for using keyword extraction methods to label clusters of documents in the map. Among the considered approaches, the best results were obtained by recently proposed YAKE!. Surprisingly, a classical TF-IDF term ranking outperformed graph and embedding-based techniques.

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Primož Godec, Nikola Ðukić, Ajda Pretnar, Vesna Tanko, Lan Žagar, Blaž Zupan. 2021-09-28. Explainable Point-Based Document Visualizations. https://arxiv.org/abs/2110.00462

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