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scikit-learn

Are We Really Making Much Progress in Text Classification? A Comparative Review - Summary

This paper reviews and compares methods for single-label and multi-label text classification, categorizing them into bag-of-words, sequence-based, graph-based, and hierarchical methods. The findings reveal that pre-trained language models outperform all recently proposed graph-based and hierarchy-b

Post Processing Recommender Systems with Knowledge Graphs for Recency, Popularity, and Diversity of Explanations - Summary

The paper proposes a re-ranking approach for explainable recommender systems using knowledge graphs to optimize for recency, popularity, and diversity of explanations. The approach is evaluated on two public datasets and shows an increase in explanation quality while preserving recommendation utili