Explainable Graph Spectral Clustering For GloVe-like Text Embeddings
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Abstract (arXiv)
In a previous paper, we proposed an introduction to the explainability of Graph Spectral Clustering results for textual documents, given that document similarity is computed as cosine similarity in term vector space. In this paper, we generalize this idea by considering other embeddings of documents, in particular, based on the GloVe embedding idea.
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References · 7
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2015Convolutional Neural Network Architectures for Matching Natural Language Sentencescited by 82
- 2014word2vec Parameter Learning Explainedcited by 53
- 2016An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generationcited by 48
- 2016Representation learning for very short texts using weighted word embedding aggregationcited by 12
- 2023Explainable Graph Spectral Clustering of Text Documentscited by 2
- 2025A Method for Handling Negative Similarities in Explainable Graph Spectral Clustering of Text Documents -- Extended Versioncited by 1
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