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arXiv · 2304.03098

Static Fuzzy Bag-of-Words: a lightweight sentence embedding algorithm

Matteo Muffo·Roberto Tedesco·Licia Sbattella·Vincenzo Scotti
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Abstract

The introduction of embedding techniques has pushed forward significantly the Natural Language Processing field. Many of the proposed solutions have been presented for word-level encoding; anyhow, in the last years, new mechanism to treat information at an higher level of aggregation, like at sentence- and document-level, have emerged. With this work we address specifically the sentence embeddings problem, presenting the Static Fuzzy Bag-of-Word model. Our model is a refinement of the Fuzzy Bag-of-Words approach, providing sentence embeddings with a predefined dimension. SFBoW provides competitive performances in Semantic Textual Similarity benchmarks, while requiring low computational resources.

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Matteo Muffo, Roberto Tedesco, Licia Sbattella, Vincenzo Scotti. 2023-04-06. Static Fuzzy Bag-of-Words: a lightweight sentence embedding algorithm. https://arxiv.org/abs/2304.03098

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