Experimental results of semantic similarity methods

Published: 26 March 2025| Version 1 | DOI: 10.17632/9vg9tr6xvm.1
Contributors:
Francesco Taglino,
,

Description

This dataset collects data used for the comparison of the following seven semantic similarity methods: 1. SemSimp with a manual taxonomy and human-annotated documents. 2. SemSimAI with an automatic taxonomy and automatically annotated documents using BERTopic. 3. SemSimAI with an automatic taxonomy and automatically annotated documents using recursive k-means clustering with Word2Vec embeddings. 4. SemSimAI with an automatic taxonomy and automatically annotated documents using recursive k-means clustering with TF-IDF vectors. 5. Cosine similarity with document representations from TF-IDF vectors. 6. Cosine similarity with document representations from BERT embeddings. 7. Cosine similarity with document representations from Word2Vec embeddings.

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Institutions

  • Istituto di analisi dei sistemi ed informatica Antonio Ruberti Consiglio Nazionale delle Ricerche
  • ENEA Agenzia Nazionale per Le Nuove Tecnologie l'Energia e lo Sviluppo Economico Sostenibile

Categories

Semantics, Similarity Measure

Licence