Papers by Renzo Arturo Alva Principe
An LCF-IDF Document Representation Model Applied to Long Document Classification (2024.lrec-main)
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| Challenge: | Document representation models have been used for years in NLP and Text Mining tasks but are limited when it comes to capturing the deeper semantics and context of textual data. |
| Approach: | They propose to use a Latent Concept Frequency-Inverse Document Frequence model to exploit the advantages of TF-IDF while incorporating semantic context into the model. |
| Outcome: | The proposed model outperforms existing models on the Long Document Classification task and shows that it performs better than TF-IDF and BERT-like representation models. |