CONF Callejas-Hernandez_IBERLEF2022_2022/IDIAP The Winning Approach for the Recommendation Systems Shared Task @REST_MEX 2022 Callejas-Hernández, Cipriano Rivadeneira-Pérez, Erika Sánchez-Vega, Fernando López-Monroy, A. Pastor Villatoro-Tello, Esaú Bag OF Words BERT Mexican Tourist Text Recommendation System Sentiment Analysis Text Information Organization Schemes EXTERNAL http://publications.idiap.ch/attachments/papers/2022/Callejas-Hernandez_IBERLEF2022_2022.pdf PUBLIC Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2022) 3202 2022 http://ceur-ws.org/Vol-3202/restmex-paper1.pdf URL This paper presents our approaches for the Recommendation System and Sentiment Analysis shared tasks at Rest-Mex 2022. In the first task, the dataset presented a number of challenges, which we overcome by exploring information organization schemes and traditional data representation. For opinion classification in the case of Sentiment Analysis we found that state-of-the-art pre-trained models by adapting two Bert-based approaches get an acceptable performance. With these two approaches we were able to reach the first place in the recommendation system task while our simple adaptation of state-of-the-art for the sentiment analysis task got a very competitive performance, only 0.58% below the winning approach