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Information × Registration Number 2122U006280, Article popup.category Препринт Title Trip planning based on sequential recommender systems using textual representations (AI translated) popup.author Yatskiv BohdanYatskiv Bohdan popup.publication 01-01-2022 popup.source_user Український католицький університет popup.source https://hdl.handle.net/20.500.14570/4455 popup.publisher Description Finding interesting places to visit is one of the most common problems while travel- ling. With the development of review services, a large amount of personalized infor- mation is produced by the users. We believe that the information that review texts contain could be used to improve the personalized recommendations. This work fo- cuses on creating a sequential recommender system that provides recommendations based on the chronological history of users’ text reviews. The proposed model uses BERT text embeddings to get review text representations and a Transformer encoder to learn the context between items in sequence with the multi-attention mechanism. This approach allows to provide relevant recommendations based on the user’s se- quential behavior and makes the trip planning more comfortable. popup.nrat_date 2025-11-05 Close