2023
DOI: 10.2298/csis220620002h
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Tourism recommendation based on word embedding from card transaction data

Abstract: In the tourism industry, millions of card transactions generate a massive volume of big data. The card transactions eventually reflect customers? consumption behaviors and patterns. Additionally, recommender systems that incorporate users? personal preferences and consumption is an important subject of smart tourism. However, challenges exist such as handling the absence of rating data and considering spatial factor that significantly affects recommendation performance. This paper applies … Show more

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