Abstract
AbstractSeveral approaches have been proposed to obtain successful models to solve complex next-item recommendation problem in non-prohibitive computational time, such as by using heuristics, designing architectures, and applying information filtering techniques. In the current technological scenario of artificial intelligence, sequential recommender systems have been gaining attention and they are a highly demanding research area, especially using deep learning in their development. Our research focuses on an efficient and practical model for managing sequential session-based recommendations of specific products for users using the wine and movie domains as case studies. Through an innovative recommender model called X-Model4Rec – eXtensible Model for Recommendation, we explore the user's dynamic taste profile using architectures with transformer and multi-head attention mechanisms to solve the next-item recommendation problem. The performance of the proposed model is compared to that of classical and baseline recommender models on two real-world datasets of wines and movies, and the results are better for most of the evaluation metrics.

Abstract
Virtual Reality (VR) has the capacity to increase tourists' responses, compared with other marketing tools. In tourism, it can play a decisive role in its promotion, since it can generate impactful information that will increase the visit intention. However, there are few reviews that focus on VR as a promotional tool in tourism. To overcome this limitation, this work provides a bibliometric analysis of papers from the Web of Science and Scopus databases. The analysis allows us to conclude that although its potential is recognized, the use of VR is infrequent in tourism. We also identified three main avenues for future research: presence and devices, promotional strategies, and segments to explore.

Abstract
Virtual Reality (VR) has proven to be an important contribution to tourists' decision-making regarding a destination. This fact can be determinant, especially when tourists face some social limitation or restriction that conditions their participation in tourism activities. Therefore, we aim to understand whether the possibility of experiencing immersive wine tourism activities can encourage future visits, as well as the recommendation of the VR experience and the destination itself. To achieve our goal, we offered 405 participants an experimental VR experience with digital content about a wine tourism activity. The results showed that participants feel that the VR experience influences their behavioural intention towards the wine tourism destination. The satisfaction felt from the experience leads to a significant effect on the intention to visit and to recommend the destination and the VR activity. These findings suggest to wine tourism destination managers that VR can play an essential role in tourism management.

Abstract
Purpose - This study investigates the barriers to the adoption of Virtual Reality (VR) in the tourism industry. Although VR has great potential to enhance the tourist experience, the adoption of this technology is still limited in the tourism sector. Building on the fundamental principles of the Technology -Organization -Environment (TOE) theory and its contribution to perceptions of technology adoption, this study aims to fill the knowledge gap regarding the specific barriers to VR adoption by tourism enterprises. Methodology - To achieve this objective, interviews were conducted with managers of tourism companies, and the data was analysed using qualitative methodology through MAXQDA 20 software. Conclusions - The results reveal that the main barriers identified by managers mainly include lack of knowledge about VR, particularly in the tourism sector. The perceived lack of usefulness, limited experience with the technology, and reluctance to invest in technological equipment also emerge as barriers to VR adoption. Originality of research - This study can help companies in the tourism sector to develop more effective strategies to overcome these barriers, thereby improving the tourist experience and increasing their competitiveness in the market using VR equipment.

Abstract

Abstract
Data-to-text systems offer a transformative approach to generating textual content in data-rich environments. This paper describes the architecture and deployment of Prosebot, a community-driven data-to-text platform tailored for generating textual summaries of football matches derived from match statistics. The system enhances the visibility of lower-tier matches, traditionally accessible only through data tables. Prosebot uses a template-based Natural Language Generation (NLG) module to generate initial drafts, which are subsequently refined by the reading community. Comprehensive evaluations, encompassing both human-mediated and automated assessments, were conducted to assess the system's efficacy. Analysis of the community-edited texts reveals that significant segments of the initial automated drafts are retained, suggesting their high quality and acceptance by the collaborators. Preliminary surveys conducted among platform users highlight a predominantly positive reception within the community.