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
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
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
The Cranfield paradigm has served as a foundational approach for developing test collections, with relevance judgments typically conducted by human assessors. However, the emergence of large language models (LLMs) has introduced new possibilities for automating these tasks. This paper explores the feasibility of using LLMs to automate relevance assessments, particularly within the context of low-resource languages. In our study, LLMs are employed to automate relevance judgment tasks, by providing a series of query-document pairs in Tetun as the input text. The models are tasked with assigning relevance scores to each pair, where these scores are then compared to those from human annotators to evaluate the inter-annotator agreement levels. Our investigation reveals results that align closely with those reported in studies of high-resource languages. © 2024 CEUR-WS. All rights reserved.

Abstract

Abstract
This paper proposes Labadain Crawler, a data collection pipeline tailored to automate and optimize the process of constructing textual corpora from the web, with a specific target to low-resource languages. The system is built on top of Nutch, an open-source web crawler and data extraction framework, and incorporates language processing components such as a tokenizer and a language identification model. The pipeline efficacy is demonstrated through successful testing with Tetun, one of Timor-Leste's official languages, resulting in the construction of a high-quality Tetun text corpus comprising 321.7k sentences extracted from over 22k web pages. The contributions of this paper include the development of a Tetun tokenizer, a Tetun language identification model, and a Tetun text corpus, marking an important milestone in Tetun text information retrieval.