Elsevier eBooks, Год журнала: 2024, Номер unknown, С. 17 - 28
Опубликована: Янв. 1, 2024
Язык: Английский
ACM Transactions on Recommender Systems, Год журнала: 2024, Номер unknown
Опубликована: Янв. 26, 2024
The prevalence of online content has led to the widespread adoption recommendation systems (RSs), which serve diverse purposes such as news, advertisements, and e-commerce recommendations. Despite their significance, data scarcity issues have significantly impaired effectiveness existing RS models hindered progress. To address this challenge, concept knowledge transfer, particularly from external sources like pre-trained language models, emerges a potential solution alleviate enhance development. However, practice transfer in RSs is intricate. Transferring between domains introduces disparities, application complex scenarios can yield negative consequences if not carefully designed. Therefore, article contributes discourse by addressing implications on introducing various strategies, augmentation, self-supervised learning, broad graph utilization, mitigate challenge. Furthermore, it delves into challenges future direction within domain, offering insights that are poised facilitate development implementation robust RSs, when confronted with scarcity. We aim provide valuable guidance inspiration for researchers practitioners, ultimately driving advancements field RS.
Язык: Английский
Процитировано
10
Journal of Network and Computer Applications, Год журнала: 2024, Номер 231, С. 103989 - 103989
Опубликована: Авг. 2, 2024
The metaverse is a nascent concept that envisions virtual universe, collaborative space where individuals can interact, create, and participate in wide range of activities. Privacy the critical concern as evolves immersive experiences become more prevalent. privacy problem refers to challenges concerns surrounding personal information data within Virtual Reality (VR) environments shared VR becomes accessible. Metaverse will harness advancements from various technologies such Artificial Intelligence (AI), Extended (XR) Mixed (MR) provide personalized services its users. Moreover, enable experiences, relies on collection fine-grained user leads issues. Therefore, before potential be fully realized, related must addressed. This includes safeguarding users' control over their data, ensuring security information, protecting in-world actions interactions unauthorized sharing. In this paper, we explore future metaverses are expected face, given reliance AI for tracking users, creating XR MR facilitating interactions. thoroughly analyze technical solutions differential privacy, Homomorphic Encryption, Federated Learning discuss sociotechnical issues regarding privacy.
Язык: Английский
Процитировано
10
IEEE Open Journal of the Computer Society, Год журнала: 2024, Номер 5, С. 195 - 214
Опубликована: Янв. 1, 2024
The metaverse is currently undergoing a profound transformation, fundamentally reshaping our perception of reality. It has transcended its origins to become an expansion human consciousness, seamlessly blending the physical and virtual worlds. Amidst this transformative evolution, numerous applications are striving mould into digital counterpart capable delivering immersive human-like experiences. These envisage future where users effortlessly traverse between dimensions. Taking step forward, affective computing technologies can be utilised identify users' emotional cues convey authentic emotions, enhancing genuine, meaningful, context-aware interactions in world. In paper, we explore how integrating intelligence enhance traditional metaverse, birthing emotionally intelligent (EIM). Our work illuminates multifaceted potential EIM across diverse sectors, including healthcare, education, gaming, automotive, customer service, resources, marketing, urban cyberspace. Through examination these uncover infusing enriches user experiences within metaverse. Nonetheless, journey riddled with challenges, address obstacles hindering realisation EIM's full potential. By doing so, lay groundwork for research endeavours aimed at further refining captivating world EIM.
Язык: Английский
Процитировано
8
Journal of Web Librarianship, Год журнала: 2024, Номер 18(2), С. 39 - 63
Опубликована: Апрель 2, 2024
This study aims to assess the familiarity, understanding, and perceptions of immersive technologies such as Virtual Environments (VEs), Augmented Reality (AR), (VR) among library professionals in India. It seeks determine importance Metaverse literacy for librarians, explore their attitudes toward integrating concepts into services, identify potential benefits, examine perceived barriers hindering adoption libraries. A quantitative research approach was employed, involving a stratified random sampling method gather data from across various universities colleges Familiarity with VEs, AR, VR high, mean scores above 4.0 most items, indicating respondents' strong interest understanding. The emphasized, high (above 4.2) on its significance enhancing services user engagement. Critical identified included cost (mean = 4.13), lack expertise 4.01), privacy concerns 3.51). results underscore need targeted training programs resource allocation support adopting technologies. Adopting libraries can help bridge digital divide promote inclusion.
Язык: Английский
Процитировано
6
International Journal of Machine Learning and Cybernetics, Год журнала: 2025, Номер unknown
Опубликована: Янв. 29, 2025
Язык: Английский
Процитировано
0
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Год журнала: 2024, Номер 17, С. 17007 - 17020
Опубликована: Янв. 1, 2024
In recent years, geospatial big data (GBD) has obtained attention across various disciplines, categorized into earth observation and human behavior data. Identifying patterns from GBD been a vital research focus in the fields of urban management environmental sustainability. This paper reviews evolution mining its integration with advanced artificial intelligence (AI) techniques. consists generated by satellites, sensors, mobile devices, geographical information systems, we categorize based on different perspectives. We outline process demonstrate how it can be incorporated unified framework. Additionally, explore new technologies like large language models (LLM), Metaverse, knowledge graphs, they could make even more useful. also share examples helping city protecting environment. Finally, discuss real challenges that come up when working GBD, such as issues retrieval security. Our goal is to give readers clear view where stands today might go next.
Язык: Английский
Процитировано
4
International Journal of Machine Learning and Cybernetics, Год журнала: 2024, Номер unknown
Опубликована: Авг. 19, 2024
Язык: Английский
Процитировано
2
Elsevier eBooks, Год журнала: 2024, Номер unknown, С. 17 - 28
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
0