智能社区移动多媒体推荐研究综述
Mobile Multimedia Recommendation in Smart Communities: A Survey
摘要：
由于互联网宽带接入的快速增长和现代移动设备的激增，各种类型的多媒体（例如，文本、图像、音频和视频）已经变得无处不在地随时可用。移动终端用户通常基于他们的个人兴趣和偏好来存储和使用多媒体内容。然而，诸如存储限制的移动终端挑战已经向用户引入了移动多媒体过载的问题。为了解决这个问题，研究人员开发了各种技术，为移动用户推荐多媒体。在这篇调查论文中，我们从三个智能社区的角度，即移动社会学习，移动事件指南和上下文感知服务，研究移动多媒体推荐系统的重要性。对现有研究的谨慎分析表明，主动的、基于传感器的和混合的推荐系统的实现可以改善移动多媒体推荐。然而，仍然有挑战和开放的问题，如纳入上下文和社会属性，这需要解决，以产生准确和值得信赖的移动多媒体推荐。
英文摘要：
Due to the rapid growth of internet broadband access and proliferation of modern mobile devices, various types of multimedia (e.g. text, images, audios and videos) have become ubiquitously available anytime. Mobile device users usually store and use multimedia contents based on their personal interests and preferences. Mobile device challenges such as storage limitation have however introduced the problem of mobile multimedia overload to users. In order to tackle this problem, researchers have developed various techniques that recommend multimedia for mobile users. In this survey paper, we examine the importance of mobile multimedia recommendation systems from the perspective of three smart communities, namely, mobile social learning, mobile event guide and context-aware services. A cautious analysis of existing research reveals that the implementation of proactive, sensor-based and hybrid recommender systems can improve mobile multimedia recommendations. Nevertheless, there are still challenges and open issues such as the incorporation of context and social properties, which need to be tackled in order to generate accurate and trustworthy mobile multimedia recommendations.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
