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The electronic calendar usually serves as a personal organizer and is a valuable resource for managing daily activities or schedules of the users. Naturally, a calendar provides various contextual information about individual's scheduled events/appointments, e.g., meeting. A number of researchers have utilized such information to predict human behavior for mobile communication, by assuming a predefined...
Mobile or cellular phones can record various types of context data related to a user's phone call activities. In this paper, we present an approach to discovering individualized behavior rules for mobile users from their phone call records, based on the temporal context in which a user accepts, rejects or misses a call. One of the determinants of an individual's phone behavior is the various activities...
Over the last few years, we are witnessing the proliferation of mobile Internet devices (MIDs) and the wide spread adoption of cloud computing for both personal and corporate usages. These technologies are converging in what is known as mobile cloud computing (MCC) paradigm. This paradigm aims at addressing resource poverty of mobile devices. Several works investigated the challenges of mobile cloud...
Context services typically provide infrastructure support for collection, management, and dissemination of context information concerning a number of subjects. Subjects may be users, objects such as handheld devices and equipment, or the environment of users. We propose, in this paper, a federation of cloud-based context brokers for context services selection. Context Brokers (CBs) of the federation...
This paper discusses issues related to digital storytelling and its use in Cultural Heritage institutions. It will demonstrate the usefulness and advantages of digital storytelling by providing concrete examples of adoption and suggest how digital storytelling may be used in different cultural heritage environments. We will identify issues and challenges and also focus on lessons learnt, all of them...
The recent development of powerful mobile devices is encouraging people to take them as a computing platform. Users are expecting to personalize services to meet their individual needs and will no longer accept “one size fits all” approach. On the other hand, there is contention between personalization and privacy. This leads to the question of how to maximize the user's experience of personalized...
Personalized on demand e-learning has gained traction driven by socio-economic and demographic change. Concomitant with these developments is the revolution in the capability and ubiquity of mobile systems. The result of these developments is interest in personalized e-learning provided on-demand using mobile technologies. Additionally, e-learning is utilizing Web 2.0 technologies to enable personalized...
The primary aim of this study is to investigate the factors influencing audience attitudes towards such location-based advertising. The results indicate that entertainment, personalization and privacy concerns all have direct impacts on consumer attitudes, with situational context moderating the impacts of these factors on such consumer attitudes. We conclude by offering some practical suggestions...
Most tourists today expect a friendly tour guidance and services considering their individual preferences and actual situation while protecting their privacy. The ideal is an intelligent guide taking care of the whole organization and execution in time. This is the main objective of the context-based Personalized Mobile Tourist Guide (PMTG). Tourist's profiles or visiting background is stored in a...
This paper presents a ringtone recommendation agent system which utilizes user's emotion to recommend an appropriate ringtone and the suitable volume level of a mobile phone. The system uses a Bayesian network (BN) to infer user's emotion and the volume level at the current situation. After inferring user's emotion, a ringtone is selected from the pool of various kinds of genres of ringtones. Also,...
Mobile devices are in a widespread use today. Restricted by the features of mobile devices, such as mobility, low communication bandwidth, small capacity of memory, limited power and inconvenient interaction, mobile services are required to recommend items adapting to the user need and location. Much existing research on recommendations ignores semantic information of user dynamic historical preferences...
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