Mobile phone-to-phone personal context sharing

Lee, Juong-Sik; Chandra, Umesh

doi:10.1109/iscit.2009.5341003

Cited by 9 publications

(6 citation statements)

References 13 publications

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“…The increasing capability of mobile devices is making it possible to create system architecture that can share personal context to other mobile devices. It is also evident that mobile devices are equipped with various sensors such as GPS, accelerometer, Bluetooth, microphone, camera, calendar, contact list that can capture personal context [11]. Use of mobile device in context sharing with other mobile devices or service providers is gaining importance in the research community of context-aware computing.…”

Section: Overview Of Personalization Approaches and Related Workmentioning

confidence: 99%

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Scrutable Mobile Client-side Personalization

Asif

2015

IJITCS

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Personalization has become an essential feature of mobile services of different domains. On the other hand, users have conflicting needs of personalized experience and privacy. This leads to the question of how to maximize the user's experience of personalized mobile services while keeping privacy. One possible solution is to provide user's control of their personal data by keeping their user model on their personal mobile devices. In this way, a user can scrutinize the data while sharing with service providers depending on her/his requirements. The client-side personalization approach can shift the control of privacy to the users and can involve them in personalization process. Transparency and user control can increase the user's trust. In this paper, we have proposed a solution with the objective of scrutable client-side personalization while keeping the user in control of both privacy and personalization process.

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Section: Overview Of Personalization Approaches and Related Workmentioning

confidence: 99%

“…Use of mobile device in context sharing with other mobile devices or service providers is gaining importance in the research community of context-aware computing. The most common architecture for personal context sharing using mobile devices is the centralized server architecture [11].…”

Section: Overview Of Personalization Approaches and Related Workmentioning

confidence: 99%

Scrutable Mobile Client-side Personalization

Asif

2015

IJITCS

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“…For example, Beach et al has explored the implications of sharing social networking IDs locally and they also discuss the privacy implications of such sharing mechanisms [1]. In addition, Lee and Chandra propose a phone-to-phone based context sharing to allow dynamic privacy control [9]. These mechanisms could be relevant when developing the proposed approach further.…”

Section: Related Workmentioning

confidence: 99%

Contextcapture

Antila

Polet

Sarjanoja

et al. 2011

Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments

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In this paper, we investigate the usage of context-based awareness cues in informal information sharing, especially in social networking services. We present an experimental mobile application, which allows users to add different descriptions of context information to their Facebook status updates. The meaningfulness and the usage of different context descriptions were evaluated in a two-week user trial. The results show that the most frequently used awareness cues in the test setting were location, surroundings, friends and activity. The results also indicate that user-defined semantic abstractions of context items (e.g. "home", "work") were often more informative and useful than more accurate indicators (e.g. the address or the name of the place). We also found out that using shared context from friends in vicinity (e.g. identifying the people around) needs careful design to overcome the extended privacy implications.

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“…Although various studies for mobile sharing method have been introduced, most of them only focused on generating "home" community [2][3] [4][5] [6] [7][8] [9]. When "home" communities are generated, they share context or content within "home" community.…”

Section: Introductionmentioning

confidence: 99%

“…Sorathia et al and Lee et al shared the personal context by using the phonebook and synchronization[6,7].…”

mentioning

confidence: 99%

KeyGraph-Based Social Network Generation for Mobile Context Sharing

Lee

Cho

2013

2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical A

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We propose a KeyGraph-based context sharing method in mobile environment. With the recent advancement of mobile sensors, a variety of mobile applications become vehicles for improving our lives. Context sharing system which shares the user behaviors, emotion, and location is one of the promising fields for the social network service. It is a difficult problem to determine whether a user will share the personal information or not. In typical social network models, users are grouped in communities, and nodes of the same community have strong social links between each other. However, some nodes also have social links outside their "home" community. They have social relationships with users of different groups. Most systems concentrate on generating internal "home" community regardless of outside social relation. In this paper, we classify the personal information into two types. First type is the information to be shared with "home" community only. Second type is the information to be shared with as many people as possible. We utilize KeyGraph algorithm to select a home community for sharing the personal contexts. KeyGraph extracts two types of people who have strong social relationships in a community and have social links with many different communities. In order to show the feasibility of the proposed method, we conduct experiments to extract the user communities from Bluetooth data and implement a real-time context sharing application.

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Mobile phone-to-phone personal context sharing

Cited by 9 publications

References 13 publications

Scrutable Mobile Client-side Personalization

Scrutable Mobile Client-side Personalization

Contextcapture

KeyGraph-Based Social Network Generation for Mobile Context Sharing

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