Personalization and visualization on handheld devices

Zhang, Dongsong; Karabatis, George; Chen, Zhiyuan; Adipat, Boonlit; Dai, Li; Zhang, Zhenxue; Wang, Yu

doi:10.1145/1141277.1141517

Cited by 11 publications

(8 citation statements)

References 12 publications

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“…We draw our second example from the area of pervasive or mobile computing [2,29,23]. The premise of pervasive computing is that all the relevant information (at each point in time and space) should be accessible to any mobile user.…”

Section: Profile-driven Data Managementmentioning

confidence: 99%

On space constrained set selection problems

Palpanas

Koudas

Mendelzon

2008

Data & Knowledge Engineering

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Space constrained optimization problems arise in a variety of applications, ranging from databases to ubiquitous computing. Typically, these problems involve selecting a set of items of interest, subject to a space constraint.We show that in many important applications, one faces variants of this basic problem, in which the individual items are sets themselves, and each set is associated with a benefit value. Since there are no known approximation algorithms for these problems, we explore the use of greedy and randomized techniques. We present a detailed performance and theoretical evaluation of the algorithms, highlighting the efficiency of the proposed solutions.

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Section: Profile-driven Data Managementmentioning

confidence: 99%

On space constrained set selection problems

Palpanas

Koudas

Mendelzon

2008

Data & Knowledge Engineering

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“…One of the most notable is real-time information availability (Zhang et al 2006) and higher flexibility for user interface (Van der Heijden and Junglas, 2006). In conjunction with this are the electronic services that can be provided by mobile devices.…”

Section: Mobile Decision Supportmentioning

confidence: 99%

Support for Real-Time Decision Making in Mobile Financial Applications

Burstein¹,

Zaslavsky²,

Pedro³

2008

Handbook on Decision Support Systems 2

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Mobile users making real-time decisions based on current information need confidence about their context been taken into consideration in producing recommendations. This chapter reviews current use of mobile technologies for decision support. Specifically, it describes a framework for assessing the impact of mobility in decision-making. The framework uses dynamic context representation of data quality to represent uncertainties in the mobile computing environment. This framework can be used for developing visual interactive displays for communicating to the user relevant changes in data quality when working in mobile environment. As an illustration, this chapter proposes a real-time decision support procedure that aims at providing on-the-spot assistance to the mobile consumer when choosing the best payment option to efficiently manage the user's budget. The proposed procedure is based on multi-attribute decision analysis, scenario reasoning and a quality of data framework. Feasibility of the approach is demonstrated with a mobile decision support system prototype implementation.

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“…For mobile information visualisation applications, a thin-client approach can be used to develop a rather complex visualisation. The objective of information visualisation [28, 23,22] is met as long as the handheld devices display the desire visualised results. Figure 1 illustrates the architectural design of the proposed visual history mechanism.…”

Section: Mobile Information Visualisationmentioning

confidence: 99%