An unsupervised approach to modeling personalized contexts of mobile users

Mobile context modeling is a process of recognizing and reasoning about contexts and situations in a mobile environment, which is critical for the success of context-aware mobile services. While there are prior works on mobile context modeling, the use of unsupervised learning techniques for mobile context modeling is still under-explored. Indeed, unsupervised techniques have the ability to learn personalized contexts, which are difficult to be predefined. To that end, in this paper, we propose an unsupervised approach to modeling personalized contexts of mobile users. Along this line, we first segment the raw context data sequences of mobile users into context sessions where a context session contains a group of adjacent context records which are mutually similar and usually reflect the similar contexts. Then, we exploit two methods for mining personalized contexts from context sessions. The first method is to cluster context sessions and then to extract the frequent contextual feature-value pairs from context session clusters as contexts. The second method leverages topic models to learn personalized contexts in the form of probabilistic distributions of raw context data from the context sessions. Finally, experimental results on real-world data show that the proposed approach is efficient and effective for mining personalized contexts of mobile users.     

Contextual usage patterns in smartphone communication services

The mobile end user context has received a lot of attention from the mobile services industry lately. The location-based and context-sensitive information that are characteristic for smartphones can be utilized to study the use context of mobile end users. Accordingly, this article utilizes handset-based data in analyzing how the context of use affects the usage of smartphone communication services. The context is identified with an algorithm utilizing mobile network cell ID and WLAN data and resulting in five place-related contexts, namely Home, Office, Other meaningful, Elsewhere and Abroad. According to our analysis, voice calls are used least intensively in the Home context where the length of the voice calls is the longest, however. Email and SMS are used most intensively in the Office context, where the voice calls are the shortest in duration. Finally, mobile IM/VoIP and social media services are more free-time oriented as they are used most intensively in Elsewhere and Other meaningful contexts. The findings imply that people use smartphone communication services differently depending on the use context. However, context can be defined and identified in a number of ways, and this article presents only one solution that is highly dependent on the type of data collected.     

Enabling Routes of Road Network Constrained Movements as Mobile Service Context

With the continuing advances in wireless communications, geo-positioning, and portable electronics, an infrastructure is emerging that enables the delivery of on-line, location-enabled services to very large numbers of mobile users. A typical usage situation for mobile services is one characterized by a small screen and no keyboard, and by the service being only a secondary focus of the user. Under such circumstances, it is particularly important to deliver the “right” information and service at the right time, with as little user interaction as possible. This may be achieved by making services context aware. Mobile users frequently follow the same route to a destination as they did during previous trips to the destination, and the route and destination constitute important aspects of the context for a range of services. This paper presents key concepts underlying a software component that identifies and accumulates the routes of a user along with their usage patterns and that makes the routes available to services. The problems associated with of route recording are analyzed, and algorithms that solve the problems are presented. Experiences from using the component on logs of GPS positions acquired from vehicles traveling within a real road network are reported.

Understanding the behavior of mobile data services consumers

Due to rapid advances in the Internet and wireless technologies, a ubiquitous computing world is becoming a reality in the form of mobile computing. At the center of this phenomenon is mobile data services which arise from the convergence of advanced mobile communication technologies with data services. Despite the rapid growth in mobile data services, research into consumers’ usage behavior is scarce. This study attempts to identify and empirically assess the factors that drive consumers’ acceptance of mobile data services. A research model based on the decomposed theory of planned behavior and incorporating factors that represent personal needs and motivations in using mobile data services is presented. The model is tested via an online survey of 811 consumers of four categories of mobile data services (i.e., communications, information content, entertainment, and commercial transactions) associated with different usage contexts. We found that attitude, social influence, media influence, perceived mobility, and perceived monetary value influence consumers’ intention to continue usage of mobile data services. In addition, perceived ease of use, perceived usefulness, and perceived enjoyment influence attitude toward continued usage of mobile data services. Finally, separate analysis of the different categories of mobile data services highlights the influence of individual usage context on consumers’ behavior.

An Ontology-Based Approach to Personalized Situation-Aware Mobile Service Supply

Mobile devices such as personal digital assistants (PDAs) and mobile phones are in widespread use already today and converging to mobile smart phones. They enable users to access a wide range of services and information without guidance through their actual demands. Especially during mass events like the Olympic Games 2008 in Beijing—which was initially the context of our work—a large service space is expected to support all mobile visitors, being athletes, journalists, or spectators. Current approaches tackling such problems are location based, meaning that a user's location is central to service provision, and even context-aware, meaning that, beyond location, characteristics of a user's environment are taken into account. Such information obviously helps to deliver relevant information at the right time to the mobile users. Going one step further, a situation-aware system abstracts from the context dimensions by translating specific contexts into logical situations. Knowing the situation end users are in allows the system to better identify the information to be delivered to them and to choose the appropriate services with regard to their scope, which is referred to as service roaming. Even though many context frameworks have been introduced in the past few years, what is usually missing is the notion of characteristic features of contexts that are invariant during certain time intervals. This paper presents these concepts in the context of a platform development, namely FLAME2008, which is able to support its mobile users with personalized situation-aware services in push and pull mode.     

Mobile home automation: merging mobile value added services and home automation technologies

In this paper we study mobile home automation, a field that emerges from an integration of mobile application platforms and home automation technologies. We motivate our research and provide a conceptual introduction, which illustrates the need for such applications by a two-dimensional conceptual model of mobility. As a first steps towards a solution we take the user’s perspective and discuss different options of how he might access a mobile home automation service and the controlled devices. Subsequently, we suggest a general system architecture for mobile home automation services and discuss related design decision. This design has been implemented in a research prototype, which we named Remotile. This helps us to discuss typical components, such as modules that integrate various home automation devices. A previous version of this paper was presented at the Sixth International Conference on Mobile Business, 2007. “Andreas Rosendahl, J. Felix Hampe, and Goetz Botterweck, Mobile Home Automation, Merging Mobile Value Added Services and Home Automation Technologies, Proceedings, Sixth International Conference on Mobile Business, 8–11 July 2007, IEEE Computer Society, ISBN 0-7695-2803-1”.     

Look, Ma, My homepage is Mobile!

Much of the ongoing research in ubiquitous computing has concentrated on providing context information, e.g. location information, to the level of services and applications. Typically, mobile clients obtain location information from their environment which is used to provide “locally optimal” services. In contrast, it may be of interest to obtain information about the current context a mobile user or device is in, from a client somewhere on the Web, i.e. to use the mobile device as an information provider for Internet clients. As an instance of such services we propose the metaphor of a “location-aware” Web homepage of mobile users providing information about, e.g. the current location a mobile user is at. Requesting this homepage can be as easy as typing a URL containing the mobile user's phone number such ashttp://mhp.net/+49123456789 in an off-the-shelf browser. The homepage is dynamically constructed as Web users access it and it can be configured in various ways that are controlled by the mobile user. We present the architecture and implementation and discuss issues around this example of “inverse” ubiquitous computing.     

Support for real-time decision making in mobile financial applications

Mobile users making real-time decisions based on current information need confidence that their context has been taken into consideration in producing the system’s recommendations. This chapter reviews current use of mobile technologies for context-aware real-time decision support. Specifically, it describes a framework for assessing the impact of mobility in decision making. The framework uses dynamic context model of data quality to represent uncertainties in the mobile decision-making 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 environments. As an illustration, this chapter proposes a real-time decision support procedure for on-the-spot assistance to the mobile consumer when choosing the best payment option to efficiently manage their budget. The proposed procedure is based on multi-attribute decision analysis, scenario reasoning, and a quality of data framework. The feasibility of the approach is demonstrated with a mobile decision-support system prototype implementation. This article is part of the “Handbook on Decision Support Systems” edited by Frada Burstein and Clyde W. Holsapple (2008) Springer.     

User needs for location-aware mobile services

Mobile contexts of use vary a lot, and may even be continuously changing during use. The context is much more than location, but its other elements are still difficult to identify or measure. Location information is becoming an integral part of different mobile devices. Current mobile services can be enhanced with location-aware features, thus providing the user with a smooth transition towards context-aware services. Potential application fields can be found in areas such as travel information, shopping, entertainment, event information and different mobile professions. This paper studies location-aware mobile services from the user's point of view. The paper draws conclusions about key issues related to user needs, based on user interviews, laboratory and field evaluations with users, and expert evaluations of location-aware services. The user needs are presented under five main themes: topical and comprehensive contents, smooth user interaction, personal and user-generated contents, seamless service entities and privacy issues.     

SpaceGlue: linking spaces for adaptive service location

We describe a mechanism called SpaceGlue for adaptively locating services based on the preferences and locations of users in a distributed and dynamic network environment. In SpaceGlue, services are bound to physical locations, and a mobile user accesses local services depending on the current space he/she is visiting. SpaceGlue dynamically identifies the relationships between different spaces and links or “glues” spaces together depending on how previous users moved among them and used those services. Once spaces have been glued, users receive a recommendation of remote services (i.e., services provided in a remote space) reflecting the preferences of the crowd of users visiting the area. The strengths of bonds are implicitly evaluated by users and adjusted by the system on the basis of their evaluation. SpaceGlue is an alternative to existing schemes such as data mining and recommendation systems and it is suitable for distributed and dynamic environments. The bonding algorithm for SpaceGlue incrementally computes the relationships or “bonds” between different spaces in a distributed way. We implemented SpaceGlue using a distributed network application platform Ja-Net and evaluated it by simulation to show that it adaptively locates services reflecting trends in user preferences. By using “Mutual Information (MI)” and “F-measure” as measures to indicate the level of such trends and the accuracy of service recommendation, the simulation results showed that (1) in SpaceGlue, the F-measure increases depending on the level of MI (i.e., the more significant the trends, the greater the F-measure values), (2) SpaceGlue achives better precision and F-measure than “Flooding case (i.e., every service information is broadcast to everybody)” and “No glue case” by narrowing appropriate partners to send recommendations based on bonds, and (3) SpaceGlue achieves better F-measure with large number of spaces and users than other cases (i.e., “flooding” and “no glue”). Tomoko Itao is an alumna of NTT Network Innovation Laboratories     

What are a Location’s “File” and “Edit” Menus?

The promise of mobile devices lies not in their capacity to duplicate the capabilities of desktop machines, but rather in their promise of enabling location-specific tasks. One of the challenges that must be addressed if they are to be used in this way is how intuitive interfaces for mobile devices can be designed that enable access to location-specific services usable across locations. We are developing a prototype mobile valet application that presents location-specific services organised around the tasks associated with a location. The basic elements of the interface exploits commonalties in the way we address tasks at various locations just as the familiar “file” and “edit” menus in various software applications exploit regularities in software tasks.     

The Human Communication Space: Towards I-centric Communications

In the last few years, a variety of concepts for service integration and corresponding systems have been developed. On the one hand, they aim for the interworking and integration of classical telecommunications and data communications services. On the other, they are focusing on universal service access from a variety of end-user systems. Many of the technical problems, resulting from the service integration, and service personalisation have been solved during the last years. However, all these systems are driven by the concept of providing several technologies to users by keeping the peculiarity of each service.  Looking at humans’ communication behaviour and their communication space, it is obvious that human beings interact habitually in a set of contexts with their environment. The individual information preferences and needs, persons to interact with, and the set of devices controlled by each individual define their personal communication space. Following this view, a new approach is to build communication systems not on the basis of specific technologies, but on the analysis of the individual communication spaces. The result is a communication system adapted to the demands of each individual (I-centric). The communication system will act on behalf of users’ demands, reflecting recent actions to enable profiling and self-adaptation to contexts and situations.  In this paper, we introduce I-centric Communications, an approach to design communication systems that adapt themselves to the individual communication space and individual environment and situation. In this context “I” means I, or individual, “Centric” means adaptable to I requirements and a certain user environment.     

Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits

Mobile payment is an emerging and important application of mobile commerce. The adoption and use of mobile payment services are critical for both service providers and investors to profit from such an innovation. The present study attempts to identify the determinants of pre-adoption of mobile payment services and explore the temporal evolution of these determinants across the pre-adoption and post-adoption stages from a holistic perspective including behavioral beliefs, social influences, and personal traits. A research model that reflects the characteristics and usage contexts of mobile payment services is developed and empirically tested by using structural equation modeling on datasets consisting of 483 potential adopters and 156 current users of a mobile payment service in China. Our findings show that behavioral beliefs in combination with social influences and personal traits are all important determinants for mobile payment services adoption and use, but their impacts on behavioral intention do vary across in different stages. Theoretical and practical implications of the findings are presented.     

Limited context semantic translation from a single knowledge-base for a natural language and structuring metarules

The article introduces an experimental system which produces multilingual semantic translations from relatively short texts from a given context. The system was conceived as an investigation instrument whose characteristics are the following: —the elaboration of a single analyzer and generator able to receive, in the form of data, specific information concerning national language, within the limits of a given area of application; —the use of exclusively semantic internal representation, whose formation is derived from “frames” (an object is defined as a list of “attribute-value” couples, permitting recursion); —a single knowledge-base is used for each natural language as initial data (the grammar transmitted was of a semantic-syntacticatn type); —the structure of grammar used in computer language processing being rarely as well adapted to analysis as to generation, the system itself is provided with the possibility of transforming and reorganizing the information for more efficient use at one stage of processing (thus, theatns are used directly in analysis, whereas for the purposes of generation they are “explored” and their information reorganized); —to produce a text, the use of general structuring principles (independent of language) are experimented with. These principles are given in the form of metarules. The application of these metarules to the restructured grammar of a natural language produces specific structuration rules, peculiar to this language. Although the system was conceived for any conceptual area or language, the present knowledge-base of the system (the experimental support) is based on a collection of elementary exercises in three-dimensional geometry written in Rumanian and in French. She does research in the CNRS group C.F. Picard headed by Professor Pitrat, University of Paris 6.     

Near field communication: an assessment for future payment systems

In this paper, we present an assessment of near field communication (NFC) in the context of a payment market. During these past years, we have been witnessing a number of mobile payment trials based on NFC. Early experiences are already quite encouraging and many expect NFC to become a highly efficient and effective technology for mobile payments. The objective of our research is to evaluate in a systematic manner the potential of NFC as an upcoming technology for mobile payments. In order to ensure the rigor of our research, we used a formal and structured approach based on multi-actor multi-criteria methods. Our research provides one of the first assessment of NFC and a realistic picture of the current Swiss situation as we involved numerous mobile payment experts. Our findings show that Swiss industry experts are quite enthusiastic about the future of NFC. A previous version of this paper was presented at the 6th international conference on mobile business, 2007. “Jan Ondrus, Yves Pigneur, An assessment of NFC for Future Payment Systems, Proceedings, Sixth International Conference on Mobile Business, 8–11 July 2007, IEEE Computer Society, ISBN 0-7695-2803-1.”     

Habits make smartphone use more pervasive

Examining several sources of data on smartphone use, this paper presents evidence for the popular conjecture that mobile devices are “habit-forming.” The form of habits we identified is called a checking habit: brief, repetitive inspection of dynamic content quickly accessible on the device. We describe findings on kinds and frequencies of checking behaviors in three studies. We found that checking habits occasionally spur users to do other things with the device and may increase usage overall. Data from a controlled field experiment show that checking behaviors emerge and are reinforced by informational “rewards” that are very quickly accessible. Qualitative data suggest that although repetitive habitual use is frequent, it is experienced more as an annoyance than an addiction. We conclude that supporting habit-formation is an opportunity for making smartphones more “personal” and “pervasive.”     

Universal technique for optimization of neural network training parameters: gasoline near infrared data example

The universal technique of finding optimum training parameters for multi-layer perceptron—such as percentage of samples in a cross-validation set and quantities of training iterations with various initial values—is offered. This technique is aimed at the searching of optimum values of two complex factors depending on accuracy and convergence of a network, and also on the time of its training. Their conventional names are “cross-validation coefficient” and “training iteration coefficient”. Near infrared spectroscopy data for gasoline samples are used to evaluate the efficiency of the method.     

Joint contexts optimization for mobile grid

This paper presents joint contexts optimization in mobile grid. The paper describes device context information for context-aware services in the mobile device collaboration. The objective of the paper is to dynamically deliver services to mobile grid users according to current context of mobile grid environment. A utility function is used as objective function that expresses values for the current contexts. The optimization is carried out by the joint context parameter optimizer with respect to an objective function. A joint contexts optimization algorithm is proposed which decomposes mobile grid system optimization problem into sub-problems. In the experiment, the performance evaluation of joint contexts optimization algorithm is conducted.     

Exploring the dual outcomes of mobile social networking service enjoyment: The roles of social self-efficacy and habit

Enjoyment experience has been generally regarded as a positive element which can drive various aspects of system usage. Little research has examined its potential adverse outcomes, especially in an emerging mobile services context. This study investigates the dual effects of enjoyment on mobile social networking service (Mobile SNS) usage behaviors by focusing on not only its positive outcomes but also its potential adverse consequences. In addition, this study explores the impacts of social self-efficacy and habit on these dual causal processes. A research model is developed and empirically tested using data collected from 398 mobile SNS users in China. The structural equation modeling analysis results indicate that enjoyment significantly affects both mobile SNS high engagement and mobile SNS addiction behaviors. Mobile SNS habit mediates the associations between mobile SNS enjoyment and mobile SNS addiction behaviors. Social self-efficacy directly affects mobile SNS users' enjoyment experience, and it also has important indirect impacts on the dual processes by effectively enhancing mobile SNS users' high engagement and alleviating their addiction behaviors. The theoretical and practical implications of our findings are also discussed.     

Mobile social group sizes and scaling ratio

Social data mining has become an emerging area of research in information and communication technology fields. The scope of social data mining has expanded significantly in the recent years with the advance of telecommunication technologies and the rapidly increasing accessibility of computing resources and mobile devices. People increasingly engage in and rely on phone communications for both personal and business purposes. Hence, mobile phones become an indispensable part of life for many people. In this article, we perform social data mining on mobile social networking by presenting a simple but efficient method to define social closeness and social grouping, which are then used to identify social sizes and scaling ratio of close to “8”. We conclude that social mobile network is a subset of the face-to-face social network, and both groupings are not necessary the same, hence the scaling ratios are distinct. Mobile social data mining.