Substantial research in the field of context modeling has explored aspects related to the use of contextualization in various mobile scenarios. The current context of a mobile user has been often limited to his/her current position, neglecting the possibilities offered by modern mobile devices of providing a much richer representation of the current user's context. This research aims to improve the usability of users' context in the mobile software development process. Therefore, this paper presents the proposal of a rich context model (RCM) as general approach for context modeling to explore the context of the users in different application domains.
Modern mobile devices provide a profound set of sensors and, together with internet connectivity, rich possibilities to present the information with respect to the users’ current needs, independently of time and space (anywhere and anytime). The context of the user plays an important role in providing personalized services and has considerable impact on users’ decision making. Considering a rich context information helps to understand many user characteristics (e.g., what the user is going to do, what the user needs to perform his/her current action, etc.) and to recommend a relevant content/information to the user in the right time and place. The contextualization of mobile users can enhance many of existing services and mobile applications by making them sensible to the users’ current situation. Currently on the Android Marketplace, more than 500 mobile applications were found, that belong to category of personalization. The most popular and used mobile application is Personalized Launcher that provides for users e.g., defining their custom gestures, actions for swiping on app shortcuts, hide/show the most used/unused mobile apps, smart home screens, personal privacy settings and more. However, current existing solutions consider limited number of context information (e.g., current user GPS location, weather information) and provide context-modeling techniques that mostly target a specific application domain. Therefore, we believe that with better understanding of the users’ current context the mobile app can better serve specific user needs. Modern mobile devices provide possibilities to gather the context information from different mobile sensors, external sensors connected to the mobile device via Bluetooth, smartwatch sensors, activity tracker bands, and to extend/enrich all of this data by using additional Web Service APIs. In our research, we define the rich context as: “Any information that describes a situation of the user, not only received from different mobile sensors, which could be extended by additional Web Services, but which also derives/use a meaningful interpretation of this information for the current user need.”
The main purpose of this research is to design and explore the applicability and reusability of a rich context model (RCM) in different application domains. This will lead to the development of a general context model and deploy it as cloud-based Contextualized Service that enables software developers to easily and fast develop contextualized mobile applications. In contrast to existing approaches, our approach will improve the applicability of the context modeling techniques in the development of personalized mobile applications, preventing re-coding and re-designing a new context model again and again depending on the application domain. Instead of this, the developers should know just the target users, what the app should do and which context data is needed to provide the best recommendations for the target users.
The remaining part of the paper is organized as follows. Section 2 overviews related work and defines the open problem and issues in the related research domain. In Section 3, we define the research questions and present the research goal with objectives. In Section 4, we describe the research methodology and the proposed approach. Section 5 presents the current stage of our research and results achieved so far. Finally, Section 6 concludes with plans for further research.
Up to now, a number of approaches and techniques have been developed and introduced for context modeling. Many studies show their benefits and applicability in different application domains [1, 2]. In the following sub-sections 2.1 and 2.2, we describe the most recent and used approaches for context modeling together with context-aware frameworks for developing contextualized mobile applications.
Recent used approaches to context modeling can be broadly classified into three main categories.
Multidimensional context modeling approach. This is one of the first
approaches proposed in [
Object-role based models. This modeling approach was adopted from the
database modeling field [
Ontology-based models. This approach has been widely used in modeling of
complex context situations. Using ontologies provides a uniform way for specifying
the model’s core concepts as well as an arbitrary amount of sub-concepts and facts,
altogether enabling contextual knowledge sharing and reuse in an ubiquitous
computing system [
The analyses of context modeling approaches and survey results [
During the literature review, we have found that most of existing frameworks provide
personalization rather then contextualization for mobile applications. The difference
between these two concepts is that personalization1 based on the user’s behaviour and
device/application usage provides recommendation to suit personal user preferences.
Examples of personalization can be offering services or products based on the user’s
search history, earlier purchase or favourite items (e.g., book author, movie director),
and adapting a user interface based on the user’s history of interactions with mobile
applications [
Based on the survey [
We propose an approach that uses the general concepts introduced in the multidimensional approach for context modeling and use its flexibility to improve the existing context models.
Many researchers have been working on developing a general solution for context
modeling. However, a major problem with this kind of models is limited usability due
to their applicability for a specific application domain. Most of them require
additional changes in the core model that takes time, effort and knowledge of a framework
that can be time consuming for software developers. In the purpose of solving this
problem, we need to answer the following research questions:
- How can we model the context in a scenario independent way for mobile
applications?
- How can this context model be used/adapted for a specific mobile scenario?
- What kind of personalized features can be provided by the contextualization
approach in order to improve existing mobile services and applications?
Based on the research questions, the main and primarily objectives of our work are:
- to empirically investigate the modeling of different context data during the
context model design
- to develop a prototype to discover an abstract representation of the context
model
- to evaluate the proposed context model in several user studies in different
application domains
- to identify the contextualized features for mobile applications
1 https://www.techopedia.com/definition/14712/personalization
2 https://www.wordnik.com/words/contextualization
The primary research approach adopted to perform this work is based on the design
science research methodology (DSRM) proposed in [
The problem identification, motivation and definition of the objectives have been described in the previous sections. The next sub-sections describe the details of each activity and what was done in the first iteration. The current action is highlighted in the Figure 1 and described in sub-section 4.1.
This step consists of designing our approach for context modeling and building an artifact of RCM. In the first iteration, the main objective was to define an approach with certain abstraction for modeling and organizing the context information independently from the scenario point of view. Here, we perform several actions shown in Figure 2.
We took as basis a multidimensional approach for context modeling and in
particularly the multi-dimensional vector space model (MVSM) [
After each performed study, the first three actions are iterated to improve the context model (e.g., make it more abstract, add/replace data processing algorithms) that should lead to providing better suggestions/recommendation results.
In the first iteration, the first prototype was developed using the jQueryMobile
framework with the Cordova API for mobile application and the NodeJs framework
for implementing our contextualization approach. To demonstrate and test the
prototype, we performed two studies in mobile learning and people-to-people
recommendation domains. The obtained results were published in two scientific conferences
[
The evaluation is carried out using adopted TAM questionnaires in particularly
Perceived Usefulness and Perceived Ease of Use. In the first study [
Currently, we are developing a second prototype of our contextualization approach. Here, firstly we went through Design and Development action to apply new changes that were defined after the first two studies. Secondly, we target to deploy the second prototype as a service in the cloud environment and evaluate it in several application domains.
The validation of proposed RCM is carried out using defined metrics and
characteristics introduced in study [
The identified problem and the proposed artifact are communicated to researches
through several publications at conferences. Our first paper was published at mLearn
conference [
The main contribution of this research work is an approach for the development of contextualized mobile applications. In contrast to the existing approaches, our approach has flexibility gained through an abstract context model that could be applied to different application domains without the need for a change in the core context model. Our approach suggests a new contextualization service that provides possibility to develop highly personalized mobile applications. With the employment of our approach, mobile software developers will be able to easily develop contextualized mobile applications for their target users and may raise the number of satisfied users hopefully leading to the increase number of potential users.
Further research will be more focusing on defining the features that our contextualization approach can provide. It will include analyses of already existing contextualized features of personalized mobile apps in the market place, gathering main requirements for developing personalized mobile apps from several mobile software developers, the development of Contextualization Service, evaluation in different application domains, and validation. This plan will help to answer the second and third research question of this work. The expected results are the classification of features and potentially of creating customized mobile app features for different application domains and users.