scholarly journals Paas EUD Tool for Developing Expert Context-Aware Mobile Applications

2021 ◽  
Vol 10 (2) ◽  
pp. 215-224
Author(s):  
Sahar Elshafei ◽  
◽  
Ehab Hassanein ◽  
Hanan Elazhary ◽  
◽  
...  
Keyword(s):  
Mobile Applications ◽  
Expert Knowledge ◽  
Contextual Information ◽  
Quality Data ◽  
Software Systems ◽  
Context Aware ◽  
Software Developers ◽  
Platform As A Service ◽  
Context Data ◽  
Current Context

Context-awareness enables systems to be tailored to the needs of users and their real circumstances at certain times. A noteworthy trend in software development is that an increasing number of software systems are being developed by individuals with expert knowledge in other sectors. Because most of the current context-aware development toolkits are intended for software developers, these types of systems cannot be easily developed by non-technical consumers. The development of tools for designing context-aware frameworks by consumers who are not programming experts but are specialists in the area of implementation would result in faster adoption of such services by businesses. This paper provides a cloud-based framework for people without programming experience to create context-aware mobile applications. The platform can provide a lightweight distribution of packaged applications that allows experts to send specified information to mobile users based on their context data without overlapping between the rules of the application. An energy-efficient mobile application was developed to acquire contextual information from the user device and to create quality data accordingly. The framework adopts Platform as a Service (PaaS) and containerization to facilitate development of context-aware mobile applications by experts in various domains rather than developing a tool for each domain in isolation, while considering multitenancy.

Context-Aware Mobile System for Public Bus Transportation

2014 ◽  
pp. 102-111
Author(s):  
Mitja Krajnc ◽  
Vili Podgorelec ◽  
Marjan Heričko
Keyword(s):  
Context Awareness ◽  
Mobile Applications ◽  
User Interaction ◽  
Context Aware ◽  
Mobile System ◽  
Activity Prediction ◽  
Context Data ◽  
Current Context ◽  
Windows Phone ◽  
Bus Transportation

The spread of smartphones in recent years announced an era of smarter and advanced mobile applications that not only show information but also adapt themselves to users’ surroundings. In this chapter, the authors present a context-aware mobile system in public bus transportation domain based on Windows Phone platform. The principal objective of this system is using users’ location, identity, and timeframe as context data to tailor shown information according to users’ needs. Together with users’ previous actions, the system predicts intended activity in the form of presenting users with preferred bus lines in the current context. The developed system shows how context-awareness and activity prediction can be combined to create mobile applications that do not require a lot of user interaction but still offer detailed information about specific domains.

scholarly journals CFDIL: A Context-aware Feature Deep Interaction Learning for  App Recommendation

2021 ◽  
Author(s):  
Qingbo Hao ◽  
Ke Zhu ◽  
Chundong Wang ◽  
Peng Wang ◽  
Xiuliang Mo ◽  
...  
Keyword(s):  
Mobile Applications ◽  
Historical Data ◽  
Contextual Information ◽  
Rapid Development ◽  
User Preferences ◽  
Mobile Internet ◽  
Context Aware ◽  
Interaction Data ◽  
Learning Potential ◽  
The One

Abstract The rapid development of Mobile Internet has spa-wned various mobile applications (apps). A large number of apps make it difficult for users to choose apps conveniently, causing the app overload problem. As the most effective tool to solve the problem of app overload, the app recommendation has attracted extensive attention of researchers. Traditional recommendation methods usually use historical data of apps used by users to explore their preferences, and then make an app recommendation list for users. Although the traditional app recommendation methods have achieved certain results, the performance of app recommendation still needs to be improved due to the following two reasons. On the one hand, it is difficult to construct traditional app recommendation models when facing with the sparse user-app interaction data. On the other hand, contextual information has a large impact on users’ app usage preferences, which is often overlooked by traditional app recommendation methods. To overcome the aforementioned problems, we proposed a Context-aware Feature Deep Interaction Learning (CFDIL) method to explore user preferences, and then perform app recommendation by learning potential user-app relationships in different contexts. The novelty of CFDIL is as follows: (1) CFDIL incorporates contextual features into users' preferences modeling by constructing a novel user and app feature portrait. (2) The problem of data sparsity is effectively solved by the use of dense user and app feature portraits, as well as the tensor operations for label sets. (3) CFDIL trains a new deep network structure, which can make accurate app recommendation using the contextual information and attribute information of users and apps. We applied CFDIL on three real datasets and conducted extensive experiments, which showed that CFDIL outperformed the benchmark method.

Infrastructures for Development of Context-Aware Mobile Applications

2011 ◽  
pp. 1104-1118
Author(s):  
Hugo Feitosa de Figueirêdo ◽  
Tiago Eduardo da Silva ◽  
Anselmo Cardoso de Paiva ◽  
José Eustáquio Rangel de Queiroz ◽  
Cláudio De Souza Baptista
Keyword(s):  
Mobile Devices ◽  
Mobile Applications ◽  
Contextual Information ◽  
Wireless Networking ◽  
Context Aware ◽  
Context Model ◽  
Technological Advances ◽  
Communication Method ◽  
Context Aware System

Context-aware mobile applications are becoming popular, as a consequence of the technological advances in mobile devices, sensors and wireless networking. Nevertheless, developing a context-aware system involves several challenges. For example, what will be the contextual information, how to represent, acquire and process this information and how it will be used by the system. Some frameworks and middleware have been proposed in the literature to help programmers to overcome these challenges. Most of the proposed solutions, however, neither have an extensible ontology-based context model nor uses a communication method that allows a better use of the potentialities of the models of this kind.

scholarly journals CONTEXT-AWARE INTERACTION AND NAVIGATION IN MOBILE GAMES

2006 ◽  
Vol 35 (3) ◽  
Author(s):  
Silke Jahn ◽  
Aizhen Liu ◽  
Mihail Dimitrov ◽  
Michail Mazo ◽  
Friedrich Jürgen ◽  
...  
Keyword(s):  
Human Computer Interaction ◽  
Mobile Phones ◽  
Mobile Applications ◽  
Contextual Information ◽  
Context Aware ◽  
Next Generation ◽  
Mobile Games ◽  
Mobile Game ◽  
Usability Problems ◽  
Computer Interaction

In this paper an approach of using contextual information for structuring and displaying menus on small devices will be discussed, based on the implementation of a game for mobile games. CitizenMOB is a location-based, multiplayer, never-ending society-driven strategic mobile game that has been developed in order to understand today's possibilities and challenges in the design of complex games for mobile phones. Integrating a context-aware navigation and adaptive menu structure is an attempt not only to reflect the effect of new contexts of use on human-computer-interaction, it is also meant to overcome usability problems that occur when limitations of small screens are combined with complex rules and massive options in the next generation of rich mobile applications.

scholarly journals Using Opinion Mining in Context-Aware Recommender Systems: A Systematic Review

Information ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 42 ◽  
Author(s):  
Camila Sundermann ◽  
Marcos Domingues ◽  
Roberta Sinoara ◽  
Ricardo Marcacini ◽  
Solange Rezende 
Keyword(s):  
Systematic Review ◽  
Recommender Systems ◽  
Digital Libraries ◽  
Opinion Mining ◽  
Contextual Information ◽  
Context Aware ◽  
Extraction Techniques ◽  
Current Context ◽  
Rich Information ◽  
The Rich

Recommender systems help users by recommending items, such as products and services, that can be of interest to these users. Context-aware recommender systems have been widely investigated in both academia and industry because they can make recommendations based on a user’s current context (e.g., location and time). Moreover, the advent of Web 2.0 and the growing popularity of social and e-commerce media sites have encouraged users to naturally write texts describing their assessment of items. There are increasing efforts to incorporate the rich information embedded in user’s reviews/texts into the recommender systems. Given the importance of this type of texts and their usage along with opinion mining and contextual information extraction techniques for recommender systems, we present a systematic review on the recommender systems that explore both contextual information and opinion mining. This systematic review followed a well-defined protocol. Its results were based on 17 papers, selected among 195 papers identified in four digital libraries. The results of this review give a general summary of the current research on this subject and point out some areas that may be improved in future primary works.

scholarly journals Travel Package Booking Application with API BOT

2019 ◽  
Vol 8 (4) ◽  
pp. 10199-10203
Keyword(s):  
User Interface ◽  
Mobile Applications ◽  
Mobile Application ◽  
Contextual Information ◽  
Interactive System ◽  
Context Aware ◽  
Context Aware Computing ◽  
Physical Environments ◽  
Tourist Information ◽  
Better Than

These days we are witnessing many mobile applications based on the recommended systems, which have become a great technology which is been used by the various mobile applications according to the situation. Recommendation provided by the mobile application is a key element for the person who is traveling to several places. For any tourist information application contextual information is much needed to guide the user on his interests this can be achieved by the Context-aware computing. Which provides the user most interactive system with the suggestions provided by it based on the input from the user in a certain location, here context includes the user’s mental, social, physical environments. To achieve this contextual information, we will design and implement the context-aware user interface based on the user for which we have to study the user and design a rich user interface. The final outcome for which users have the satisfaction when using context-aware functionality will be much better than non-context-aware application.

scholarly journals Context-Aware Neural Machine Translation for Korean Honorific Expressions

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1589
Author(s):  
Yongkeun Hwang ◽  
Yanghoon Kim ◽  
Kyomin Jung
Keyword(s):  
Machine Translation ◽  
Deep Neural Networks ◽  
Contextual Information ◽  
Context Aware ◽  
Neural Machine Translation ◽  
Translation Quality ◽  
Sentence Level ◽  
Proposed Model ◽  
The Given ◽  
The Relationship

Neural machine translation (NMT) is one of the text generation tasks which has achieved significant improvement with the rise of deep neural networks. However, language-specific problems such as handling the translation of honorifics received little attention. In this paper, we propose a context-aware NMT to promote translation improvements of Korean honorifics. By exploiting the information such as the relationship between speakers from the surrounding sentences, our proposed model effectively manages the use of honorific expressions. Specifically, we utilize a novel encoder architecture that can represent the contextual information of the given input sentences. Furthermore, a context-aware post-editing (CAPE) technique is adopted to refine a set of inconsistent sentence-level honorific translations. To demonstrate the efficacy of the proposed method, honorific-labeled test data is required. Thus, we also design a heuristic that labels Korean sentences to distinguish between honorific and non-honorific styles. Experimental results show that our proposed method outperforms sentence-level NMT baselines both in overall translation quality and honorific translations.

CASE AND ITS CHALLENGE FOR CHANGE

1991 ◽  
Vol 01 (02) ◽  
pp. 151-163 ◽  
Author(s):  
GREG BOONE
Keyword(s):  
Systems Engineering ◽  
Software Industry ◽  
Software Systems ◽  
Work Practices ◽  
Software Developers ◽  
Productivity Improvement ◽  
Computer Aided ◽  
Difficult Challenge ◽  
Ideological Change ◽  
Productivity Gains

Although the majority of professional trade press and academic attention regarding CASE (Computer Aided Software/Systems Engineering) has focused on technology, software developers have not been deluded by overinflated productivity gains attributed to those technologies. Truly profound technologies require a concomitant change in methods, practices, and techniques. Unfortunately, the majority of the software industry has had the expectation that CASE will automate their current work without rethinking work practices. Changing work practices, particularly among highly independent-minded software developers, who prize independent creativity more than team engineering, is the most difficult challenge facing the advance of the software development profession. Equally difficult is the ideological change from a productivity improvement expectation to a quality improvement expectation. This paper examines the current rate of CASE adoption and the changes necessary to accelerate its successful adoption.

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