CWcollab: A Context-Aware Web-Based Collaborative Multimedia System

2021 ◽  
Author(s):  
Chunxu Tang ◽  
Beinan Wang ◽  
C. Y. Roger Chen ◽  
Huijun Wu
Keyword(s):  
Multimedia System ◽  
Context Aware ◽  
Web Based

Semantic Web-based context-aware service selection in task-computing

2009 ◽  
Vol 29 (3) ◽  
pp. 892-895 ◽  
Author(s):  
Run-cai HUANG ◽  
Yi-wen ZHUANG ◽  
Ji-liang ZHOU ◽  
Qi-ying CAO
Keyword(s):  
Semantic Web ◽  
Service Selection ◽  
Context Aware ◽  
Web Based ◽  
Context Aware Service

New Trends on RIAs Development

2014 ◽  
pp. 323-336
Keyword(s):  
Web 2.0 ◽  
User Interfaces ◽  
Mobile Applications ◽  
Web Technology ◽  
Context Aware ◽  
Internet Applications ◽  
Web Based ◽  
Web 3.0 ◽  
Rich Internet Applications ◽  
The Web

Rich Internet Applications (RIAs) are considered one kind of Web 2.0 application; however, they have demonstrated to have the potential to transcend throughout the steps in the Web evolution, from Web 2.0 to Web 4.0. In some cases, RIAs can be leveraged to overcome the challenges in developing other kinds of Web-based applications. In other cases, the challenges in the development of RIAs can be overcome by using additional technologies from the Web technology stack. From this perspective, the new trends in the development of RIAs can be identified by analyzing the steps in the Web evolution. This chapter presents these trends, including cloud-based RIAs development and mashups-rich User Interfaces (UIs) development as two easily visible trends related to Web 2.0. Similarly, semantic RIAs, RMAs (Rich Mobile Applications), and context-aware RIAs are some of the academic proposals related to Web 3.0 and Web 4.0 that are discussed in this chapter.

Adaptation and Personalization of Web-Based Multimedia Content

2006 ◽  
pp. 284-304 ◽  
Author(s):  
Panagiotis Germanakos ◽  
Constantinos Mourlas
Keyword(s):  
Cognitive Processing ◽  
Service Providers ◽  
User Profile ◽  
Processing Parameters ◽  
Multimedia System ◽  
Multimedia Content ◽  
Web Based ◽  
Three Layer Architecture ◽  
The Subject ◽  
The Relationship

A traditional multimedia system presents the same static content and suggests the same next page to all users, even though they might have widely differing knowledge of the subject. Such a system suffers from an inability to be all things to all people, especially when the user population is relatively diverse. The rapid growth of mobile and wireless communication allowed service providers to develop new ways of interactions, enabling users to become accustomed to new means of multimedia-based service consumption in an anytime, anywhere, and anyhow manner. This chapter investigates the new multi-channel constraints and opportunities emerged by these technologies, as well as the new user-demanding requirements that arise. It further examines the relationship between the adaptation and personalization research considerations, and proposes a three-layer architecture for adaptation and personalization of Web-based multimedia content based on the “new” user profile, with visual, emotional, and cognitive processing parameters incorporated.

ECHO

2010 ◽  
pp. 539-555 ◽  
Author(s):  
Hadas Weinberger
Keyword(s):  
Learning Experience ◽  
Semantic Annotation ◽  
Methodological Approach ◽  
Context Aware ◽  
Web Based ◽  
New Approach ◽  
Approach To Learning ◽  
Web Technologies ◽  
Web Based Learning

In this chapter, we suggest Echo, a model for utilizing Web technologies for the design of Web-based context-aware learning. Web technologies are continuously evolving to enhance information retrieval, semantic annotation, social interactions, and interactive experiences. However, these technologies do not offer a methodological approach to learning. In this chapter, we offer a new approach to Web-based learning, which considers the role of the user in shaping the learning experience. The key feature in Echo is the analysis and modeling of content for the design of a Web-based learning experience in context. There are three elements in Echo: 1) a methodology to guide the learning process, 2) techniques to support content analysis and modeling activities, and 3) a three-layered framework of social-semantic software. Incorporating this framework facilitates knowledge organization and representation. We describe our model, the methodology, and the three-layered framework. We then present preliminary results from on-going empirical research that demonstrates the feasibility of Echo and its usefulness for the design of a context-aware learning experience. Finally, we discuss the usefulness of Echo and its contribution to further research in the field of Web technologies.

scholarly journals Every Cloud Has a Push Data Lining: Incorporating Cloud Services in a Context-Aware Application

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Tor-Morten Grønli ◽  
Jarle Hansen ◽  
Gheorghita Ghinea ◽  
Muhammad Younas
Keyword(s):  
Cloud Services ◽  
User Needs ◽  
Context Aware ◽  
Multiple Sources ◽  
Web Based ◽  
Mobile Client ◽  
Automatic Adaptation ◽  
Key Features ◽  
Calendar Data ◽  
Push Messaging

We investigated context-awareness by utilising multiple sources of context in a mobile device setting. In our experiment we developed a system consisting of a mobile client, running on the Android platform, integrated with a cloud-based service. These components were integrated using push messaging technology. One of the key features was the automatic adaptation of smartphones in accordance with implicit user needs. The novelty of our approach consists in the use of multiple sources of context input to the system, which included the use of calendar data and web based user configuration tool, as well as that of an external, cloud-based, configuration file storing user interface preferences which, pushed at log-on time irrespective of access device, frees the user from having to manually configure its interface. The system was evaluated via two rounds of user evaluations (n= 50 users), the feedback of which was generally positive and demonstrated the viability of using cloud-based services to provide an enhanced context-aware user experience.

scholarly journals Mining Smart Learning Analytics Data Using Ensemble Classifiers

2020 ◽  
Vol 15 (12) ◽  
pp. 81
Author(s):  
Samina Kausar ◽  
Solomon Sunday Oyelere ◽  
Yass Khudheir Salal ◽  
Sadiq Hussain ◽  
Mehmet Akif Cifci ◽  
...  
Keyword(s):  
Learning Analytics ◽  
Recent Progress ◽  
Educational Systems ◽  
Context Aware ◽  
Ensemble Classifiers ◽  
Ubiquitous Learning ◽  
Web Based ◽  
Smart Learning ◽  
Ensemble Techniques ◽  
Intelligent Tools

Recent progress in technology has altered the learning behaviors of students; besides giving a new impulse which reshapes the education itself. It can easily be said that the improvements in technologies empower students to learn more efficiently, effectively and contentedly. Smart Learning (SL) despite not being a new concept describing learning methods in the digital age- has caught attention of researchers. Smart Learning Analytics (SLA) provides students of all ages with research-proven frameworks, helping students to benefit from all kinds of resources and intelligent tools. It aims to stimulate students to have a deep comprehension of the context and leads to higher levels of achievements. The transformation of education to smart learning will be realized by reengineering the fundamental structures and operations of conventional educational systems. Accordingly, students can learn the proper information yet to support to learn real-world context, more and more factors are needed to be taken into account. Learning has shifted from web-based dumb materials to context-aware smart ubiquitous learning. In the study, a SLA dataset was explored and advanced ensemble techniques were applied for the classification task. Bagging Tree and Stacking Classifiers have outperformed other classical techniques with an accuracy of 79% and 78% respectively.

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