Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Fab: content-based, collaborative recommendation
Communications of the ACM
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Automatic personalization based on Web usage mining
Communications of the ACM
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Understanding and Using Context
Personal and Ubiquitous Computing
Mining Multiple-Level Association Rules in Large Databases
IEEE Transactions on Knowledge and Data Engineering
Handheld Use in K-12: A Descriptive Account
WMTE '02 Proceedings IEEE International Workshop on Wireless and Mobile Technologies in Education
Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
Ubi-learning integrates indoor and outdoor experiences
Communications of the ACM - Interaction design and children
A methodology for a Very Small Data Base design
Information Systems
Educational resources and implementation of a Greek sign language synthesis architecture
Computers & Education
A location-aware recommender system for mobile shopping environments
Expert Systems with Applications: An International Journal
Packet-based context aware system to determine information system user's context
Expert Systems with Applications: An International Journal
Behaviour & Information Technology
Context-aware systems: A literature review and classification
Expert Systems with Applications: An International Journal
Designing collaborative, constructionist and contextual applications for handheld devices
Computers & Education - Virtual learning? Selected contributions from the CAL 05 symposium
Expert Systems with Applications: An International Journal
Feature-based recommendations for one-to-one marketing
Expert Systems with Applications: An International Journal
Surrogate object based data mining for distributed mobile systems
Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia
Computers & Education
Exploiting space-time status for service recommendation
APWeb'12 Proceedings of the 14th international conference on Web Technologies and Applications
Developing a NFC-equipped smart classroom: Effects on attitudes toward computer science
Computers in Human Behavior
Comparing context-aware recommender systems in terms of accuracy and diversity
User Modeling and User-Adapted Interaction
International Journal of Enterprise Information Systems
An NFC based context-aware solution for access to bibliographic sources in university environments
Journal of Ambient Intelligence and Smart Environments - Context Awareness
Hi-index | 12.05 |
Advances in wireless networking, mobile broadband Internet access technology as well as the rapid development of ubiquitous computing means e-learning is no longer limited to certain settings. A ubiquitous learning (u-learning) system must however not only provide the learner with learning resources at any time and any place. However, it must also actively provide the learner with the appropriate learning assistance for their context to help him or her complete their e-learning activity. In the traditional e-learning environment, the lack of immediate learning assistance, the limitations of the screen interface or inconvenient operation means the learner is unable to receive learning resources in a timely manner and incorporate them based on the actual context into the learner's learning activities. The result is impaired learning efficiency. Though developments in technology have overcome the constraints on learning space, an inability to appropriately exploit the technology may make it an obstacle to learning instead. When integrating the relevant information technology to develop a u-learning environment, it is therefore necessary to consider the personalization requirements of the learner to ensure that the technology achieves its intended result. This study therefore sought to apply context aware technology and recommendation algorithms to develop a u-learning system to help lifelong learning learners realize personalized learning goals in a context aware manner and improve the learner's learning effectiveness.