Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
A multilevel approach to intelligent information filtering: model, system, and evaluation
ACM Transactions on Information Systems (TOIS)
WebMate: a personal agent for browsing and searching
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
User Modeling for Adaptive News Access
User Modeling and User-Adapted Interaction
PVA: A Self-Adaptive Personal View Agent
Journal of Intelligent Information Systems
A Middleware Infrastructure for Active Spaces
IEEE Pervasive Computing
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
Context-Aware Support for Computer-Supported Ubiquitous Learning
WMTE '04 Proceedings of the 2nd IEEE International Workshop on Wireless and Mobile Technologies in Education (WMTE'04)
A Framework of Ubiquitous Learning Environment
CIT '04 Proceedings of the The Fourth International Conference on Computer and Information Technology
Ubi-learning integrates indoor and outdoor experiences
Communications of the ACM - Interaction design and children
Pervasive, Persuasive eLearning: Modeling the Pervasive Learning Space
PERCOMW '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications Workshops
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Context Model and Context Acquisition for Ubiquitous Content Access in ULearning Environments
SUTC '06 Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing - Vol 2 - Workshops - Volume 02
Unifying user-based and item-based collaborative filtering approaches by similarity fusion
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
MHS Learning Services for Pervasive Campus Environments
PERCOMW '06 Proceedings of the 4th IEEE international workshop on Pervasive Computing and Communications Workshops: supplement papers
Effective missing data prediction for collaborative filtering
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A Computer-Assisted Approach for Designing Context-Aware Ubiquitous Learning Activities
SUTC '08 Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008)
Context-Aware Computing Applications
WMCSA '94 Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications
Human-Computer Interaction
Designing educational experiences using ubiquitous technology
Computers in Human Behavior
International Journal of Business Information Systems
Hi-index | 0.00 |
As it is difficult for learners to discover and obtain the most appropriate resources from massive education resources according to traditional keyword searching method, the context-aware based resource recommendation service becomes a significant part of pervasive learning environments. At present, recommendation mechanisms are widely used in e-commerce field, where content-based or collaborative-based filter strategies are usually considered separately. However, in these existing recommendation mechanisms, the dynamic interests and preference of learners, the access pattern and the other attributes of pervasive learning environments (such as multi-modes connecting and resources distribution) are always neglected. Thus, these mechanisms can not effectively reflect learners' actual preference and can not adapt to pervasive learning environments perfectly. To address these problems, a context-aware resource recommendation model and relevant recommendation algorithm for pervasive learning environments are proposed. Therein, with taking into account the relevant contextual information, the calculation of relevant degree between learners and resources can be divided into two main parts: logic-based RRD (resource relevant degree) and situation-based RRD. In the first part, content-based and collaborative-based recommendation mechanisms are combined together, where the individual preference tree (IPT) is introduced to take into account the multi-dimensional attributes of resources, learners' rating matrix and the energy of access preference. Meanwhile, the learners' historical sequential patterns of resource accessing are also considered to further improve the accuracy of recommendation. In the second part, in order to enhance the validation of recommendation, the connecting type relevance and time satisfaction degree are calculated according to other relevant contexts. Then, the candidate resources can be filtered and sorted via combining these two parts to generate (Top-N) recommendation results. The simulations show that our newly proposed method outperforms other state of-the-art algorithms on traditional and newly presented metrics and it may also be more suitable for pervasive learning environments. Finally, a prototype system is implemented based on SEU-ESP to demonstrate the relevant recommendation process further.