SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Distributed content-based visual information retrieval system on peer-to-peer networks
ACM Transactions on Information Systems (TOIS)
Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Data mining in course management systems: Moodle case study and tutorial
Computers & Education
Flexible Recommendations for Course Planning
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Clustering and Sequential Pattern Mining of Online Collaborative Learning Data
IEEE Transactions on Knowledge and Data Engineering
Short Chosen-Prefix Collisions for MD5 and the Creation of a Rogue CA Certificate
CRYPTO '09 Proceedings of the 29th Annual International Cryptology Conference on Advances in Cryptology
A hybrid of sequential rules and collaborative filtering for product recommendation
Information Sciences: an International Journal
Exploiting peer relations for distributed multimedia information retrieval
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Mining changes in customer buying behavior for collaborative recommendations
Expert Systems with Applications: An International Journal
Social tagging in recommender systems: a survey of the state-of-the-art and possible extensions
Artificial Intelligence Review
Recsplorer: recommendation algorithms based on precedence mining
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
A new collaborative filtering metric that improves the behavior of recommender systems
Knowledge-Based Systems
Workshop on recommender systems for technology enhanced learning
Proceedings of the fourth ACM conference on Recommender systems
Evaluating, combining and generalizing recommendations with prerequisites
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Recommendation based on object typicality
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Exploring folksonomy and cooking procedures to boost cooking recipe recommendation
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Recommendation systems with complex constraints: A course recommendation perspective
ACM Transactions on Information Systems (TOIS)
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Recent development in multimedia e-learning technologies
World Wide Web
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With the rapid development of online learning technology, a huge amount of e-learning materials have been generated which are highly heterogeneous and in various media formats. Besides, e-learning environments are highly dynamic with the ever increasing number of learning resources that are naturally distributed over the network. On the other hand, in the online learning scenario, it is very difficult for users without sufficient background knowledge to choose suitable resources for their learning. In this paper, a hybrid recommender system is proposed to recommend learning items in users' learning processes. The proposed method consists of two steps: (1) discovering content-related item sets using item-based collaborative filtering (CF), and (2) applying the item sets to sequential pattern mining (SPM) algorithm to filter items according to common learning sequences. The two approaches are combined to recommend potentially useful learning items to guide users in their current learning processes. We also apply the proposed approach to a peer-to-peer learning environment for resource pre-fetching where a central directory of learning items is not available. Experiments are conducted in a centralized and a P2P online learning systems for the evaluation of the proposed method and the results show good performance of it.