User Modeling and User-Adapted Interaction
Course Sequencing for Static Courses? Applying ITS Techniques in Large-Scale Web-Based Education
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Preference formulas in relational queries
ACM Transactions on Database Systems (TODS)
Web-Based Adaptive Tutoring: An Approach Based on Logic Agents and Reasoning about Actions
Artificial Intelligence Review
Optimization of relational preference queries
ADC '05 Proceedings of the 16th Australasian database conference - Volume 39
Flexible integration of multimedia sub-queries with qualitative preferences
Multimedia Tools and Applications
Foundations of preferences in database systems
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Multi-objective query processing for database systems
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Querying with preferences in a digital library
Proceedings of the 2005 international conference on Federation over the Web
Learning services provisioning using semantic web technologies
Proceedings of the 1st International Conference on Intelligent Semantic Web-Services and Applications
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We address the problem of generating entire course sequences, given a set of target skills along with possibly prioritized student preferences over course descriptions. Compared to logic frameworks formulating course sequencing as a planning problem, our work relies on a set-theoretic framework for generating course sequences using preference-based queries. We introduce the concept of ordered partition for sequencing, and the ordered product of partitions, when it is necessary to combine more than one preference orderings. In our context, ordered partitions originate from preferences expressed over general relations, rather than on functional attributes of traditional database tuples (or objects) addressed by other approaches. We believe that the proposed framework is expressive enough to produce course sequences from descriptions expressed in diverse data models (e.g., XML, RDF/S) with respect to a variety of user preferences, also including priorities over the preferences.