Information filtering and information retrieval: two sides of the same coin?
Communications of the ACM - Special issue on information filtering
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Meta-recommendation systems: user-controlled integration of diverse recommendations
Proceedings of the eleventh international conference on Information and knowledge management
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
IEEE Transactions on Knowledge and Data Engineering
New Recommendation Techniques for Multicriteria Rating Systems
IEEE Intelligent Systems
The effects of transparency on trust in and acceptance of a content-based art recommender
User Modeling and User-Adapted Interaction
A Multi-Criteria Decision Method Based on Rank Distance
Fundamenta Informaticae
Tagommenders: connecting users to items through tags
Proceedings of the 18th international conference on World wide web
On the similarity metric and the distance metric
Theoretical Computer Science
A survey of collaborative filtering techniques
Advances in Artificial Intelligence
Assigning trust to Wikipedia content
WikiSym '08 Proceedings of the 4th International Symposium on Wikis
The problem of information overload in business organisations: a review of the literature
International Journal of Information Management: The Journal for Information Professionals
| Hi-index | 0.00 |
Information overload and an abundance of choices create situations where selecting one option becomes extremely difficult or even worse, a guessing game. Collaborative ranking systems are widely used to alleviate this problem by creating intelligent rankings of items based on an aggregation of user opinions. Current ranking systems can still be improved in a number of areas, including accuracy, transparency and flexibility. This paper presents a multi-criteria ranking algorithm that can be used on a non-rigid set of criteria. The system implementing the algorithm fares well with respect to the above qualities.