Evaluation of Item-Based Top-N Recommendation Algorithms
Proceedings of the tenth international conference on Information and knowledge management
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
Being accurate is not enough: how accuracy metrics have hurt recommender systems
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Recommender systems and their impact on sales diversity
Proceedings of the 8th ACM conference on Electronic commerce
Introduction to Information Retrieval
Introduction to Information Retrieval
CARD: a decision-guidance framework and application for recommending composite alternatives
Proceedings of the 2008 ACM conference on Recommender systems
Analysis of Methods for Novel Case Selection
ICTAI '08 Proceedings of the 2008 20th IEEE International Conference on Tools with Artificial Intelligence - Volume 02
Statistical Modeling of Diversity in Top-N Recommender Systems
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Novel Item Recommendation by User Profile Partitioning
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Optimizing multiple objectives in collaborative filtering
Proceedings of the fourth ACM conference on Recommender systems
A unified framework for recommending diverse and relevant queries
Proceedings of the 20th international conference on World wide web
ACM Transactions on Interactive Intelligent Systems (TiiS)
A new collaborative filtering approach for increasing the aggregate diversity of recommender systems
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Who likes it more?: mining worth-recommending items from long tails by modeling relative preference
Proceedings of the 7th ACM international conference on Web search and data mining
Multi-objective mobile app recommendation: A system-level collaboration approach
Computers and Electrical Engineering
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In recent years it has been argued that, besides the standard accuracy metrics, other characteristics of the recommendation algorithm ought to be taken into account when evaluating recommendation performance. One such characteristic is recommendation diversity and this topic is the focus of this research project. The overall goal of the project is to examine ways to improve the diversity of recommendations while maintaining high accuracy. During the course of my work to date I have addressed the question of how best to evaluate diversification strategies and have proposed a number of new diversity enhancement algorithms.