A threshold of ln n for approximating set cover
Journal of the ACM (JACM)
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Beyond independent relevance: methods and evaluation metrics for subtopic retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
When will information retrieval be "good enough"?
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Less is more: probabilistic models for retrieving fewer relevant documents
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Learning diverse rankings with multi-armed bandits
Proceedings of the 25th international conference on Machine learning
Novelty and diversity in information retrieval evaluation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Rank-biased precision for measurement of retrieval effectiveness
ACM Transactions on Information Systems (TOIS)
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Efficient Computation of Diverse Query Results
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
An Effectiveness Measure for Ambiguous and Underspecified Queries
ICTIR '09 Proceedings of the 2nd International Conference on Theory of Information Retrieval: Advances in Information Retrieval Theory
Probabilistic models of ranking novel documents for faceted topic retrieval
Proceedings of the 18th ACM conference on Information and knowledge management
Top-k retrieval using facility location analysis
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Explicit relevance models in intent-oriented information retrieval diversification
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Preference based evaluation measures for novelty and diversity
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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A useful ability for search engines is to be able to rank objects with novelty and diversity: the top k documents retrieved should cover possible intents of a query with some distribution, or should contain a diverse set of subtopics related to the user's information need, or contain nuggets of information with little redundancy. Evaluation measures have been introduced to measure the effectiveness of systems at this task, but these measures have worst-case NP-hard computation time. The primary consequence of this is that there is no ranking principle akin to the Probability Ranking Principle for document relevance that provides uniform instruction on how to rank documents for novelty and diversity. We use simulation to investigate the practical implications of this for optimization and evaluation of retrieval systems.