Preference structure, inference and set-oriented retrieval
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
A probabilistic model of information retrieval: development and comparative experiments
Information Processing and Management: an International Journal
Document language models, query models, and risk minimization for information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
On Event Spaces and Probabilistic Models in Information Retrieval
Information Retrieval
Probabilistic optimized ranking for multimedia semantic concept detection via RVM
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
On event space and rank equivalence between probabilistic retrieval models
Information Retrieval
Building a framework for the probability ranking principle by a family of expected weighted rank
ACM Transactions on Information Systems (TOIS)
| Hi-index | 0.00 |
This paper presents a new perspective of the probability ranking principle (PRP) by defining retrieval effectiveness in terms of our novel expected rank measure of a set of documents for a particular query. This perspective is based on preserving decision preferences, and it imposes weaker conditions on PRP than the utility-theoretic perspective of PRP.