An introduction to quantum computing for non-physicists
ACM Computing Surveys (CSUR)
A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
The Geometry of Information Retrieval
The Geometry of Information Retrieval
What can quantum theory bring to information retrieval
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Using the quantum probability ranking principle to rank interdependent documents
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Investigating query-drift problem from a novel perspective of photon polarization
ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
Modeling term dependencies with quantum language models for IR
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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Quantum theory (QT) has recently been employed to advance the theory of information retrieval (IR). A typical method, namely the Quantum Probability Ranking Principle (QPRP), was proposed to re-rank top retrieved documents by considering the interdependencies between documents through the "quantum interference". In this paper, we attempt to explore another important QT concept, namely the "quantum measurement". Inspired by the photon polarization experiment underpinning the "quantum measurement", we propose a novel reranking approach. Evaluation on several TREC data sets shows that in ad-hoc retrieval, our method can significantly improve the first-round ranking from a baseline retrieval model, and also outperform the QPRP.