The Journal of Machine Learning Research
Pachinko allocation: DAG-structured mixture models of topic correlations
ICML '06 Proceedings of the 23rd international conference on Machine learning
LDA-based document models for ad-hoc retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A Comparative Study of Utilizing Topic Models for Information Retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Quantum latent semantic analysis
ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
Using the quantum probability ranking principle to rank interdependent documents
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
An investigation of quantum interference in information retrieval
IRFC'10 Proceedings of the First international Information Retrieval Facility conference on Adbances in Multidisciplinary Retrieval
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Recently, increasing attention has been given to a possible reinterpretation of information retrieval issues in the more general probabilistic framework offered by Quantum Theory. In this paper, we investigate the use of the well-known wave-like phenomenon of Quantum Interference for topic models such as Latent Dirichlet Allocation (LDA). We use interference effects in order to model interactions between latent topics. Our aim is to elaborate a way to build more precise document models starting from original LDA estimations. Experiments in ad-hoc retrieval show statistically significant improvements on several TREC collections.