qontext

D. Song, Lalmas, M., van Rijsbergen, C. J., Frommholz, I., Piwowarski, B., Wang, J., Zhang, P., Zuccon, G., Bruza, P., Arafat, S., Azzopardi, L., Di Buccio, E., Huertas-Rosero, A., Hou, Y., Melucci, M., and Rueger, S., “How Quantum Theory is Developing the Field of Information Retrieval”, in AAAI-Fall 2010 Symposium on Quantum Informatics for Cognitive, Social, and Semantic Processes (QI 2010), Washington DC, USA, 2010, pp. 105-108.

A Quantum Model for the Ellsberg and Machina Paradoxes

D. Aerts, Sozzo, S., and Tapia, J., “A Quantum Model for the Ellsberg and Machina Paradoxes”, in QI, 2012, pp. 48-59.

D4.3

Submitted by BruzaP on Tue, 09/11/2012 - 09:27

The following paper provides the basis for a retrieval from memory based approach to abductive inference in relation to conceptual combinations:

Kitto, K., Bruza, P.D. and Gabora, L. (2012) A quantum information retrieval approach to memory. Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN 2012)

The following paper provides a basis for testing which conceptual combinations have a non-compositional semantics:

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A Visual Tool for Bayesian Data Analyisis: The Impact of Smoothing on Naıve Bayes Text Classifiers

{G. M. } Di Nunzio and Sordoni, A., “A Visual Tool for Bayesian Data Analyisis: The Impact of Smoothing on Naıve Bayes Text Classifiers”, in Proceeding of the 35th International ACM SIGIR 2012, Portland, Oregon, USA, 2012, p. 1002.

How Well do We Know Bernoulli?

{G. M. } Di Nunzio and Sordoni, A., “How Well do We Know Bernoulli?”, in Italian information Retrieval Workshop, 2012, vol. 835, pp. 38-44.

Leveraging Web 2.0 Data for Scalable Semi-supervised Learning of Domain-specific Sentiment Lexicons.

R. K. Lau and Bruza, P., “Leveraging Web 2.0 Data for Scalable Semi-supervised Learning of Domain-specific Sentiment Lexicons.”, in 20th ACM Conference on Information and Knowledge Management, 2011.

A quantum information retrieval approach to memory

K. Kitto, Bruza, P., and Gabora, L., “A quantum information retrieval approach to memory”, in International Joint Conference on Neural Networks (IJCNN 2012), Brisbane, Australia, 2012.

Quantum models of cognition and decision

J. Busemeyer and Bruza, P., Quantum models of cognition and decision. Cambridge University Press, 2012.

Tests and Models of Non-compositional Concepts

K. Kitto and Bruza, P., “Tests and Models of Non-compositional Concepts”, in 34th Annual Meeting of the Cognitive Science Society (CogSci 2012), Sapporo, Japan, 2012.

A Brief Account on the Recent Advances in the Use of Quantum Mechanics for Information Retrieval

M. Melucci, “A Brief Account on the Recent Advances in the Use of Quantum Mechanics for Information Retrieval”, in New Challenges in Distributed Information Filtering and Retrieval, vol. 439, C. Lai, Semeraro, G., and Vargiu, E., Eds. Springer Berlin / Heidelberg, 2013, pp. 1-14.

Search Engines and Rank Correlation

M. Melucci, “Search Engines and Rank Correlation”, vol. 4, Emerald, 2012, pp. 203–224.

Deriving a Quantum Information Retrieval Basis

M. Melucci, “Deriving a Quantum Information Retrieval Basis”, The Computer Journal, vol. 56, no. 11, 2013.

Tutorial on Quantum Information Access and Retrieval

Tutorial Information

Slides will be published soon.

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Modeling Emergent Associations of Nominal Compounds: Ongoing Research and Preliminary Results

M. Melucci and Sitbon, L., “Modeling Emergent Associations of Nominal Compounds: Ongoing Research and Preliminary Results”, in Proceedings of the Italian Information Retrieval workshop, 2011.

On Modeling Rank-Independent Risk in Estimating Probability of Relevance

P. Zhang, Song, D., Wang, J., Zhao, X., and Hou, Y., “On Modeling Rank-Independent Risk in Estimating Probability of Relevance”, in The Seventh Asia Information Retrieval Societies Conference (AIRS 2011), 2011.

Pure High-order Word Dependence Mining via Information Geometry.

Y. Hou, Zhao, X., He, L., and Song, D., “Pure High-order Word Dependence Mining via Information Geometry.”, in The 3rd International Conference on the Theory of Information Retrieval (ICTIR2011), Bertinoro, Italy, 2011.

Investigating Query-Drift Problem from a Novel Perspective of Photon Polarization.

P. Zhang, Song, D., Zhao, X., and Hou, Y., “Investigating Query-Drift Problem from a Novel Perspective of Photon Polarization.”, in The 3rd International Conference on the Theory of Information Retrieval (ICTIR2011), Bertinoro, Italy, 2011.

Contextual Image Annotation via Projection and Quantum theory Inspired Measurement for Integrating Text and Visual Features.

L. Kaliciak, Wang, J., Song, D., Zhang, P., and Hou, Y., “Contextual Image Annotation via Projection and Quantum theory Inspired Measurement for Integrating Text and Visual Features.”, in The 5th International Symposium on Quantum Interactions (QI2011), Aberdeen, UK, 2011.

How Concepts Combine: A Quantum Theoretic Modeling of Human Thought

Entanglement of Conceptual Entities in Quantum Model Theory (QMod)

How Quantum Theory is Developing the Field of Information Retrieval