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Bibliography

Found 105 results
2013
S. Li, El-Saddik, A., Wang, M., Mei, T., Sebe, N., Yan, S., Hong, R., and Gurrin, C., Eds., Advances in Multimedia Modeling, 19th International Conference, MMM 2013, Huangshan, China, January 7-9, 2013, Proceedings, Part I, MMM (1), vol. 7732. Springer, 2013.
E. Di Buccio and Nunzio, G. M. D., Are There New BM25 Expectations?, in IIR, 2013, pp. 1-12.
E. Di Buccio and Di Nunzio, {G. M. }, Are there new BM25 Expectations?, in Italian information Retrieval Workshop, 2013.
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.
L. Kaliciak, Song, D., Wiratunga, N., and Pan, J., Combining Visual and Textual Systems within the Context of User Feedback, in MMM (1), 2013, pp. 445-455.
E. Di Buccio, Nunzio, G. M. D., and Silvello, G., A curated and evolving linguistic linked dataset, Semantic Web, vol. 4, pp. 265-270, 2013.
M. Melucci, Deriving a Quantum Information Retrieval Basis, The Computer Journal, vol. 56, no. 11, 2013.
E. Di Buccio, Melucci, M., and Moro, F., Detecting verbose queries and improving information retrieval, Information Processing & Management, p. -, 2013.
M. Melucci, Initial Specifications for the Design of Information Retrieval Systems Based on Quantum Detectors Using Kinds, in Proceedings of Quantum Interaction, 2013.
Y. Hou, Zhao, X., Song, D., and Li, W., Mining pure high-order word associations via information geometry for information retrieval, ACM Trans. Inf. Syst., vol. 31, p. 12, 2013.
E. Di Buccio and Nunzio, G. M. D., More Than Words: A Review of Planets, Stars and Sample Spaces, in ICTIR, 2013, p. 27.
{G. M. } Di Nunzio and Sordoni, A., Picturing Bayesian Classifiers: A Visual Data Mining Approach to Parameters Optimization, in Data Mining Applications with R, Y. Zhao and Cen, Y., Eds. Elsevier, 2013, p. In press.
P. D. Bruza, Kitto, K., Ramm, B. J., and Sitbon, L., A probabilistic framework for analysing the compositionality of conceptual combinations, CoRR, vol. abs/1305.5753, 2013.
D. Aerts, Broekaert, J., Gabora, L., and Sozzo, S., Quantum Structure and Human Thought, Behavioural and Brain Science, 2013.
X. Zhao, Hou, Y., Yu, Q., Song, D., and Li, W., Understanding Deep Learning by Revisiting Boltzmann Machines: An Information Geometry Approach, CoRR, vol. abs/1302.3931, 2013.
E. Di Buccio and Nunzio, G. M. D., A Visual Analysis of the Effects of Assumptions of Classical Probabilistic Models, in ICTIR, 2013, p. 28.

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