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Conference Paper
R. Liu, Wang, W. Hui, Monreale, A., Pedreschi, D., Giannotti, F., and Guo, W., AUDIO: An Integrity ıt Audi}ting Framework of ıt O}utlier-Mining-as-a-Service Systems, in ECML/PKDD (2), 2012.
R. Baraglia, Morales, G. De Francis, and Lucchese, C., Document Similarity Self-Join with MapReduce, in Proceedings of the 2010 IEEE International Conference on Data Mining, 2010.
N. Tonellotto, Macdonald, C., and Ounis, I., Efficient and effective retrieval using selective pruning, in Proceedings of the sixth ACM international conference on Web search and data mining, New York, NY, USA, 2013.
G. De Francis Morales, Gionis, A., and Lucchese, C., From chatter to headlines: harnessing the real-time web for personalized news recommendation, in Proceedings of the fifth ACM international conference on Web search and data mining, New York, NY, USA, 2012.
A. Freire, Macdonald, C., Tonellotto, N., Ounis, I., and Cacheda, F., Hybrid query scheduling for a replicated search engine, in Proceedings of the 35th European conference on Advances in Information Retrieval, Berlin, Heidelberg, 2013.
C. Macdonald, Tonellotto, N., and Ounis, I., Learning to predict response times for online query scheduling, in Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval, New York, NY, USA, 2012.
D. Broccolo, Macdonald, C., Ounis, I., Orlando, S., Perego, R., Silvestri, F., and Tonellotto, N., Load-Sensitive Selective Pruning for Distributed Search, in ACM CIKM '13, 2013.
K. Garimella, Morales, G. De Francis, Gionis, A., and Mathioudakis, M., Quantifying Controversy in Social Media, in Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, New York, NY, USA, 2016.
K. Garimella, Morales, G. De Francis, Gionis, A., and Mathioudakis, M., Quantifying Controversy in Social Media, in Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, New York, NY, USA, 2016.
Journal Article
N. Forgó, Hänold, S., van den Hoven, J., Krügel, T., Lishchuk, I., Mahieu, R., Monreale, A., Pedreschi, D., Pratesi, F., and van Putten, D., An ethico-legal framework for social data science, 2020.
N. Forgó, Hänold, S., van den Hoven, J., Krügel, T., Lishchuk, I., Mahieu, R., Monreale, A., Pedreschi, D., Pratesi, F., and van Putten, D., An ethico-legal framework for social data science, 2020.
M. Berlingerio, Coscia, M., Giannotti, F., Monreale, A., and Pedreschi, D., Evolving networks: Eras and turning points, Intell. Data Anal., vol. 17, pp. 27-48, 2013.
D. Broccolo, Marcon, L., Nardini, F. Maria, Perego, R., and Silvestri, F., Generating suggestions for queries in the long tail with an inverted index, Information Processing & Management, vol. 48, pp. 326–339, 2012.
A. Monreale, Andrienko, G. L., Andrienko, N. V., Giannotti, F., Pedreschi, D., Rinzivillo, S., and Wrobel, S., Movement Data Anonymity through Generalization, Transactions on Data Privacy, vol. 3, pp. 91-121, 2010.
F. Giannotti, Lakshmanan, L. V. S., Monreale, A., Pedreschi, D., and Wang, H., Privacy-preserving Mining of Association Rules from Outsourced Transaction Databases, IEEE Systems Journal, 2013.
M. Berlingerio, Coscia, M., Giannotti, F., Monreale, A., and Pedreschi, D., The pursuit of hubbiness: Analysis of hubs in large multidimensional networks, J. Comput. Science, vol. 2, pp. 223-237, 2011.
C. Macdonald, Ounis, I., and Tonellotto, N., Upper-bound approximations for dynamic pruning, ACM Trans. Inf. Syst., vol. 29, pp. 17:1–17:28, 2011.