Nicola Barbieri

Orcid: 0000-0002-1993-2946

According to our database1, Nicola Barbieri authored at least 37 papers between 2010 and 2021.

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Bibliography

2021
A Factorization Approach for Survival Analysis on Diffusion Networks.
IEEE Trans. Knowl. Data Eng., 2021

2018
Characterizing and Predicting Users' Behavior on Local Search Queries.
ACM Trans. Web, 2018

Click-through prediction when searching local businesses.
Proceedings of the 5th Spanish Conference on Information Retrieval, 2018

2017
Efficient Methods for Influence-Based Network-Oblivious Community Detection.
ACM Trans. Intell. Syst. Technol., 2017

Applying Space Syntax to Online Mapping Tools.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Click Through Rate Prediction for Local Search Results.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Evolution of Ego-networks in Social Media with Link Recommendations.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

Survival Factorization on Diffusion Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016
Modeling adoptions and the stages of the diffusion of innovations.
Knowl. Inf. Syst., 2016

Improving Post-Click User Engagement on Native Ads via Survival Analysis.
Proceedings of the 25th International Conference on World Wide Web, 2016

Validation of matching.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

The Role of Relevance in Sponsored Search.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
Efficient and effective community search.
Data Min. Knowl. Discov., 2015

2014
Probabilistic Approaches to Recommendations
Synthesis Lectures on Data Mining and Knowledge Discovery, Morgan & Claypool Publishers, ISBN: 978-3-031-01906-7, 2014

Analysing and Enriching Focused Semantic Web Archives for Parliament Applications.
Future Internet, 2014

Validation of Network Reconciliation.
CoRR, 2014

Influence Maximization with Viral Product Design.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Who to follow and why: link prediction with explanations.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Online Topic-aware Influence Maximization Queries.
Proceedings of the 17th International Conference on Extending Database Technology, 2014

2013
Probabilistic topic models for sequence data.
Mach. Learn., 2013

Topic-aware social influence propagation models.
Knowl. Inf. Syst., 2013

Cascade-based community detection.
Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013

Towards Topic-aware Social Influence Propagation Models.
Proceedings of the 21st Italian Symposium on Advanced Database Systems, 2013

CSI: Community-Level Social Influence Analysis.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Influence-Based Network-Oblivious Community Detection.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012
Hierarchical Latent Factors for Preference Data.
Proceedings of the Twentieth Italian Symposium on Advanced Database Systems, 2012

Balancing Prediction and Recommendation Accuracy: Hierarchical Latent Factors for Preference Data.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Probabilistic Sequence Modeling for Recommender Systems.
Proceedings of the KDIR 2012 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval, Barcelona, Spain, 4, 2012

2011
A Probabilistic Hierarchical Approach for Pattern Discovery in Collaborative Filtering Data (Extended Abstract).
Proceedings of the Sistemi Evoluti per Basi di Dati, 2011

A Probabilistic Hierarchical Approach for Pattern Discovery in Collaborative Filtering Data.
Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Modeling item selection and relevance for accurate recommendations: a bayesian approach.
Proceedings of the 2011 ACM Conference on Recommender Systems, 2011

An Analysis of Probabilistic Methods for Top-N Recommendation in Collaborative Filtering.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

A Block Coclustering Model for Pattern Discovering in Users' Preference Data.
Proceedings of the Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2011

Characterizing Relationships through Co-clustering - A Probabilistic Approach.
Proceedings of the KDIR 2011, 2011

Regularized Gibbs Sampling for User Profiling with Soft Constraints.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2011

2010
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data.
Proceedings of the IIR 2010, 2010

A Block Mixture Model for Pattern Discovery in Preference Data.
Proceedings of the ICDMW 2010, 2010


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