Nicola Barbieri

发表

Auction Theory meets Collective Intelligence : Towards Designing Next-Generation Community Question Answering Systems

G. Iosifidis, Nicola Barbieri, 2013 .

Probabilistic topic models for sequence data

G. Manco, E. Ritacco, Nicola Barbieri, 2013, Machine Learning.

Efficient Methods for Influence-Based Network-Oblivious Community Detection

Nicola Barbieri, Francesco Bonchi, Giuseppe Manco, 2016, ACM Trans. Intell. Syst. Technol..

Efficient and effective community search

Nicola Barbieri, Francesco Bonchi, Francesco Gullo, 2015, Data Mining and Knowledge Discovery.

Influence-Based Network-Oblivious Community Detection

Nicola Barbieri, Francesco Bonchi, Giuseppe Manco, 2013, 2013 IEEE 13th International Conference on Data Mining.

CSI: Community-Level Social Influence Analysis

Yasir Mehmood, Nicola Barbieri, Francesco Bonchi, 2013, ECML/PKDD.

Cascade-based community detection

Nicola Barbieri, Francesco Bonchi, Giuseppe Manco, 2013, WSDM.

Efficient and effective community search

Francesco Gullo, F. Bonchi, Nicola Barbieri, 2015, Data mining and knowledge discovery.

Click-through prediction when searching local businesses

Nicola Barbieri, Fidel Cacheda, Fidel Cacheda, 2018, CERI.

Characterizing and Predicting Users’ Behavior on Local Search Queries

Roi Blanco, Nicola Barbieri, Fidel Cacheda, 2018, ACM Trans. Web.

Click Through Rate Prediction for Local Search Results

Roi Blanco, Nicola Barbieri, Fidel Cacheda, 2017, WSDM.

Evolution of Ego-networks in Social Media with Link Recommendations

Nicola Barbieri, Luca Maria Aiello, L. Aiello, 2017, WSDM.

A Factorization Approach for Survival Analysis on Diffusion Networks

Nicola Barbieri, Ettore Ritacco, Giuseppe Manco, 2021, IEEE Transactions on Knowledge and Data Engineering.

Who to follow and why: link prediction with explanations

Nicola Barbieri, Francesco Bonchi, Giuseppe Manco, 2014, KDD.

Probabilistic Approaches to Recommendations

Nicola Barbieri, Ettore Ritacco, Giuseppe Manco, 2014, Probabilistic Approaches to Recommendations.

Survival Factorization on Diffusion Networks

Nicola Barbieri, Ettore Ritacco, Giuseppe Manco, 2017, ECML/PKDD.

Topic-aware social influence propagation models

Nicola Barbieri, Francesco Bonchi, Giuseppe Manco, 2012, Knowledge and Information Systems.

The Role of Relevance in Sponsored Search

Nicola Barbieri, Xiao Bai, Ricardo Baeza-Yates, 2016, CIKM.

Applying Space Syntax to Online Mapping Tools

Daniele Quercia, Nicola Barbieri, Yandi Li, 2017, WSDM.

An Analysis of Probabilistic Methods for Top-N Recommendation in Collaborative Filtering

Nicola Barbieri, Giuseppe Manco, G. Manco, 2011, ECML/PKDD.

Online Topic-aware Influence Maximization Queries

Nicola Barbieri, Ricardo Baeza-Yates, Francesco Bonchi, 2014, EDBT.

Influence Maximization with Viral Product Design

Nicola Barbieri, Francesco Bonchi, F. Bonchi, 2014, SDM.

Improving Post-Click User Engagement on Native Ads via Survival Analysis

Fabrizio Silvestri, Nicola Barbieri, Mounia Lalmas, 2016, WWW.

Modeling item selection and relevance for accurate recommendations: a bayesian approach

Nicola Barbieri, Gianni Costa, Riccardo Ortale, 2011, RecSys '11.

Balancing Prediction and Recommendation Accuracy: Hierarchical Latent Factors for Preference Data

Nicola Barbieri, Riccardo Ortale, Ettore Ritacco, 2012, SDM.

Analysing and Enriching Focused Semantic Web Archives for Parliament Applications

Diana Maynard, Thomas Risse, Nicola Barbieri, 2014, Future Internet.

Probabilistic Approaches to Recommendations

G. Manco, E. Ritacco, Nicola Barbieri, 2014, Probabilistic Approaches to Recommendations.

A Block Mixture Model for Pattern Discovery in Preference Data

Nicola Barbieri, Massimo Guarascio, Giuseppe Manco, 2010, 2010 IEEE International Conference on Data Mining Workshops.

2012 IEEE 12th International Conference on Data Mining Topic-aware Social Influence Propagation Models

Nicola Barbieri, Francesco Bonchi, Giuseppe Manco, 2022 .

Regularized Gibbs Sampling for User Profiling with Soft Constraints

Nicola Barbieri, Nicola Barbieri, 2011, 2011 International Conference on Advances in Social Networks Analysis and Mining.

Characterizing Relationships through Co-clustering - A Probabilistic Approach

Nicola Barbieri, Gianni Costa, Ettore Ritacco, 2011, KDIR.

A Probabilistic Hierarchical Approach for Pattern Discovery in Collaborative Filtering Data (Extended Abstract)

Nicola Barbieri, Ettore Ritacco, Giuseppe Manco, 2011, SEBD.