Francesco Bonchi spends much of his time researching Data mining, Artificial intelligence, Social network, Machine learning and Social graph. His Data mining research incorporates themes from Set, Monotone polygon and Pruning. His work deals with themes such as Network science, Dynamic network analysis and Viral marketing, which intersect with Artificial intelligence.
His research integrates issues of Link, Key and Set in his study of Social network. His research investigates the link between Machine learning and topics such as Topic model that cross with problems in Reduction. His Social graph study incorporates themes from Scalability and Interpersonal ties.
His scientific interests lie mostly in Data mining, Theoretical computer science, Graph, Social network and Artificial intelligence. His biological study deals with issues like Pruning, which deal with fields such as Monotone polygon. His research investigates the connection between Theoretical computer science and topics such as Set that intersect with problems in Approximation algorithm, Mathematical optimization and Greedy algorithm.
His Graph research is multidisciplinary, relying on both Betweenness centrality and Scalability. His studies deal with areas such as Key, Data science and Set as well as Social network. His Artificial intelligence research includes elements of Machine learning and Pattern recognition.
Francesco Bonchi mainly investigates Theoretical computer science, Graph, Vertex, Graph and Set. His Theoretical computer science research includes themes of Centrality, Graph drawing and Social network. Many of his research projects under Social network are closely connected to Matrix decomposition with Matrix decomposition, tying the diverse disciplines of science together.
He interconnects Contrast, Soundness, Task, Artificial intelligence and Online algorithm in the investigation of issues within Graph. His study in the fields of Sentence under the domain of Artificial intelligence overlaps with other disciplines such as Predictability. His Set research integrates issues from Algorithm, Approximation algorithm and Quadratic equation.
His primary areas of investigation include Graph, Theoretical computer science, Scalability, Centrality and Data collection. He has researched Graph in several fields, including Social media and Computational sociology. His work deals with themes such as Ranging, Graph, restrict and Viral marketing, which intersect with Theoretical computer science.
His Scalability research is multidisciplinary, incorporating perspectives in Graph summarization, Online algorithm and Cluster analysis. His study in Centrality is interdisciplinary in nature, drawing from both Variety, Duration, Relevance and Identification. His Vertex study combines topics from a wide range of disciplines, such as Upper and lower bounds, Computation and Partition.
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Learning influence probabilities in social networks
Amit Goyal;Francesco Bonchi;Laks V.S. Lakshmanan.
web search and data mining (2010)
Never Walk Alone: Uncertainty for Anonymity in Moving Objects Databases
O. Abul;F. Bonchi;M. Nanni.
international conference on data engineering (2008)
The query-flow graph: model and applications
Paolo Boldi;Francesco Bonchi;Carlos Castillo;Debora Donato.
conference on information and knowledge management (2008)
Topic-aware social influence propagation models
Nicola Barbieri;Francesco Bonchi;Giuseppe Manco.
Knowledge and Information Systems (2013)
Social Network Analysis and Mining for Business Applications
Francesco Bonchi;Carlos Castillo;Aristides Gionis;Alejandro Jaimes.
ACM Transactions on Intelligent Systems and Technology (2011)
Fast shortest path distance estimation in large networks
Michalis Potamias;Francesco Bonchi;Carlos Castillo;Aristides Gionis.
conference on information and knowledge management (2009)
A data-based approach to social influence maximization
Amit Goyal;Francesco Bonchi;Laks V. S. Lakshmanan.
very large data bases (2011)
Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining
Sara Hajian;Francesco Bonchi;Carlos Castillo.
knowledge discovery and data mining (2016)
Denser than the densest subgraph: extracting optimal quasi-cliques with quality guarantees
Charalampos Tsourakakis;Francesco Bonchi;Aristides Gionis;Francesco Gullo.
knowledge discovery and data mining (2013)
Mining Graph Evolution Rules
Michele Berlingerio;Francesco Bonchi;Björn Bringmann;Aristides Gionis.
european conference on machine learning (2009)
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